# Survey on Terahertz Nanocommunication and Networking: A Top-Down Perspective

Filip Lemic1, Sergi Abadal2, Wouter Tavernier3, Pieter Stroobant3, Didier
Colle3,
Eduard Alarcón2, Johann Marquez-Barja1, Jeroen Famaey1
Email<EMAIL_ADDRESS>1Internet Technology and Data Science Lab
(IDLab), Universiteit Antwerpen - imec, Belgium
2NaNoNetworking Center in Catalunya (N3Cat), Universitat Politècnica de
Catalunya, Spain
3Internet Technology and Data Science Lab (IDLab), Ghent University - imec,
Belgium

###### Abstract

Recent developments in nanotechnology herald nanometer-sized devices expected
to bring light to a number of groundbreaking applications. Communication with
and among nanodevices will be needed for unlocking the full potential of such
applications. As the traditional communication approaches cannot be directly
applied in nanocommunication, several alternative paradigms have emerged.
Among them, electromagnetic nanocommunication in the terahertz (THz) frequency
band is particularly promising, mainly due to the breakthrough of novel
materials such as graphene. For this reason, numerous research efforts are
nowadays targeting THz band nanocommunication and consequently nanonetworking.
As it is expected that these trends will continue in the future, we see it
beneficial to summarize the current status in these research domains. In this
survey, we therefore aim to provide an overview of the current THz
nanocommunication and nanonetworking research. Specifically, we discuss the
applications envisioned to be supported by nanonetworks operating in the THz
band, together with the requirements that such applications pose on the
underlying nanonetworks. Subsequently, we provide an overview of the current
contributions on the different layers of the protocol stack, as well as the
available channel models and experimentation tools. As the final contribution,
we identify a number of open research challenges and outline several potential
future research directions.

###### Index Terms:

Nanotechnology, electromagnetic, terahertz, nanocommunication, nanonetworking,
protocols, channel models, experimentation tools.

##  I Introduction

“There’s Plenty of Room at the Bottom: An Invitation to Enter a New Field of
Physics” [1] was the title of a visionary lecture given by the Nobel Prize
recipient Prof. Richard Feynman at the annual American Physical Society
meeting at the California Institute of Technology (Caltech) in December 1959.
Prof. Feynman discussed the possibility of directly manipulating materials on
an atomic scale - and he surely wasn’t joking. The concepts originally
outlined by Prof. Feynman later became circumscribed under the term
“nanotechnology”, first introduced by Prof. Norio Taniguchi from Tokyo
University of Science in 1974. Due to substantial research efforts in recent
years, nanotechnology is today paving the way toward sub-$\mu$m scale devices
(i.e., from one to a few hundred nanometers). Controlling materials on such a
scale is expected to give rise to integrated nanodevices with simple sensing,
actuation, data processing and storage, and communication capabilities,
opening the horizon to a large variety of novel, even groundbreaking
applications.

Communication and coordination among the nanodevices, as well as between them
and the macro-scale world, will be required to achieve the full promise of
such applications. Thus, several alternative nanocommunication paradigms have
emerged in the recent years, the most promising ones being electromagnetic,
acoustic, mechanical, and molecular communication [2].

In molecular nanocommunication, a transmitting device releases molecules into
a propagation medium, with the molecules being used as the information
carriers [3]. Acoustic nanocommunication utilizes pressure variations in the
(fluid or solid) medium to carry information between the transmitter and
receiver. In mechanical (i.e., touch-based) nanocommunication, nanorobots are
used as carriers for information exchange [4]. Finally, electromagnetic
nanocommunication uses the properties of electromagnetic waves (e.g.,
amplitude, phase, delay) as the information carriers [5]. Among the above
paradigms, molecular and electromagnetic nanocommunication show the greatest
promise for enabling communication between nanodevices [6]. This work focuses
on electromagnetic nanocommunication. This is due to the fact that it is among
the two most promising nanocommunication paradigms, as well as due to its
suitability to different propagation mediums (e.g., in-body, free space, on-
chip) and potential for meeting the applications’ requirements (more details
in Section III).

Classical electromagnetic communication and networking paradigms are not
directly applicable to the majority of nanoscale communication and networking
scenarios, predominantly due to the small sizes and limited capabilities of
nanodevices [7, 8]. That it to say, microwave or even millimeter-wave (mmWave)
frequencies impose relatively large antennas (i.e., mm-scale and larger) that
do not fit into nanodevices. To meet the size requirements of nanodevices, a
classical metallic antenna would be required to use very high radiation
frequencies. For example, a one-micrometer-long dipole antenna would resonate
at approximately 150 terahertz (THz) [9]. Although the communication bandwidth
increases with the increase in the antenna’s resonance frequency, the same
happens with the propagation loss. Due to the highly constrained power of
nanodevices [10], the feasibility of nanonetworks would be compromised if this
approach would be adopted. In addition, nanoscale material properties of
common metals are unknown, hence the common assumptions from antenna theory
might not be correct [11]. Finally, it is currently also technologically
infeasible to develop miniature transceiver that could operate at such high
frequencies [9].

As an alternative approach, graphene has attracted substantial research
attention, mainly due to its unique electrical and optical properties [12].
The interaction of electromagnetic radiation with graphene and its derivatives
(i.e., carbon nanotubes (CNT) [13] \- rolled graphene and graphene nanoribbons
(GNRs) - thin strips of graphene), differs from that of the conventional
metals. Specifically, it has been demonstrated that graphene supports the
propagation of Surface Plasmon Polariton (SPP) waves in the THz frequency band
[14, 15, 15, 16]. Due to that, graphene-enabled electromagnetic
nanocommunication in the THz frequencies is able to deliver miniaturization
[17, 18], i.e., a prerequisite for nanocommunication. In addition, the
possibility to operate at lower frequencies relaxes the energy and power
requirements for the nanodevices [9, 17]. Moreover, graphene shows unique
tunability properties, which allow to steer the beam or tune the resonance
frequency by just changing a bias voltage [18, 19]. For these reasons and
given its experimentally demonstrated compatibility with CMOS manufacturing
processes [20, 21, 22], graphene allows versatile antennas to be directly
integrated in nanocommunication devices as envisaged in multiple works [5, 23,
19]. Consequently, graphene-enabled THz nanocommunication attracted
substantial attention from a broad scientific community.

As the efforts targeting THz band nanocommunication yielded highly encouraging
results, the research focus soon spread from the communication to the
networking community, giving birth to nanonetworking in the THz band. Suffice
to say, the results of these efforts are equally encouraging and promising, at
this point arguably also abundant. Hence, we believe a summary of the research
efforts and current State-of-the-Art (SotA) on THz nanocommunication and
nanonetworking would be beneficial to the community, which provides the main
motivation for this survey.

In this survey, we first discuss several application domains that could be
enabled by nanonetworks operating in the THz band. These include software-
defined metamaterials, wireless robotic materials, body-centric communication,
and Wireless Networks-on-Chip. Moreover, we derive a set rule-of-thumb
requirements that each of the application domains posits on the supporting
nanonetworks. Then, we utilize a top-down approach in discussing the SotA of
different layers of the nanonetworks’ protocol stack. We believe a top-down
approach to be more natural than the bottom-up alternative, as it provides the
reader with a straightforward mapping between the application requirements on
the one side, and the underlying protocols and their design goals on the
other. In addition, we provide an overview of existing channel models and
simulation and experimentation tools available for THz nanocommunication and
nanonetworking research. At the end of each section, we discuss the
corresponding research “gaps” and open challenges. Moreover, we summarize
several additional open challenges related to THz nanocommunication and
nanonetworking in general, but not directly pertaining to specific layers of
the protocol stack, channel models, or experimentation tools. We aim to
provide a straightforward introduction to THz nanocommunication and
nanonetworking research, as well at as to identify the “missing pieces” in the
current results and suggest potential future research directions.

###  I-A Methodology

This survey has been developed following the Systematic Literature Review
(SLR) methodology [24, 25]. We aimed to select all the relevant works in the
context of THz nanocommunication and nanonetworking, in turn resulting in the
detection of the open challenges and missing “pieces” in the existing research
literature. We have considered the following inclusion criteria: i) an article
proposes a full novel solution rather than conceptual, informative, or ongoing
efforts (i.e., position, poster, demo, and Work-in-Progress (WiP) articles
were not considered), ii) an article went through a peer-review process and is
either publicly available (e.g., in ArXiv) or included in the Web of Science
(WoS), Scopus, IEEEXplore, ACM, and/or Springer databases, and iii) an article
is written in English. In terms of the step-by-step methodology, we have used
the Google Scholar database in the initial review phase, during which the
articles were included or excluded based on their titles and abstracts. In the
consequent step, the full texts were assessed along the above-mentioned
inclusion criteria. As a commonly accepted practice, we have placed extra
emphasis on articles published since 2015, highly cited ones, and the ones
published in the most important venues, e.g., IEEE Transactions on
Nanotechnology, ELSEVIER’s Nano Communication Networks, IEEE Nanotechnology
Magazine, and ACM International Conference on Nanoscale Computing and
Communication (ACM NANOCOM).

###  I-B Structure

The rest of this paper is structured as follows. In Section II, we provide an
overview of the related surveys in the existing literature. The application
domains that could potentially be supported by nanonetworks operating in the
THz band are, together with the requirements such applications pose on the
underlying nanonetworks, discussed in Section III. The current research
efforts on the network, link, and physical layers of the protocol stack are
summarized in Sections IV, V, and VI, respectively. Moreover, in Section VII
we discuss the available channel models for THz nanocommunication, while the
existing experimentation and simulation tools are outlined in Section VIII. In
Section IX, we discuss several more general open challenges, i.e., the ones
not directly related to the content of the previous sections, yet still
relevant to THz nanocommunication and nanonetworking research. Finally, we
conclude the survey in Section X.

##  II Related Work

There are several contributions generically targeting THz band communication
[26, 27, 28]. They provide useful insights into the paradigm from the device’s
perspective, as well as from the communication point of view. In terms of
communication, advances and challenges pertain to channel modeling,
development of communication protocols, and establishment of supporting
experimentation tools and facilities.

There are also several specialized survey papers that discuss different
aspects of THz band nanocommunication. The pioneering work targeting this
topic was published by Akyildiz and Jornet [5], providing an in-depth view on
nanotechnology and discussing several options for enabling communication among
nanonodes. In [5], the authors take the nanodevice standpoint and first
outline the envisioned architecture of the nanodevice, consisting of units for
sensing, actuating, powering, data processing and storage, and communication.
The authors follow by outlining several application groups for Wireless Nano-
Sensor Networks: biomedical, environmental, industrial and consumer goods, and
military and defense. Moreover, they briefly discuss the architecture of a
WNSN consisting of nanonodes, nanorouters, nano-micro interfaces, and
gateways. In addition, several open research questions and promising
directions for future research are outlined. It is worth mentioning that the
survey is dated to 2010.

TABLE I: Surveys on THz band communication and networking Name | Year | Type |  Summary of covered topics
---|---|---|---
Akyildiz  _et al._ [29] | 2010 | Internet of Nano-Things |  SotA in THz nanocommunication for the IoNT; research challenges (channel modeling, information encoding, and protocols for the IoNT).
Akyildiz  _et al._ [5] | 2010 | THz nanocommunication |  SotA in nanodevice technology; summaries of WNSN applications and architectures; overview of nanocommunication and networking challenges.
Jornet  _et al._[30] | 2012 | Internet of Nano-Things |  SotA, open challenges, and research directions in the THz nanocommunication and Internet of Multimedia Nano-Things (IoMNT).
Rikhtegar  _et al._ [8] | 2013 | THz nanocommunication |  Molecular and electromagnetic (THz) communication for nanoscale applications; summary of nanoscale communication paradigms and potential applications.
Balasubramaniam  _et al._ [31] | 2013 | Internet of Nano-Things |  Challenges in realizing the IoNT (data collection and routing, bridging the outside world and nanonetworks, etc.); possible IoNT applications.
Akyildiz  _et al._ [27] | 2014 | THz communication |  THz band applications at macro and nanoscale; SotA in THz band transceivers and antennas; open challenges from communication and networking perspectives; simulation and experimentation tools for THz band communication.
Akyildiz  _et al._ [26] | 2014 | THz communication |  SotA in THz band transceivers and antennas; open challenges from communication and networking perspectives.
Akyildiz  _et al._ [32] | 2015 | Internet of Nano-Things |  Introduction to the Internet of Bio-Nano Things (IoBNT); bridging the outside world and the IoBNT; open challenges in the IoBNT.
Miraz  _et al._ [33] | 2015 | Internet of Nano-Things |  Short overview and future research directions pertaining to the Internet of Things (IoT), Internet of Everything (IoE), and Internet of Nano-Things (IoNT).
Dressler  _et al._ [34] | 2015 | Internet of Nano-Things |  Bridging the outside world and in-body nanonodes for health-care applications; IoNT network architectures; simulation tools for in-body nanonetworks.
Petrov  _et al._ [28] | 2016 | THz communication |  SotA in THz band communication; engineering trade-offs in typical applications; open challenges and research directions in THz band communication.
Alsheikh  _et al._ [35] | 2016 | THz nanocommunication |  Existing MAC protocols for WNSN; performance analysis and design guidelines for WNSN MAC protocols.
Rizwan  _et al._ [36] | 2018 |  | Nanocommunication in
---
healthcare
Nanosensors and nanonetworks for healthcare systems; big data analytics (data
sources, preprocessing, feature extraction, visualization, predictive
modelling)
Ghafoor  _et al._ [37] | 2019 | THz communication |  Features of the THz band; THz macro and nanoscale applications; design requirements for THz MAC protocols; classification of existing MAC protocols; open challenges for MAC protocols.
This survey | 2021 | THz nanocommunication |  THz nanoscale applications; THz nanocommunication and nanonetworking protocols; THz nanoscale channel models; simulation and experimentation tools

It is also worth noting the work in [8], which provides an overview of
molecular and electromagnetic nanocommunication. In addition, [36] briefly
discusses electromagnetic communication from a stand-point of future
healthcare systems, with the main focus of the work being big data analytics
for healthcare data. In terms of electromagnetic nanocommunication utilizing
THz frequencies, [8] provides similar insights as [5]. Moreover, in [35], the
authors provide a comparative survey of different Media Access Control (MAC)
protocols for WNSN. In [37], the authors provide a survey of MAC protocols for
THz band communication in general. In addition, performance analyses of these
protocols have been carried out in terms of consumed energy, transmission
distance, and probability of collisions.

Several contributions target different aspects of the IoNT, most notably [29,
30, 31, 34, 33, 32]. In these works, the authors tend to agree on the IoNT
architecture, consisting of a nanonetwork connected to the macro-world through
a nano-macro gateway. In addition, several application domains have been
outlined in these works, which can roughly be grouped into health-care,
environmental and agricultural monitoring, multimedia, and military and
defense. Moreover, the works converge toward the idea that there are two
encouraging nanocommunication options, namely molecular and electromagnetic
utilizing THz frequencies. The former is predominantly feasible for in-body
nanocommunication. Among the above-mentioned contributions targeting IoNT,
arguably the most relevant ones for this survey are [34] and [30]. The work in
[34] is interesting as it summarizes several requirements for
nanocommunication for enabling in-body health-care applications. These pertain
to legal (e.g., legislation on duration of the body contact, invasiveness or
implantability of nanodevices), functional (i.e., the purpose of communication
between nanonetwork and macro-world), and technical (e.g., reliability,
safety, privacy, real-time capabilities) requirements. The work is also
relevant because it discusses several challenges for in-body
nanocommunication, as well as useful simulation tools for the problem at hand.
Jornet _et al._ [30] provide a relevant read due to the fact that it
explicitly outlines nanocommunication challenges in the multimedia-focused
IoNT. These challenges pertain to data compression and signal processing, THz
channel modeling, and challenges on different layers of the protocol stack.

In order to position our work in the context of the above-outlined
contributions (summarized in Table I), it is first relevant to note that these
contributions, apart from [37, 36], date from 2016 or before. Several novel
proposals have been made on various aspects of THz nanocommunication and
nanonetworking in the recent years, ranging from novel protocols in different
layers, to THz channel modeling and experimentation tools. We believe that at
this point in time a critical summary of these contributions and their
positioning in regard to the older ones would benefit the scientific
community. Second, some of the current surveys focus either on THz
communication in general or on nanocommunication, resulting in neglecting
numerous aspects relevant to THz band electromagnetic nanocommunication.
Adversely, other contributions are substantially more focused, targeting for
example only the IoNT or MAC layer protocols for THz band (nano)communication.
Third, due to its very recent roll-out with the most important works being
only a few years old, THz band nanonetworking has not received sufficient
treatment in the existing surveys. We aim at filling the above-stated gaps by
providing a full view on the problem, ranging from applications and their
requirements, different layers of the protocols stack, channel models, and
experimentation tools, to challenges and open research questions, but
pertaining exclusively to electromagnetic nanocommunication and nanonetworking
in the THz band.

Finally, it is worth emphasizing that this work does not cover THz macro-scale
applications, protocols, nor channel models. Interested readers are directed
to several recent papers surveying these topics, e.g., [38, 39, 40, 41, 42].
In addition, this survey deals with electromagnetic nanocommunication only.
Hence, molecular and other potential paradigms for nanocommunication and
networking are out of scope of this paper. Interested readers can find more
details in recent surveys from the literature [43, 44, 45, 46, 47]. Similarly,
THz nanocommunication hardware-related aspects are out of scope of this work.
Although arguably not abundant, existing survey papers discuss aspects such as
THz sources [48, 49], graphene antennas [19, 50], and circuits/devices [51,
52].

##  III Application Domains Enabled by THz Nanonetworks

In this section, we provide an overview of the most prominent application
domains with the potential of being enabled by THz-operating nanonetworks. For
each of the domains, we discuss its requirements, which are at the end of the
section summarized in Table II. Note that in the table we include the most
stringent requirements for each application domain, although these can
potentially be more lenient for some applications in the domain. Also note
that we differentiate the application domains based on their requirements. For
example, we distinguish wireless robotic materials and body-centric
communication, although both domains contain a variety of sensing-only
applications. Due to that, some works from the literature (e.g., [53, 32])
specify WNSNs or IoNT as applications that could potentially be enabled by THz
band nanonetworks, which is in our case “embedded” in some of the specified
application domains.

###  III-A Software-Defined Metamaterials

Metamaterials (and metasurfaces, their two-dimensional counterparts [54]) are
manufactured structures that enable powerful control of electromagnetic waves.
As such, metamaterials can be used to realize devices with engineered and even
unnatural properties related to the reflection, absorption, or transmission of
electromagnetic radiation. For instance, metamaterials have been proposed for
the electromagnetic cloaking of objects [55], noise [56] cancellation,
holography [57], anomalous reflection [58], and focusing of energy with
unprecedented accuracy [59]. Such unprecedented control is achieved through
the careful design of a periodic array of subwavelength elements typically
called _unit cells_. The main issue with current metamaterials, however, is
that the unit cells are “hard-coded” for a single application and operational
condition (e.g., to work for a single angle of incidence) and cannot be reused
across applications nor reprogrammed for different operations. To alleviate
this issue, Liaskos _et al._ [60] proposed Software-Defined Metamaterials, a
new paradigm of programmable metamaterials where the unit cells can be
reconfigured through a software interface with a set of well-defined
instructions.

By virtue of the unprecedented and real-time control of the absorption,
reflection, and transmission characteristics of metasurfaces, the SDM approach
is expected to enable a plethora of applications in areas such as sensing,
communications, or imaging [61]. In wireless communications, SDMs have been
proposed as a basic building block of _intelligent reflecting surfaces_
enabling the revolutionary concept of _programmable wireless environments_
[62, 63]. By controlling the reflection and scattering profiles at selected
spots, both propagation loss and multipath effects can be mitigated in any
wireless channel. This has proven to be a true paradigm shift in wireless
communications, as the recent explosion of works can attest [64, 65, 66, 67],
because the channel has been traditionally an inescapable limiting factor.
Another application related to wireless communications is the development of
simplified architectures for wireless communication transmitters [68]. There,
the metasurfaces are utilized to directly modulate the carrier wave in
multiple channels using the baseband signal without the need of core
components of the RF chain such as mixers, filters, amplifiers, which can
become hard to realize at high frequencies. Finally, we also highlight the
applicability of SDMs in the area of holographic imaging, where real-time
programmability opens the door to dynamic holograms with outstanding spatial
resolution given by the subwavelength granularity of the unit cells [69].

Fundamentally, the behavior of SDMs hinges on the collective response of each
of its subwavelength unit cells. To enable the reprogramming without
compromising the autonomy of the metamaterial, the SDM paradigm proposes to
embed a communication network of controllers within the metamaterial, as shown
in Figure 1. In such a scenario, each controller interacts locally with its
associated unit cells to adjust its properties and communicates with other
unit cells to obtain or distribute the desired behavior. However, the
subwavelength scale the SDM unit cells poses a frequency-dependent form-factor
limit on the internal network of controllers. In this context, to enable the
SDM applications in a wide range of frequencies, nanocommunications in the THz
band becomes a desired paradigm to implement the communication between the
unit cell controllers within an SDM [70]. Depending on the actual application,
the number of unit cells can range from thousands to millions [70, 71],
translating to a similar number of controllers in the THz nanonetwork. Their
exact number will depend on the physical sizes of the SDMs and the final
application, which in some predictions could cover the walls of an entire
office for the programmable wireless environment case [64]. Moreover, the
controllers will have to be interconnected for better adaptation and operative
range purposes. Due to the small form-factor and a huge number of envisioned
controllable metamaterials comprising an intra-SDM network, the energy
consumption of each metamaterial and consequently of the intra-SDM network
will have to be low. Owing to practical reasons, these metamaterials will only
have energy harvesting capabilities, with capacitor-based storage instead of
batteries.

Figure 1: Envisioned high-level architecture for enabling software-defined
metamaterials [72]

Currently, a first wave of SDM designs is under development to showcase the
capabilities of this new technology [61]. The latency requirements are
expected to be relaxed in this first stage, i.e., between a few milliseconds
and a few seconds [70]. Moreover, very simple controllers and intra-SDM
network infrastructure will be deployed in first prototypes. The network
traffic is expected to be downlink mostly, predominantly used for controlling
the behavior of metamaterials. Moreover, the initial phase envisions no
mobility, i.e., the metamaterials and network nodes are expected to be static.
Low reliability of data delivery will presumably suffice and the security is
not expected to play an important role [70]. This is mainly because, in the
current stage, the aim is to deliver a proof of concept of the SDM paradigm.

To the best of our knowledge, derivations in regard to the performance
requirements for SDMs in their roll-out phase are scarce in the current
literature [73, 74] and we make a brief analysis here based on the discussions
within [61]. In essence, the SDM is a programmable metasurface with a control
sub-system that modifies the response of the metasurface at a given maximum
rate that depends on the application. In holographic displays, SDMs should be
programmable at the typical refresh rates of displays, this is, around 60
times per second. In wireless programmable environments, SDMs need to be fast
enough to adapt to changes in the channel due to mobility or other phenomena,
which typically occur at the 1-100 milliseconds scale. Finally, in SDMs used
as wireless communication transmitters, the required refresh rate of the
metasurface is thus the modulation rate of the transmitter.

The figures above allow us to make an estimation of the performance
requirements of intra-SDM networks. On the one hand, the intra-SDM
communication latency needs to be a fraction of the required refresh time: in
the millisecond range for holographic displays and programmable wireless
environments and below for metasurface-based wireless transmitters. With
respect to the throughput, we can assume that an SDM module will consist of
10000 unit cells and will cover an area of 100 cm2 based on recent estimates
[64, 68]. If the range of an individual intra-SDM controller operating in THz
frequencies is 1 cm, roughly 10x10 interconnected controllers are needed for
controlling the whole metamaterial. Say that every 100 ms the metamaterial
elements have to be updated and that this update is performed in a flood-like
multi-hop fashion using a byte-long command, starting from a controller
positioned in one corner of the metamaterial surface. Note that a byte-long
command has been selected as most EM functionalities can be achieved with 8-16
states [75]. Under these assumptions, the number of hops until all controllers
are reached equals $2\times(10-1)\times 10=180$. Note that each transmission
between controllers can potentially also be utilized by instrumenting the
metamaterials controlled by the controller, hence we arrive to the required
minimal data throughput of 1800 transmissions per sec = 14.4 kbps. Arguably,
the signaling overhead in such scenario is relatively low and, to further
simplify the analysis, we can assume that the network throughput equals the
data throughput. Note that, due to a variety of simplifications made in our
derivations, the derived value should be used only as a very rough indication
of the minimum required network throughput. With that in mind, we can then
provide a rule of thumb estimate of the required network throughput in the
order of 1 to 50 kbps (Table II).

As the SDM technology evolves, new prototypes will arise that explore its full
potential. Demonstrations of mission-critical applications with stronger
timing requirements on the order of microseconds are expected [70, 61].
Moreover, SDMs are also envisioned to become wearable, thus having the ability
to bend, stretch, and roll [54]. For the supporting network, this will
represent an additional requirement in terms of shape resiliency and operation
in high mobility scenarios. For enabling mission-critical applications and
although SDMs show certain resilience to faults [76], the reliability of
communication will have to be high, while some guarantees for security will
also have to be in place. For supporting a variety of potential applications
in this domain, addressing will be required on a level of an individual
controller, or even on the level of an individual metamaterial element. For
similar reasons, the communication links will have to be bidirectional
enabling communication from the user to the SDM unit cells and vice versa, as
well as among SDM unit cells to implement distributed sensing and intelligence
within the device [61]. In terms of throughput and using the same approach for
analysis as before and using 10 ms and 10 $\mu$s as the metamaterial unit
update period, we arrive to a minimum required network throughputs of 144 kbps
and 144 Mbps, respectively. Hence, roughly speaking the required network
throughput for SDMs of the second generation will be in the range of 50 kbps
to 500 Mbps. Note that in the derivation we assumed that each transmission
between controllers is simultaneously used as a command for controlling the
corresponding metamaterials. For more detailed traffic analyses, we refer the
reader to [73].

###  III-B Wireless Robotic Materials

In contrast to SDMs that are envisioned to control electromagnetic waves,
wireless robotic materials are expected to enable smart composites that
autonomously change their shape, stiffness, or physical appearance in a fully
programmable way [77, 78]. The term wireless robotic material has been coined
in [77, 79]. They define the robotic materials as multi-functional composites
that tightly integrate sensing, actuation, computation, and communication to
create smart composites that can sense their environment and change their
physical properties in an arbitrary programmable manner. The applications that
the authors in [77] suggest are airfoils that change their aerodynamic
profile, vehicles with camouflage abilities, bridges that detect and repair
damage, or robotic skins and prosthetics with a realistic sense of touch.
Similarly, the authors in [79] envision applications such as tactile sensing
skin, robots (i.e., nanodevices) that can reproduce patterns projected onto
them for camouflage, and a dress that can localize the direction of incoming
sound and display it to its wearer. Several promising applications envisioned
to be enabled by wireless robotic materials are depicted in Figure 2.

As argued in [79], the envisioned applications will require very large swarms
of nanodevices tightly integrated into fabric, on skin, etc. This poses
limitations in terms of the size of the elements of robotic materials,
yielding the THz band as one of the most promising communication paradigms for
controlling these elements. Moreover, the network size and density will be
largely influenced by the application that the network is envisioned to
support. We believe that the application of enabling camouflage abilities will
require the largest (i.e., covering an entire vehicle or human body) and most
dense networks. Nonetheless, the requirements for network size and node
density are expected to be less pronounced than for the SDMs, primarily due to
the expected difference in sizes of the robotic materials (a few millimeters)
and metamaterials (potentially much smaller than 1 mm).

In terms of network traffic, the authors in [79] argue that the envisioned
sensors and actuators embedded in wireless robotic materials could generate
information ranging from binary (e.g., for enabling distributed gesture
recognition [80]) to a few-hundreds-of-hertz-bandwidth signals (e.g.,
localized texture recognition by robotic skin [81]). Let us provide a simple
calculation for deriving for supported traffic load by the network of wireless
robotic materials. Similar to the previous calculations, we make a vague
assumption that a robotic material patch will consist of 100 elements that
have to be updated every 20 ms, which is the assumption taken from the Tactile
Internet use-cases [82] in which the network latency has to be comparable to
the human observational abilities. Furthermore, we assume that this update is
performed in a flood-like multi-hop fashion, starting/ending at the
source/sink node positioned in the corner of the wireless robotic material
patch. Under these assumptions and following the same approach as before, the
network traffic needed for controlling the wireless robotic material patch
then equals 450 kbps and 3.6 Mbps for control signals carrying 1 and 8 bits of
information, respectively. Utilizing the numbers, we estimate that the network
throughput of roughly between 100 kbps and 10 Mbps will be needed for enabling
the wireless robotic materials-related applications. Note that, intuitively,
the network will have to support bidirectional traffic, primarily for enabling
the vision of sensing and actuating networks [83].

Figure 2: Example applications of wireless robotic materials

As summarized in Table II, the reliability of data delivery in the networks
enabling wireless robotic materials will have to be high for some
applications, e.g., for detecting and repairing damage on bridges, ceilings,
and other “critical” structures. Taking the same application as an example,
the security of data transmission will have to be high for the above-mentioned
applications. The applications also involve wearable electronics, “smart”
dresses, and artificial skin, all being carried by a person. Hence, the
mobility is expected to be very high for some of the applications. In some
cases, there will be a need to localize the nodes of the network under such
mobility conditions, e.g., for localized texture recognition by robotic skin
[81]. Furthermore, some applications will tolerate cluster-based addressing of
nodes (e.g., bridge repairs), while some others may require individual
addressing (e.g., camouflage). Finally, the energy consumption of the devices
and consequently in the networks will in some cases have to be low, e.g., when
the devices are expected to have long lifetime such as in construction
monitoring scenarios. However, since these devices are expected to be larger
than the metamaterials discussed above, their energy efficiency and power
profile requirements are not expected to be as stringent as for the
metamaterials. Although the larger robotic materials could be powered by
smaller batteries, for the smaller robotic materials and dense networks the
authors in [79] suggest to use energy scavenging and harvesting [84].

Note that in the literature, researchers often make a distinction between
wireless robotic materials and wireless nanosensor networks. We find such a
distinction unnecessary, given that we separate different applications based
on the requirements they pose on the supporting nanonetwork. Wireless
nanosensor networks have been proposed in [53] and envision applications such
as high-resolution environmental monitoring [85], wearables [86], nanocameras-
based extreme spatial resolution recordings [87], nanoscale imaging [88], and
the Internet of Multimedia Nano-Things [30]. Nonetheless, these applications
can be viewed as a sensing-only subset of applications enabled by the wireless
robotic materials, hence we do not group them into a separate category.

###  III-C In-body Communication

Mobile medical nanodevices are a promising technology for in-situ and in-vivo
applications [89, 90]. These nanodevices will be access small regions of the
human body (e.g., gastrointestinal, brain, spinal cord, blood capillaries,
inside the eye), while essentially being non-invasive. The authors in [89]
argue that mobile medical nanodevices could even enable access to
unprecedented sub-millimeter size regions inside the human body, which have
not been possible to access currently with any medical device technology.
Similarly, the authors in [91] envision: “therapeutic nanomachines able to
operate either in inter- and intra-cellular areas of the human body“. By doing
so, pioneering applications, such as immune system support, bio-hybrid
implant, drug delivering system, health monitoring, and genetic engineering,
will be enabled, argue the authors. The authors in [2] envision applications
such as human physical movement monitoring, early diagnosis and treatment of
malicious agents (e.g., viruses, bacteria, cancer cells), bone-growth
monitoring in diabetes patients, and organ, nervous track, or tissue
replacements (i.e., bio-hybrid implants). Finally, the authors in [92] outline
several example applications that could be supported by THz nanonetworks, such
as smart drug administration, nanoscale surgeries, and epidemic spread
detection and management.

As indicated in Figure 3, the nanodevices would be able to perform sensing
(e.g., blood composition or functioning of specific organs) and actuation
(e.g., targeted drug delivery), all while reporting or being controlled from
the outside world. Obviously, the form-factor of these nanodevices will be of
prime importance, again yielding THz band communication as one of the most
suitable communication paradigms. The number of mobile medical nanodevices is
expected to be very large (up to a billion according to some estimations [93])
for some applications (e.g., for tissue engineering or detecting bacteria via
swarms of sub-millimeter-scale nanodevices).

Figure 3: Envisioned high-level architecture for enabling body-centric
applications

The amount of traffic that the network of mobile medical nanodevices will have
to support will largely depend on the application. Given that the aim of the
nanodevice is to enter and sense/influence something in sub-millimeter regions
inside the human body, the main goals of the network will be to deliver this
information to the outside world and to support the control of the nanodevice.
The network per-se will be formed by only a set of devices relaying the
information to/from the outside world. However, given that the aim of a swarm
of medical nanodevices is to sense a variety of events inside of a body (e.g.,
the presence of a bacteria) or to form a tissue, the supporting network will
arguably be mesh-like. The nanodevices will in this case also need to create
control loops with the outside world, hence the network will have to operate
under real-time constraints. Let us assume one such scenario, i.e., a swarm of
mobile nanodevices is sensing a human brain and potentially creating an
artificial tissue if there is damage in the brain. Roughly speaking, the
network is distributed across the area of 1000 cm3 and consists of 106 mobile
nanodevices (a relatively conservative assumption), each one sending or
receiving 8 bits of information every 20 msec. We assume flood-based
distribution of traffic from or toward the outside world. Utilizing similar
calculation approach as before, we come to the staggering number of
transmissions which equals roughly 3$\times$106 transmissions/s, resulting in
the network throughput of 24 Mbps. Along the above derivation, the required
network throughput for enabling body-centric applications will - as a rule of
thumb - be in the range between 1 and 50 Mbps.

The body-centric communication related network requirements are arguably the
most challenging among the applications potentially supported by THz band
communication, as summarized in Table II. In addition to large network sizes,
high throughput requirements, and in-body propagation of signals, the energy
consumption of the nanodevices and consequently the networks supporting their
operation have to be very low, primarily due to the required small form-factor
of the devices. Hence, these nanodevices are presumably going to use energy
harvesters are their only energy source. Moreover, the reliability of
communication will have to be very high (e.g., for controlling medical
nanodevices in a brain), while the end-to-end latencies will have to be very
low for enabling real-time control of the nanodevices. Obviously, the security
of communication will have to be very high, especially for the ones envisioned
to stay in a person’s body for a longer period (e.g., for monitoring
purposes). This is to avoid the nanodevices being “hijacked” by the attackers,
while the patient is not being in a controlled environment shielded from the
potential attackers. In cases when the nanonetworks are not extremely large,
the addressing will have to be individual in order to e.g., control the
movements of a particular nanodevice [89]. Moreover, the nanodevices are
envisioned to be localizable and traceable [89] for enabling localized sensing
and movement control of the nanodevices. Finally, due to both blood streams in
a person’s body and potential movement of the person (primarily the relative
movement of person’s body parts respective to one another), the nodes are
expected to be highly mobile, which poses an additional challenge for the
supporting nanonetworks [89].

Note that the above example, as well as the requirements that the applications
are expected to pose on the supporting nanonetworks, have been derived for the
most challenging applications. In contrast to the other promising application
domains discussed in this work, for in-body communication there are several
recent efforts targeting the derivation of network requirements for only
certain applications in the domain. In this direction, the interested reader
is referred to [94, 95], where the authors derive the achievable throughput as
a function of various network parameters such as transmission rate and
nanonodes’ available energy. The work was carried out assuming flow-guided
nanonetworks (i.e., the ones operating in the blood circulatory system).
Moreover, the work was extended in [96] to demonstrate the feasibility of
flow-guided nanonetworks in enabling low throughput applications such as viral
load monitoring, restenosis, sepsis and bacterial blood infections, and heart
attacks. Moreover, the authors in [92] qualitatively distinguish nanonetwork
requirements based on the high-level function of the applications. They
envision the monitoring, detection, and therapy-related functionalities,
however without providing quantitative characterizations.

###  III-D On-chip Communication

Virtually all processors nowadays are based on multi-core architectures where
a single chip contains multiple independent processor cores and a given amount
of on-chip memory. The different processors compute in parallel and use the
memory to share data and synchronize their executions. In this context, the
current trend to increase performance is to integrate more cores within the
same chip [97]. This, however, places an increased burden to the on-chip
interconnect, which is used to send control signals and move shared data
across the chip, to the point of turning intra-chip communication into the key
determinant of the processor’s computational performance and energy efficiency
[98]. Hence, substantial research efforts focused on the on-chip
interconnects, with initial bus-based interconnects soon giving way to more
efficient and resilient Networks-on-Chip. Initially, NoCs were wired
solutions, which posed challenges in terms of delay, power requirements, and
area overhead as more cores were integrated within a single chip [99, 100,
101]. This has prompted the proposal of multiple alternative interconnect
technologies [102, 101], among which we find wireless on-chip communications.

TABLE II: Summary of requirements in different application domains Requirements | Software-defined metamaterials | Wireless robotic materials |  In-body communication | On-chip communication
---|---|---|---|---
| Gen. 1 |  Gen. 2 |  |  |
Network size |  $10^{3}$ to $10^{6}$ |  $10^{9}$ | 10 to 106 |  103 to 109 | Up to 103
Node density | 100 to 10000 nodes per cm2 | 1 to 100 nodes per cm2 |  $>$103 nodes per cm3 | 10-100 per mm2
Latency | ms to s |  $\mu$s | ms |  ms to s | 10-100 ns
Throughput | 1-50 kbps |  50 kbps to 500 Mbps | 100 kbps-10 Mbps |  1-50 Mbps | 10-100 Gbps
Traffic type | downlink |  bidirectional | bidirectional |  bidirectional | bidirectional
Reliability | low |  medium | high |  very high | very high
Energy consumption | very low |  very low | low |  very low | low
Mobility | none |  medium to high | high |  high | none
Addressing | none to cluster |  individual | cluster to individual |  individual | individual
Security | none |  low to medium | high |  very high | medium
Additional features |  |  | localization |  in-body communication |
|  |  |  |  localization & tracking |

The advantages of employing wireless communication for intra-chip networks
include reduced propagation delay, reconfigurability, and improved scalability
in terms of latency, throughput, and energy consumption [103, 104].
Nevertheless, as shown in Figure 4, current WNoCs are predominantly utilized
for long-range point-to-point links for decreasing the average hop count of
traditional NoC solutions. In other words, WNoC are currently deployed for
enhancing the wired NoC, mostly due to the relatively large sizes of the
metallic antennas required for enabling wireless communication in the mmWave
band, which has generally been assumed in this context. Recently, Abadal _et
al._ [105] proposed the employment of nanoscale WNoCs by means of graphene
nanoantennas. Graphene-based nanoantennas with sizes of only a few
micrometers, i.e., two orders of magnitude below the dimensions of metallic
antennas, could provide inter-core communication utilizing the THz
frequencies. Moreover, the antennas are inherently tunable, providing new ways
to reconfigure the network. This novel approach is expected to fulfill the
stringent requirements of the area-constrained, latency-bound, and throughput-
intensive on-chip communication. This concept has recently been further
developed [106, 107].

Figure 4: Envisioned high-level architecture for enabling on-chip
communication [105]

In the envisioned multicore on-chip communication, on-chip traffic typically
consists of a mixture of short control messages employed for cache coherence,
data consistency, and synchronization purposes, together with larger data
transfers. The communication is clearly bidirectional, while the addressing in
the network has to be individual, as reflected in Table II. Depending on the
memory access patterns exhibited by the application, communication will have
varying degrees of unicast, multicast, and broadcast transmissions. Note, for
instance, that some applications have strong all-to-all communication
patterns. Although latency is the primary concern in on-chip communications,
as delays in the serving of packets essentially delay the whole computation,
throughput is an important metric to avoid throttling of the computing cores.
The recent literature reports the on-chip network throughput requirement in
the range of 10-100 Gbps [98, 108], which can be further pushed to the Tbps
barrier in communication-intensive architectures such as accelerators [109].

As mentioned above, the WNoC scenario has very challenging end-to-end latency
requirements in the range of sub-$\mu$s [98] with high reliability (typical
Bit-Error-Ratios lower than $10^{-15}$ [110, 98] to compete with that of on-
chip wires). As the chips are generally shielded, security issues related to
on-chip communication are not of paramount importance. In the unlikely event
of hardware trojans being present within the chip, several lightweight
measures can be taken to avoid spoofing, eavesdropping, or Denial of Service
(DoS) attacks [111]. Moreover, although the chips are expected to be mobile,
the relative locations of the nodes on a chip are not going to change. In that
sense, there is no mobility of network nodes that should be anticipated. Due
to very small sizes of the chips, the energy efficiency of the network should
be high. This is to avoid overheating of the chip due to high energy
dissipation [112]. $\blacksquare$

A summary of the requirements that different application domains pose on the
supporting communication networks is given in Table II. Compared to other
application domains, software-defined metamaterials posit the least stringent
constrains for the majority of requirements. This pertains to the throughput
and security requirements, as well as the traffic type and mobility support.
On-chip communication can be considered as a relatively unique application
domain as the topology of a network and propagation characteristics can be
considered as static and known upfront [113]. Nonetheless, compared to other
domains, this domain poses the most stringent constraints in terms of node
density, delivery latency, achievable throughput, and reliability of
communication. We have mentioned before that electromagnetic nanocommunication
can be utilized in different propagation mediums, in contrast to molecular
nanocommunication. In addition, we’ve stated that electromagnetic
communication in THz frequencies, primarily due to graphene, can support
device minimization and antenna tunability, in contrast to mmWave, microwave,
and other electromagnetic frequency bands. Due to that and in contrast to
other paradigms, electromagnetic nanocommunication in THz frequencies is a
promising candidate for supporting all of the discussed application domains.

In theory, the THz band can support very large bit-rates, up to several Tbps.
However, it is clear from the discussion above and Table II that such
throughputs will not be required for enabling the envisioned applications
domains. Nonetheless, a very large bandwidth enables new simple communication
mechanisms suited for the expected limited capabilities of nanodevices,
primarily in terms of their energy levels [114]. In addition, a large
bandwidth enables the development of efficient medium sharing schemes [115],
which can both enable low energy performance and scale to the required numbers
and densities of the nanonodes. In addition, it is worth emphasizing again
that the THz frequency band is “the last piece of RF spectrum puzzle” [116].
Hence, the interferences from other communication sources in the same
frequencies are currently virtually non-existent. In the future, they are
expected to be very low, due to the low utilization, high attenuation, and
large bandwidth of the THz frequency band [116]. This suggests that highly
reliable nanocommunication, which is required by several of the outlined
application domains, can be enabled by utilizing the THz band.

The above considerations suggesting the potential for low power, highly
scalable, and reliable communication make a strong argument in favor of using
electromagnetic nanocommunication in the THz frequency band for supporting the
desired application domains. Certainly, there are unresolved challenges to be
addressed, and one aim of this survey is to detect, summarize, and discuss
them.

##  IV Network Layer

The network layer functionality is responsible for enabling data communication
between connected THz nanonodes at arbitrary distance from each other. To
enable such communication, nanonodes might rely on intermediate nanonodes
(hops) to forward information. Forwarding functionality might be available for
all or a subset of nanonodes. Routing functionality ensures that (collective)
forwarding behaviour results into successful paths between data sources and
destinations. The nanonodes therefore might rely on mechanisms to be
identified and/or addressed, either individually or as a group (e.g., based on
their physical location). Due to hardware limitations in transceivers,
traditional routing, forwarding, and addressing schemes are often not
applicable. Traditional routing protocols, as used in e.g., the Internet, rely
on the exchange of control or meta messages to learn and distribute
information about the network topology or reachability. However, memory,
channel, and energy restrictions in nanonetworks impose stringent requirements
on the relay, forwarding, and routing functionalities. These constraints are
similar to those encountered in the domain of Wireless Sensor Networks. Some
THz routing protocols expand upon conventional mechanisms by incorporating
THz-specific link models when deciding between various paths (e.g., by
incorporating molecular absorption loss). However, an additional challenge of
routing in THz nanonetworks is the scale, since the majority of WSN routing
protocols are optimized for up to 200 motes [117], while some of the
application domains enabled by THz nanonetworks require significantly larger
number of nanonodes, as summarized in Table II. In addition, in many
applications nanonodes are more prone to failures than sensor motes, as their
only powering option is to harvest energy from the available environmental
sources. Therefore, other research efforts take application-specific
information into account for settings which are outside the scope of WSNs.

Below we provide an overview on existing research categorized according to the
core mechanism they rely on. Figure 5 depicts an overview of our approach.
Subsection IV-A discusses forwarding and relaying methods. These works focus
on whether to transmit a packet directly to a hop which is further away, or
whether to relay the information via one or more intermediary nanonodes. The
other subsections focus on algorithms aiming at finding the nanonodes that
should send and/or forward a packet in order to reach one or more destinations
(i.e., routing). Subsection IV-B focuses on flooding-based mechanisms, which
are used for one-to-many routing. Subsections IV-C and IV-D discuss one-to-one
routing in regular and irregular topologies, respectively.

THz Network Layer Protocols Relaying & Forwarding (Sect. IV-A) Xia _et al._
[118] Rong _et al._ [119] Yu _et al._ [120] PESAWNSN [121] Pierobon _et al._
[122] Cánovas-Carrasco _et al._ [123] Cánovas-Carrasco _et al._ [124] Routing
Flooding-based routing (Sect. IV-B) Liaskos _et al._ [125] Tsioliaridou _et
al._ [126] Afsana _et al._ [127] LENWB [128] Buther _et al._ [129] E3A [130]
Pathfinding Regular topologies (Sect. IV-C) Radetzki _et al._ [131] Maze
routing [132] Fukushima _et al._ [133] Jovanovic _et al._ [134] Ebrahimi _et
al._ [135] Saeed _et al._ [136] Irregular topologies (Sect. IV-D) Tsioliaridou
_et al._ [137] Tsioliaridou _et al._ [138]

Figure 5: Classification of network layer protocol for THz nanocommunication

###  IV-A Relaying and Forwarding for THz Nanonetworks

Enabling multi-hop communication in THz nanonetworks introduces design
restrictions at the lower layers. Xia and Jornet [118] mathematically
characterize relaying strategies maximizing network throughput with respect to
transmission distance, transmission power energy and packet generation rate in
a THz band network consisting of nanonodes with directional antennas. The
unique characteristics of THz communication are considered by modeling the
distance-dependent and frequency-selective characteristics of molecular
absorption. To reduce the BER of cooperative relaying strategies in WNSNs,
amplify-and-forward and decode-and-forward relaying nanonodes are evaluated by
Rong _et al._ [119], whilst taking into account spreading and molecular
absorption losses. Using the former forwarding technique, relaying nanonodes
amplify the received signal as it is, whilst using the latter technique,
relaying nanonodes demodulate the signal before it is forwarded. The bit error
rate of both schemes is compared to that of direct transmission, and a
relaying gain of approximately 2.2 dB was observed for amplify-and-forward and
5 dB for decode-and-forward. As molecular absorption and other frequency-
selective features seriously hamper multi-hop throughput in the THz band, Yu
_et al._ [120] propose channel-aware forwarding schemes in WNSNs, ensuring
that data will not be forwarded to: i) a relaying nanonode in a region which
is adversely affected by molecular absorption, or ii) to a short-distant
nanonode, which will result in unnecessarily large hop count. Compared to
direct transmission, the authors report an increase of end-to-end capacity by
a factor 12-13, whilst limiting the delay increase to less than 0.02%.
Similarly accounting for molecular absorption, Yen  _et al._ [121] combine
signal quality-aware forwarding with data aggregation in WNSNs, while also
taking free path space loss into account. Data aggregation (e.g., taking the
minimum of received values) in intermediary nanonodes is often possible,
depending on the particular application (e.g., if only the lowest value is
needed). The resulting design problem is formulated as an optimization of
routing decisions, for which an efficient heuristic has been proposed for
calculating minimum cost spanning trees considering transmission power and
signal quality.

Energy efficiency is crucial in THz band nanonetworks. The throughput
attainable in a these environments is therefore strongly related to the
associated nanoscale energy harvesting processes. Pierobon _et al._ [122]
present a hierarchical cluster-based architecture for WNSNs, extending their
work on MAC protocols [115]. Each cluster is assumed to have a nanocontroller,
which is a nanonode with more advanced capabilities and which can transmit
directly to all nanonodes (when given sufficient transmission power). The
nanocontroller is in charge of optimizing the trade-off between multi-hop
forwarding among individual nanonodes vs. communication via the nanocontroller
from the perspective of throughput and lifetime of the network and its
associated connectivity. Based on the probability of energy saving through
multi-hop transmission, the nanocontroller instructs nanonodes what
transmission power to use for optimal hop distance and throughput, as well as
selects the next hop on the basis of their energy and current load. Both total
path loss and molecular absorption loss are considered in modeling the
channel. For nanonodes at a distance of 1 to 10 mm, the authors find that the
total energy spent per bit halves using forwarding as compared to direct
transmission, whilst the delay improves by a factor 3-4.

Another similar hierarchical architecture with a focus on energy management is
proposed by Cánovas-Carrasco _et al._ ([123] and [124]). Concretely, a body
area network is proposed, compromising a large number of nanonodes injected
into the bloodstream and thus always moving. These nanonodes communicate with
one or more nanorouters, which are more powerful devices implanted under the
skin. The nanorouters in turn connect to an Internet gateway. The first of
these works [123] focuses on a scenario in which a nanorouter is implanted in
a human hand. The work discusses a molecular absorption loss model which takes
the different layers of tissues inside the hand into account. Also, it
proposes concrete power supply components which harvest energy from the
bloodstream itself and from an external ultrasound source (the ultrasound-
based power source also allows nanonodes to detect whether they are in
vicinity of the nanorouter). The authors estimate that each nanonode is able
to send a 40 bit packet every 52 minutes. [124] considers a scenario in which
the nanonodes report events with different levels of importance. A Markov
Decision Process (MDP) for the transmission policy of a nanonode is proposed,
the states of which take the type of event detected by the nanonodee into
account, as well as the battery level and the distance between the nanonode
and the last detected nanorouter. The authors compare their approach to
policies in which all events are transmitted, only high priority events are
transmitted or a decision whether to report an event is made based on an
estimate of the nanonode’s power level when reaching the next nanorouter. The
throughput of the proposed approach always exceeds the throughput of any other
policy by at least a couple of percents. Moreover, as events become more
frequent, the advantage of the MDP over the other approaches becomes more
pronounced.

###  IV-B Flooding-based Routing

Baseline THz nanonetworking mechanisms are in essence direct extensions of MAC
protocols which rely on flooding to deliver data to their intended
destinations. Flooding involves unconditional packet retransmission by all
involved nanonodes. Advantages of flooding include its simplicity, its
reliability through redundant transmissions and a lack of (topology-dependent)
initialization, making it a good choice for applications with mobile
nanonodes. Unfortunately, unmodified flooding involves a high number of
redundant transmissions.

Therefore, several efforts have been undertaken to mitigate the number of
redundant transmissions by limiting the involvement of particular nanonodes or
through selectively forwarding in a probabilistic manner. Liaskos _et al._
[125] adopt an adaptive flooding scheme where wireless nanonodes in a static
environment can deactivate themselves based on their perceived signal to
interference ratio and resource levels and thus create a dynamic flooding
infrastructure. Compared to fine-tuned probabilistic flooding, the proposed
scheme achieves an improvement of approximately 10% in packet rate to achieve
full network coverage and a similar latency. It also manages to fully remove
interference effects. Tsioliaridou _et al._ [126] follow a similar mechanism
relying on the Misra-Gries algorithm to determine if each nanonode should act
as user or retransmitter. Concretely, each incoming packet is classified as
(i) suffering from a parity error, (ii) a duplicate of an earlier received
packet, (iii) a correctly decoded packet which is received for the first time.
This results in a stream of events, with the Misra-Gries algorithm is employed
to estimate the frequency of each event, thus resulting in statistics which
are used to decide if a nanonode should act as a retransmitter. Molecular
absorption, fading effects and electromagnetic scattering (simulated using a
ray tracing engine) are taken into account in simulating the physical layer.
In the context of body area networks, Afsana _et al._ [127] propose a cluster-
based forwarding scheme in which cluster controllers are elected as a function
of their residual energy. Network communication is then optimized for intra-
and inter-cluster communication considering energy consumption at the link
level. The resulting performance has been evaluated in terms of Signal to
Interference Plus Noise Ratio (SINR) (for an SNR up to 20 dB) and outage
probability up to 0.5, considering the impact of shadowing, molecular
absorption, and spreading loss. In all cases, the proposed scheme results in a
data-rate improvement of 3-15% over the baseline.

Various flooding mechanisms are discussed by Stelzner _et al._ [128] in the
context of in-body nanonetworks. The baseline forwarding mechanism floods
messages based on a fixed, predetermined probability. A more advanced scheme,
‘probA’ involves adaptively changing that probability according to the
estimated density of transmitters close to a given nanonode. Both mechanisms
are evaluated within an environment modeling an aorta and artery (a
cylindrical environment with a wide or narrow radius). Probabilistic flooding
requires approximately 60% of nanonodes to participate in the routing to
achieve full network coverage in both cases. ProbA performs well in the aorta
and requires participation of only 40% of nanonodes, but fails to achieve full
network coverage in the more restricted artery.

As an alternative to probabilistic flooding, Stelzner _et al._ [128] also
propose a scheme (i.e., _LENWB_) requiring nanonodes to store information up
to 2-hop distant neighbors. In the aorta, LENWB achieves full network coverage
when 50% of nanonodes participate, and in the artery LENWB performs even
better, achieving full network coverage with only 20% of nanonodes forwarding
the messages. However, we do note that this high delivery reliability and
coverage comes at a significant cost in terms of memory requirements. Buther
_et al._ [129] go a step further, and propose individual nanonodes to learn
and store their hop distance to a micro-scale gateway. The hop count is then
used as a direction indicator to determine if the packet needs to be flooded
or not. They consider a naive version of the algorithm, in which nanonodes do
not remember if a message has been forwarded, and propose an optimized
approach by invalidating the hop count of nanonodes once they have acted as a
forwarding nanonode. This results in decreasing the total massage count from
exponential to quadratic behaviour. A similar approach is taken by Al-Turjman
_et al._ [130] in the context of IoNT, where the next hop towards a gateway
node is not only determined by its hop count, but is also restricted to the
first next hop which satisfies some energy-related constraints (e.g., at least
50% battery remaining). The path loss model takes both molecular absorption
and spread path loss into account. When compared to a shortest path data
collection strategy, the proposed approach avoids overusing nanonodes which
are close to a gateway, thus resulting in a larger network lifetime (6 times
or more). This however comes at the cost of a higher latency due to the
selection of longer paths (2-3 times higher).

Each of the discussed algorithms is (to a varying degree) successful in
reducing the number of redundant transmissions, and may be considered for
implementing one-to-many communication. However, for when one-to-one
communication is required, flooding is inefficient by nature, since all
nanonodes in the network receive each message. ([129] is an exception, but
even there all nanonodes will receive a message if the target is far enough
from the gateway.) Furthermore, the reduction in the number of transmitted
messages is typically at the cost of some advantage of flooding: probabilistic
flooding may fail to deliver messages if not tuned carefully, and other
mechanisms collect topology-dependent information, making them less useful if
the nanonodes are mobile.

TABLE III: Summary of network layer protocols Protocol | Distinct Features | Potential Applications | Evaluation Topology | Evaluation Metrics
---|---|---|---|---
Xia _et al._ [118] |  | \- directional antennas
---
\- directivity-sensitive buffer
and queuing
\- wireless robotic materials |  | \- 2D Poisson distributed nodes
---
\- grid of relay nodes
| \- throughput vs. packet
---
generation rate and
transmission distance
Rong _et al._ [119] |  | \- amplify-and-forward
---
vs. decode-and-forward
| \- wireless robotic materials
---
\- body-centric communication
\- 3 node network | \- bit-error rate
Yu _et al._ [120] | \- channel-aware forwarding |  | \- wireless robotic materials
---
\- body-centric communication
| \- 1D (string) network
---
\- uniform or random nodes
\- 5 to 50 nodes
| \- end-to-end capacity
---
\- average latency
PESAWNSN [121] |  | \- power and signal quality
---
-aware arc weight
\- data aggregation
| \- software-defined met. (gen. I)
---
\- wireless robotic materials
\- body-centric communication
| \- 2D random nodes
---
\- 10000 nodes
| \- power consumption
---
vs. transmission range
Pierobon _et al._ [122] |  | \- hierarchical cluster-based
---
\- distributed probabilistic
energy-based forwarding
| \- wireless robotic materials
---
\- body-centric communication
| \- 2D Poisson distributed nodes
---
\- 100 nodes
| \- average latency
---
\- capacity per node
\- energy efficiency
| Cánovas-Carrasco
---
 _et al._ [123]
| \- hierarchical cluster-based
---
\- circulating nanonodes
\- energy harvesting
| \- body-centric communication
---
| \- 1 nanorouter implanted in
---
the skin and 1 nanonode
in the center of a vein
| \- energy efficiency
---
| Cánovas-Carrasco
---
 _et al._ [124]
| \- hierarchical cluster-based
---
\- circulating nanonodes
\- MDP-guided event reporting
| \- body-centric communication
---
| \- cylindrical volume
---
\- random nodes
\- 6000 nodes
| \- energy efficiency
---
\- effect of nanorouter
position on
throughput
Liaskos _et al._ [125] |  | \- adaptive flooding
---
\- nodes may deactivate
| \- software-defined met. (gen. I)
---
\- wireless robotic materials
\- body-centric communication
\- on-chip communication
| \- 2D uniform grid
---
\- 625 to 4000 nodes
| \- achieved coverage
---
\- mean service time
\- energy efficiency
Tsioliaridou _et al._ [126] |  | \- adaptive flooding
---
\- based on reception statistics
\- Misra-Gries algorithm
| \- software-defined metamaterials
---
\- on-chip communication
| \- 2D and 3D uniform grids
---
\- 1000 to 8000 nodes
| \- achieved coverage
---
\- mean service time
\- energy efficiency
Afsana _et al._ [127] |  | \- cluster-based forwarding
---
\- centers selected based
on residual energy
\- body-centric communication | \- unspecified |  | \- throughput vs. SNR
---
LENWB [128] |  | \- probabilistic flooding vs.
---
(locally) adaptive flooding
\- body-centric communication |  | \- cylindrical volumes of
---
various sizes
\- random nodes
\- 10 to 2000 nodes
| \- coverage
---
\- memory usage
Buther _et al._ [129] |  | \- flooding based comm.
---
\- using hop-distance
\- destructive mode to
avoid broadcast storms
\- body-centric communication |  | \- cylindrical volume
---
\- random and uniform nodes
\- up to 60 nodes
| \- power consumption
---
vs. network size
E3A [130] |  | \- sensor-to-gateway comm.
---
\- forwarding based on hop-
distance and energy level
| \- software-defined met. (gen. I)
---
\- wireless robotic materials
| \- 2D uniform grid
---
\- 1500 nodes
| \- average latency
---
\- failure rate
\- energy efficiency
Tsioliaridou _et al._ [137] |  | \- geographic routing using
---
hop-distance coordinates
\- integer calculations only
\- software-defined met. (gen I.) |  | \- 2D uniform grid
---
and random nodes
\- 10000 nodes
| \- failure rate
---
\- energy efficiency
Tsioliaridou _et al._ [138] |  | \- geographic routing using
---
hop-distance coordinates
\- integer calculations only
\- coordinates selection alg.
| \- software-defined metamaterials
---
\- wireless robotic materials
| \- 3D uniform grid
---
and random nodes
\- 5000 nodes
| \- failure rate
---
\- energy efficiency

###  IV-C Routing in (Semi-)Regular Topologies

Some applications require to transmit messages to a specific nanonode, in
which case flooding (which transmits a message to all nanonodes in the
network) is an inefficient solution. To achieve such unicast communication,
some strong form of addressing is needed (i.e., nanonodes needing an
identifier, physical or logical location). When network topologies follow
regular patterns, relatively simple addressing and routing mechanisms become
possible. This is the case for NoC applications, where nanonodes are often
static and laid out according to a regular grid pattern, enabling hard-coded
coordinates for routing nanonodes among the two main axes. Researchers
designing wireless NoC protocols often envision cores communicating using THz
frequencies because carbon nanotube-based antennas have the potential for
higher transmission rates and lower power and area overhead than e.g., ultra-
wide band communication [139].

A simple XY routing mechanism lets routers forward messages along the X-axis
(horizontal) first, until a router is found with the same X coordinate, and
subsequently the routers forward along the Y-axis until the destination is
reached. Greedy forwarding mechanisms rely on a distance metric which can be
calculated between coordinates and aim to choose a neighbor which minimizes
the distance to the destination. In the presence of faults or in non-planar
topologies, greedy forwarding might result in a message being routed to a non-
destination nanonode with no distance decreasing neighbors. Thus, fault
tolerant routing techniques have been developed, an overview of which is
provided by Radetzki _et al._ [131]. Since some of the core ideas for fault-
tolerance were originally proposed for (wired or wireless) NoC settings, we
provide an overview of these papers. Since these efforts do not specifically
target THz nanocommunication, they are omitted in Tables III and VII. One
important technique in fault tolerant routing is face routing, which defines
rules to route around spots with faulty nanonodes. Maze routing [132] adds
extra fields to a message, allowing to route around fault regions without
requiring nanonodes to store any information other than their coordinates.
Maze routing is however limited to planar topologies, and the route may be far
from optimal.

Fukushima _et al._ [133] propose to collect local information to group faulty
nanonodes in rectangular non-overlapping fault regions. The restriction that
the fault regions must be non-overlapping may require to expand a fault region
to include some operational nanonodes. Such healthy nanonodes inside a fault
region cannot receive packets and thus must be switched off. More complex
shaped fault regions can be realized by expanding the information collection
region [134].

Using fault-tolerant routing to reroute packets around faulty regions will
increase the packet latency and create congestion around the faulty region.
Ebrahimi _et al._ [135] augments the XY algorithm with local nanonode
information to route along failures reducing congestion through the
incorporation of local queue and buffer information. Similarly, Saeed _et al._
[136] propose two fault-adaptive XY routing mechanisms (one avoiding loops,
and another maximizing success delivery probability) enabling communication
between a network of controllers in the context of hyper-surfaces. These fault
tolerant algorithms typically trade off the information required to take a
routing decision (and the corresponding algorithmic) complexity, with
flexibility to deal with more complex fault scenarios. An exception to this is
maze routing, but that approach is restricted to planar topologies and may
result in suboptimal paths.

###  IV-D Irregular Topologies

When network topologies get even more irregular, nanonodes need a mechanism to
determine their own coordinates. Tsioliaridou _et al._ [137] was one of the
first approaches to use a number of fixed anchor points in a 2D or 3D space
(as in software-defined meta-materials) to flood announcements of their
existence across the network. Based on triangulation, nanonodes could
determine their (non-unique) coordinate. Once the initialization phase is
over, nanonodes can participate in a stateless manner in the packet forwarding
process which consists of selective flooding towards the destination. The
authors compare their approach with probabilistic flooding and a dynamic
infrastructure flooding approach. Since the flooding approaches deliver each
packet to all nanonodes in the network, they both require many more nanonodes
to unnecessarily spend energy on decoding the massage (5 times more in the
paper, but this depends on the network size). This approach was further
refined in Tsioliaridou _et al._ [138] by proposing a routing approach which
further minimizes required retransmits. A mechanism is proposed relying only
on integer calculations and nanonode-local information enabling each nanonode
to deduce whether it is located on the linear segment connecting the sender to
the recipient nanonode. The energy efficiency of the scheme can be further
optimized by tuning the width of the linear path. This path width allows to
trade-off reliability and energy efficiency: a larger path width allows the
algorithm to deal with more irregular scenarios, but it also results in an
increased amount of transmitted messages. THz-band specific features such as
molecular absorption and shadow fading are also taken into account when
evaluating the algorithm.

Both of these schemes offer efficient one-to-one routing solutions, but they
require a static environment, as nanonode mobility would result in frequent
invalidation of the coordinate systems. Another open challenge is that these
techniques may enable nanonodes to determine their own coordinates, but these
works do not address how they might obtain the coordinates or addresses of
other nnanonodes with whom communication is needed.

The particular addressing needs of medical application scenarios are
conceptually investigated in Stelzner _et al._ [140]. The authors distinguish
addressing from guidance concepts. The latter refer to alternate solutions to
reach a target, without requiring an explicit address in communication, e.g.,
through kinds of wiring, electromagnetic fields, or bio-circuits. Function-
centric nanonetworking refers to a scheme were location and functional
capability of groups of nanonodes are addressed rather than the communication
(individual) endpoint(s). The location can refer to an area defined in the
human body, the function refers to a type or category of nanonodes rather than
an individual one (e.g., blood pressure sensor). $\blacksquare$

Table III lists publications focusing on one or more network layer protocols.
For each publication, the main novel features are given, as well some
applications proposed by the authors themselves. We also mention the specific
topology in which the routing schemes were evaluated and the evaluation
metrics considered by the respective authors.

Across different applications and topologies, there is a large focus on
minimizing _power consumption_ and _energy efficiency_. However, these metrics
are often exclusively evaluated based on the number of sent (and received)
messages. This provides an incomplete picture, since the power per message
also depends on the transmission distance and the message length.

_Resiliency_ has also been studied in various settings: papers focusing on
flooding typically discuss network coverage (the percentage of nanonodes which
receive a one-to-all broadcast). Another example is Tsioliaridou _et al._
[138], where a path redundancy parameter is introduced, which allows to tune
the number of nanonodes which participate in the transmission of a point-to-
point message.

Most applications require large numbers of participating nanonodes.
Nonetheless, the _scalability_ of routing protocols is often not evaluated.
Table III shows that almost all works focus on networks with a set number of
nanonodes, typically corresponding to a small fraction of the larger network.
However, papers which do look into the effect of network size, such as Liaskos
_et al._ [125] and Stelzner _et al._ [128] find that parameters such as
network coverage and power consumption depend non-linearly on both the
area/volume covered by the network, and the density of the nanonodes. Future
work should evaluate the sensitivity in function of this metric, as limiting
the evaluation to a set network size may result in conclusions which do not
generalize well to larger or smaller networks.

Whilst collecting these results,the effect of _nanonode mobility_ remains
often overlooked. This is permitted in some applications, where the topology
is indeed static, or network changes occur very infrequently. Such scenarios
include network-on-chip, the monitoring of mission critical materials and some
software-defined metamaterials and IoNT/WSN settings. However, in-body network
applications, the network is intrinsically mobile: when nanonodes operate
within a bloodstream they move due to the blood flow, if they are attached to
tissue, the body in which they are situated may move and change their relative
positioning. From the existing research which targets in-body network
applications, only Buther _et al._ [129] and Cánovas-Carrasco _et al._ [123]
[124] mention nanonode mobility. The work of [123] and [124] focuses on
nanonodes reporting events rather than nanonodes communicating directly with
each other. Since an event message can be transmitted via any nanorouter, the
main issue in this setting is a) knowing if, and b) estimating how long it
will be until, a particular nanonode is in reach of a nanorouter. The first
issue is addressed in [123] via an ultrasound energy source. The second issue
is approached in [124] using MDPs. In [129], the mobility issue is addressed
by periodically invalidating and reinitializing all routing information.
Whilst such an approach is (in theory) always possible, we note that this may
place a considerable burden on the network load and is costly in terms of
energy consumption. Also, even in a slow moving environment, the frequency at
which an individual connection change between any pair of nanonodes may be
high (due to there being a large number of nanonodes), and thus, routing
protocols which depend on global network information may require frequent
updates. In future work, the effect of mobility on a network protocol should
be carefully evaluated and simulated in an environment in which nanonodes are
continuously moving. Ideas from research regarding mobile ad-hoc networks
could provide a valuable starting point.

Finally, due to the large variety of application scenarios, evaluation
topologies and metrics, it is difficult to _compare_ the results of various
authors. There are various approaches to remedy this problem: open-sourcing
the network topologies may allow researchers to easily evaluate their
algorithms in a standardized variety of settings (without needing the in-depth
knowledge to generate the specific topologies). However, there are many other
modeling and evaluation parameters which may influence the results and
complicate any comparison. In view of these observations, contributions
focusing on the numerical comparison of various existing algorithms in a
variety of settings, such as Stelzner _et al._ [128] are highly valuable tools
to provide a comparison of existing work. Such work is unfortunately rare, and
should be further encouraged.

##  V Link Layer

In THz band nanonetworks, link layer protocols are used for enabling direct
communication between a pair of nanonodes or between a nanonode and a more
powerful device (e.g, nanorouter, nanocontroller, gateway, nano-macro
interface). The primary functions of link layer protocols are channel access
coordination, which is traditionally performed on the MAC sub-layer, and
recovery from bit transmission errors, usually performed on the Logical Link
Control (LLC) sub-layer. Classical MAC and LLC protocols cannot be directly
applied in THz band nanocommunication for the following reasons [114, 35].
First, the existing link layer protocols have been predominantly designed for
band-limited channels. However, the THz frequency band provides almost a 10
THz wide bandwidth window, which constitutes the main difference between
graphene-enabled THz nanocommunication and classical link layer protocols.
Second, existing link layer protocols are mostly carrier-sensing techniques
and are therefore too complex for THz nanocommunication in a number of
application domains and scenarios. Finally, nanodevices feature highly limited
energy, in various scenarios requiring the usage of energy-harvesting systems
[10, 141, 142]. This changes the availability of the nanodevices’
communication systems over time, which is not a constraint posited to the
classical link layer protocols [72]. This has been recognized in the research
community and several link layer (often MAC sub-layer only) protocols for THz
nanocommunication have been proposed.

As shown in Figure 6, they can be grouped into hierarchical protocols that
assume the availability of more powerful nanocontrollers, and distributed, in
which all nanonodes are considered as equal (Figure 7). In addition, protocols
specifically designed for on-chip nanocommunication can be separately grouped,
due to the uniqueness of communication features, as in more details discussed
below. Compared to the distributed protocols, the main advantages of the
hierarchical link-layer protocols include reduced energy consumption,
increased network scalability, and increased reliability due to interference
and collision probability [143]. Their main disadvantages are their comparably
higher complexity and delivery latency.

THz Link Layer Protocols Distributed (Sect. V-A) Akkari _et al._ [144]
Alsheikh _et al._ [145] PHLAME [114] DRIH-MAC [146] TCN [147] Xia _et al._
[148] Smart-MAC [149] APIS [150] Hierarchical (Sect. V-B) Wang _et al._ [115]
EEWNSN-MAC [151] EESR-MAC [152] CSMA-MAC [153] On-Chip Communication (Sect.
V-C) Mansoor _et al._ [154] BRS-MAC [108] Dynamic MAC [155] ;

Figure 6: Classification of link layer protocols for THz nanocommunication
Figure 7: Distributed vs. hierarchical MAC protocols

###  V-A Distributed Protocols

Akkari _et al._ [144] reason that there is a need for novel link layer
protocols for nanonetworks due to the fact that nanodevices have strict power,
memory, energy, and computation constraints. Thus, the authors argue, the
nanonodes may only be able to store one packet, requiring packets to be
delivered before certain hard deadlines. Motivated by this claim, they propose
a distributed and computation-light MAC protocol for nanonetworks. The
protocol determines the optimal transmission times for nanonodes so that the
largest set of traffic rates can be supported, while ensuring delivery within
a hard deadline. Optimal transmission decisions are made locally using
Carrier-Sense Multiple Access (CSMA) Markovian chain and Lyapunov
optimization, which are based on nanonode’s incoming traffic rate and queue
length. The protocol achieves continuous communication by simultaneously
considering its energy consumption and harvesting rate.

Motivated by the fact that nanonodes communicating in the THz band are capable
of achieving very high transmission bit-rates at very short distances, the
authors in [145] also argue that classical MAC protocols cannot be directly
applied in THz band nanocommunication. Therefore, they propose an energy-aware
MAC protocol for synchronizing the communication between nanodevices. The
proposed protocol is based on a Time Spread ON-OFF keying (TS-OOK) scheme
(more details in Section VI), which is a pulse-based communication scheme for
THz band nanonetworks, and assumes grid-like distribution of the nanonodes. In
the protocol, active nanonodes transmit their packets in an interleaved way to
the receivers based on the calculated Critical Transmission Ratio (CTR), i.e.,
the maximum ratio between the transmission time and the energy harvesting time
needed for continuous operation.

Jornet _et al._ [114] propose the PHysical Layer Aware MAC protocol for
Electromagnetic nanonetworks in the Terahertz Band (PHLAME), which is built on
top of modified TS-OOK. In PHLAME, the transmitting and receiving nanonodes
jointly select the transmission symbol rate (the ratio between time between
symbols and pulse duration) and channel coding scheme. They do that by
performing a handshaking process initiated by a nanonode that has information
to transmit and enough energy to complete the transmission. Using the common
coding scheme, the transmitter generates a packet containing the
synchronization trailer, transmitter ID, receiver ID, packet ID, randomly
selected transmitting data symbol rate, and error detecting code. The
handshaking acknowledgment is issued by the receiver upon the reception of the
packet. If the handshake is accepted, the receiver issues a packet containing
the synchronization trailer, transmitter ID, receiver ID, packet ID,
transmitting data coding scheme, and error detecting code. The transmitter
then transmits a data packet using the symbol rate specified by the
transmitter, and encoded with the weight and repetition order specified by the
receiver during the handshake process. The authors show that the proposed
protocol is able to support densely populated nanonetworks in terms of energy
consumption per useful bit of information, average packet delay, and
achievable throughput.

Another distributed MAC protocol is Distributed Receiver-Initiated Harvesting-
Aware MAC (DRIH-MAC) [146]. Simply stated, in DRIH-MAC (RIH-MAC in its
preliminary version [156]) the communication is initiated by the receiver by
transmitting a Ready-to-Receive (RTR) packet to one or multiple transmitters.
The recipients of the RTR packet transmit a data packet to the receiver.
Scheduling in DRIH-MAC is based on a probabilistic scheme-based on the edge-
coloring problem. The idea of edge-coloring is to color the edges of a graph
such that two edges incident to the same node are of different colors.
Obviously, in DRIH-MAC different edge colors translate to transmission
sequences. The authors claim DRIH-MAC to be scalable and light-weight, with
the minimized probability of collisions and maximized utilization of harvested
energy.

The authors in [147] propose Timing Channel for Nanonetworks (TCN), a link
layer THz band nanocommunication protocol that exploits “timing channels”.
They define the timing channels as logical channels in which the information
is encoded in the silence duration between two consequent transmissions. The
authors argue that, by using timing channel-based communications, TCN enables
energy efficient low data-rate communication. Moreover, by introducing
acknowledgment-based collision detection, TCN enables recovery from
transmission errors. Retransmissions are then envisioned for improving the
reliability of communication.

A link-layer synchronization and MAC protocol for wireless communication in
the THz band is presented in [148]. The link-layer synchronization capability
is achieved through a receiver-initiated (i.e., one-way) handshake procedure.
The core idea of the handshake is to prevent data transmissions when the
receiver does not have enough energy for reception. Additionally, the protocol
aims at maximizing the channel utilization and minimizing the packet discard
probability. It does that by making use of a sliding flow-control window at
the link-layer, i.e., the receiver specifies the amount of data that can be
received for its current energy level.

The authors in [149] propose Smart-MAC, a MAC protocol delivered as a part of
the NanoSim simulator and often used as a baseline for benchmarking of other
MAC protocols. Smart-MAC uses a handshake procedure for discovering nanonodes
within its transmission range. If at least one nanonode is discovered, the
packet is transmitted. In case the nanonode does not have any neighbors,
Smart-MAC uses a random back-off delay prior to restarting the handshake
procedure. In case of multiple packets in the queue, a new transmission is
scheduled after a specific time computed through the same back-off mechanism,
which reduces the probability of collisions.

A distributed scheduling mechanism named Adaptive Pulse Interval Scheduling
(APIS) is proposed [150] for the interconnection between nanonetworks and an
IoT gateway, targeting software-defined metamaterial and wireless robotic
material applications. In APIS, the sink distribute a transmission schedule,
followed by the nanonodes transmitting data based on the channel sensing
results and traffic patterns. The proposed protocol was evaluated in terms of
reliability of data delivery, achievable throughput, and energy consumption.
Due to the scheduled transmissions, high time precision and continuous
operation of the nanonodes are required for scheduling, which could be
infeasible under limited computational capacity and stored energy. Moreover,
the communication between the nanonodes is abstracted and not considered in
this work.

###  V-B Hierarchical Protocols

The authors in [115] propose an energy and spectrum-aware MAC protocol for THz
band nanocommunication. First, they propose to utilize the hierarchical
network architecture characteristic to WNSNs for shifting the protocol
complexity to more resourceful nanocontrollers. Therefore, the nanocontroller
regulates the channel access on behalf of the nanonodes of its cluster. The
nanocontroller does that by utilizing Time Division Multiple Access (TDMA) and
based on the nanonodes’ data requirements and energy constraints. The proposed
MAC protocol utilizes CTR, i.e., the maximum allowable ratio between the
transmission and energy harvesting times below which the nanonode consumes
less energy than harvested. Based on this and assuming TS-OOK as the physical
layer communication scheme, a symbol-compression scheduling protocol is
proposed for assigning each nanonode with different sets of transmission slots
in such a way that the overall nanonetwork achieves optimal throughput, while
maintaining transmission ratios below the CTR for achieving energy balancing.
Note that the protocol utilizes the TS-OOK’s elasticity in the inter-symbol
spacing, allowing multiple nanonodes to transmit their packets in parallel
without inducing collisions.

Rikhtegar _et al._ [151] present the Energy Efficient Wireless Nano Sensor
Network MAC (EEWNSN-MAC), a MAC protocol for mobile multi-hop THz band
nanonetworks. They assume a network comprised of nanonodes moving randomly at
a constant speed, as well as static nanorouters and a nano-micro interface.
EEWNSN-MAC is divided into three steps: i) handshaking-based selection of a
cluster head (i.e., nanorouter); ii) TDMA-based scheduling phase in which a
nanorouter schedules the transmission times for the nanonodes in its cluster;
iii) the data transmission phase in which the nanonodes send their packets to
the nanorouters, followed by their aggregation and forwarding to the nano-
micro interface.

The authors in [152] propose EESR-MAC, an energy efficient, scalable, and
reliable MAC protocol for THz nanonetworks. In the protocol, the cluster head
is first derived as the one that is equidistant from other nanonodes in the
cluster. Then, the classic TDMA approach is used for inter and intra-cluster
communication, where the master node is assumed to transmit the schedule to
the other nanonodes. The approach is presented here for completeness purposes,
as it has not been evaluated nor benchmarked against other approaches (and is
therefore omitted in Table VII).

A slotted CSMA/CA based MAC protocol (CSMA-MAC) is proposed for energy
harvesting nanonodes in [153]. The protocol assumes a coordinator node
periodically transmitting beacon packets containing the super-frame structure.
A nanonode that wants to transmit receives the beacon, synchronizes itself to
the super-frame structure, followed by transmitting its data using slotted
CSMA/CA channel access mechanism. The protocol has been benchmarked in terms
of achievable data-rate against a simple round robin approach.

TABLE IV: Summary of link layer protocols Protocol | Sub-layer | Distinct Features | Potential Applications | Evaluation Metrics
---|---|---|---|---
Akkari _et al._ [144] | MAC |  | \- CSMA-based with hard deadline
---
\- continuous communication
| \- software-defined metamaterials
---
\- wireless robotic materials
\- timely-delivery ratio111Percentage of packets successfully delivered before
the deadline.
Alsheikh _et al._ [145] | MAC |  | \- blind transmission
---
\- continuous communication
\- grid constellation
| \- software-defined metamaterials (gen. I)
---
\- wireless robotic materials
| \- consumed energy
---
\- collision probability
\- transmission delay
\- network throughput
PHLAME [114] |  MAC, LLC |  | \- handshake-based
---
\- interference minimization
\- retransmissions possible
| \- software-defined metamaterials (gen. I)
---
\- wireless robotic materials
\- body-centric communication
| \- consumed energy
---
\- collision probability
\- network throughput
DRIH-MAC [146] | MAC |  | \- receiver-initiated communication
---
\- schedule-based transmissions
\- wireless robotic materials |  | \- transmission delay
---
\- capacity utilization
\- energy utilization
TCN [147] |  MAC, LLC |  | \- scheduled transmissions (TDMA)
---
\- acknowledgement-based
\- retransmissions possible
\- body-centric communication |  | \- energy per bit
---
\- collision probability
\- energy consumption
Xia _et al._ [148] | MAC |  | \- handshake-based
---
\- receiver-initiated synchronization
\- sliding window flow control
\- wireless robotic materials |  | \- packet discard probability
---
\- network throughput
Smart-MAC [149] | MAC |  | \- default MAC in NanoSim
---
\- handshake and backoff-based
\- wireless robotic materials |  | \- packet-loss ratio
---
\- scalability
APIS [150] | MAC |  | \- designed for gateway to sink links
---
\- based on traffic and channel sensing
| \- software-defined metamaterials
---
\- wireless robotic materials
| \- achievable throughput
---
\- energy efficiency
\- delivery reliability
Wang _et al._ [115] | MAC |  | \- TDMA-based
---
\- continuous communication
\- fairness-oriented
| \- software-defined metamaterials (gen. I)
---
\- wireless robotic materials
| \- single-user throughput
---
\- achievable data-rate
EEWNSN-MAC [151] | MAC |  | \- TDMA with clustering
---
\- mobility and multi-hopping
| \- software-defined metamaterials (gen. I)
---
\- wireless robotic materials
| \- energy consumption
---
\- scalability
\- packet-loss ratio
EESR-MAC [152] | MAC | \- TDMA with clustering |  | \- software-defined metamaterials (gen. I)
---
\- wireless robotic materials
\- none
CSMA-MAC [153] | MAC |  | \- beaconing-based
---
-CSMA/CA channel access
| \- body-centric communication
---
\- wireless robotic materials
\- achievable throughput
Mansoor _et al._ [154] |  MAC, LLC |  | \- token-passing-based
---
\- based on traffic estimates
\- on-chip communication |  | \- average data-rate
---
\- energy efficiency
\- transmission delay
BRS-MAC [108] |  MAC, LLC |  | \- CSMA and NACK-based
---
\- preamble-based collision detection
\- on-chip communication |  | \- achievable throughput
---
\- transmission delay
Dynamic MAC [155] |  MAC, LLC |  | \- combines CSMA and token-passing
---
\- based on expected traffic loads
\- on-chip communication |  | \- achievable throughput
---
\- energy efficiency
\- protocol overhead

###  V-C Protocols for On-Chip Communication

The authors in [98] provide a context analysis of MAC protocols for on-chip
communication. They argue that, from the link layer perspective, on-chip
communication represents a unique scenario with respect to traditional
wireless communication. This is predominantly due to the fact that the
topology of a network, chip layout, and characteristics of the building
materials are static and known in advance [113]. Therefore, the on-chip
wireless channel can be accurately characterized as quasi-deterministic from
the link layer perspective.

As discussed before, the on-chip applications require very low and
deterministic latency, high reliability, and very high throughput. As the
secondary requirement, the energy consumption should be constrained to limit
the heat dissipation on the chip. This has to an extent been recognized in the
existing literature. Note that these works do not consider the usage of THz
frequencies for communication, but instead focus on the sub-THz (i.e., 30-300
GHz) band. Nonetheless, we will outline them here due to the intrinsic
similarities between the THz and mmWave bands in the context on on-chip
nanocommunication.

Two flavors of a token-passing (i.e., dynamic TDMA-based) MAC protocol for on-
chip wireless communication are proposed in [154]. In token-passing, the
channel access is based on the possession of a token which circulates between
nodes in a round-robin fashion to ensure fairness. The duration of token
possession is in [154] determined on predicted estimates of communication
demands for different nanonodes. The protocol is evaluated in terms of average
data-rate, energy efficiency, and latency of packet delivery.

Mestres _et al._ [108] propose the {Broadcast, Reliability, Sensing} protocol
(BRS-MAC). BRS-MAC combines the CSMA/CA and CSMA/CD mechanisms by utilizing
preamble-based collision detection. Specifically, as the first envisioned step
and only if the channel is sensed idle, the sender transmits a preamble
(otherwise the node backs off). Nanonodes that correctly received it remain
silent for the rest of the transmission, while the ones that detected a
collision respond with a Negative ACKnowledgment (NACK). If the NACK was
received, the original sender cancels the transmission and backs off, while
the other nodes discard the preamble. Adversely, the sender transmits the rest
of the packet. The protocol has been evaluated in terms of achievable
throughput and delivery latency.

The authors in [155] argue that there is a need for reconfigurable wireless
links for optimizing the utilization of the on-chip channel bandwidth.
Grounded on that observation, they propose a dynamic MAC protocol by
integrating the CSMA and token-based mechanisms. The proposed protocol
utilizes the token-passing mechanism in case of high traffic loads. When the
traffic loads are low, token passing becomes energy inefficient. Therefore, in
such cases the dynamic MAC unit of the protocol switches the operation to a
CSMA-based mechanism in which the consumed energy is due to valid transmission
only. The protocol is evaluated in terms of achievable throughput, energy
efficiency, and protocol overhead (i.e., power, area, and delay
characteristics). $\blacksquare$

Table IV provides a summary of the above-discussed link layer protocols for
THz band nanonetworks. As visible in the table, there are several open
challenges pertaining to the link layer protocols for nanonetworks. First, the
majority of the current protocols deal with the MAC sub-layer, with only the
PHLAME and TCN protocols additionally proposing a LLC sub-layer mechanism.
This implies that the majority of current protocols are not tailor-made for
applications that require high communication reliability (e.g., body-centric
and on-chip communication). One of the open research questions is to improve
the reliability of THz band nanocommunication on the link layer. As an
example, PHLAME supports packet repetitions as means for improving the
nanonetwork reliability (i.e., Packet Reception Rate (PRR)). However, when and
how many repetitions should be utilized is still unclear. Such a decision
could potentially be based on the current energy levels of the nanonodes,
their distances, and/or the amounts of traffic, as in more detail discussed in
[157].

Second, the majority of the existing protocols do not optimize for the latency
of data delivery. The only protocol that goes in this direction is Akkari _et
al._ [144], where a hard deadline on data delivery is imposed, however the
minimization of delivery latency is not attempted. Optimization of link layer
protocols in terms of latency is required for several of the envisioned
applications (e.g., the second generation of software-defined metamaterials,
on-chip communication). In addition and to the best of our knowledge,
protocols aiming at jointly optimizing throughput and latency, which is
required for on-chip nanocommunication, are currently missing.

Third, apart for EEWNSN-MAC, none of the protocols explicitly accounts for the
fact that nanonodes can be mobile. Even the EEWNSN-MAC protocol, given that it
hierarchical, requires the selection of cluster heads, which is known to
yields unsatisfactory performance in scenarios with high mobility. In mobility
scenarios, are handshake and clustering-based hierarchical protocols are
generally expected to yield poor performance. This is further accentuated by
the fact that, due to harvesting, a certain amount of time will usually have
to pass between the handshake and data transmission. In high mobility
scenarios, the optimal strategy for data transmission could be to just send
data when there is data to send and enough energy for transmission.
Nonetheless, such strategies have yet to be investigated.

In Table IV, we have listed the application domains that could potentially be
supported by a given protocol. There are seemingly no link layer protocols
explicitly targeting on-chip THz band communication. We have outlined the most
promising candidates from the mmWave band, which is indeed similar to the
signal propagation in THz frequencies. Yet, propagation is not the same for
these two bands, mostly due to the fact that THz signals attenuate faster and
resonate with water, in contrast to mmWave signals resonating with oxygen
molecules. Hence, the applicability of the listed protocols for on-chip THz
nanocommunication is yet to be evaluated.

Finally, all of the existing protocols have been evaluated either analytically
or by means of simulation. Their performance results are potentially not
accurate, as they have not been derived with a very high level of realism. For
example, the energy consumption of a nanonode’s communication system is in the
evaluations of all protocols attributed to either transmission of reception,
while idling energy has been fully neglected. Evaluation results with higher
levels of realism are certainly needed. In addition, the metrics used in the
evaluations are non-standardized and non-exhaustive, as shown in the table.
Hence, various performance insights are currently lacking. For example, one of
the primary requirements for many of the envisioned applications is
scalability. Nonetheless, the scalability of link layer protocols has been
evaluated only in EEWNSN-MAC and even there the conclusion is that “EEWNSN-MAC
is potentially a scalable protocol”. Due to the fact that the evaluation
metrics are currently non-standardized and non-exhaustive, comprehensive
comparison of protocols for different application scenarios is at the moment
infeasible. Given that THz nanocommunication is in many aspects challenging,
even minor improvements in the protocol design could yield high benefits.
Thus, comprehensive protocol benchmarking is certainly a promising research
direction of high priority.

##  VI Physical Layer

The physical layer defines the means of transmitting raw bits over a physical
link interconnecting two nodes. In the specific case of wireless
communication, the physical layer is concerned with the modulation, the
coding, error control, and other methods that determine the data rate and
error rate of the solution, as well as its area and power.

The scenario of THz nanocommunication has a unique blend of constraints and
requirements that greatly impacts the physical layer and prevents the use of
well-established techniques. The nanoscale dimension imposes very stringent
restrictions on the available resources (i.e., area, energy, memory) that,
despite being dependent on the particular application context, suggest the use
of simple and ultra-efficient modulations and coding. This is especially
limiting in intermittent computing applications where devices are powered via
energy harvesting. This is evidently impacting the devices’ available energy,
but also causing intermittency in devices’ operation, posing an additional
challenge in regard to their reliability.

The THz dimension of the scenario affects the physical layer of the design as
well. The main reason is technological, as mature THz circuits and systems for
communication are yet to come, although the community is making significant
leaps forward [158, 159, 160, 161, 19]. Moreover, the THz channel introduces
the effect of molecular absorption which, for increasing distances, becomes
another impairment for communication.

Overall, the existing proposals for THz nanocommunication have embraced
simplicity as one of the main design drivers. As we discuss next in Section
VI-A, on-chip communication works mostly advocate for fast Continuous-Wave
(CW) On-Off Keying (OOK) to avoid power-hungry circuits and minimize signal
processing delay, whereas other applications need to simplify the physical
layer further via Impulse Radio (IR)-like techniques. In the latter case,
modulations rely on the transmission of femtosecond-long pulses and, not
surprisingly, adopt cross-layer strategies in an attempt to further simplify
the protocol stack. As shown in Figure 8, we outline the main alternatives of
such pulse-based modulations and coding techniques in Sections VI-B and VI-C,
respectively. Finally, we analyze recent proposals for simplified beaming,
detection, and synchronization in Section VI-D.

###  VI-A Continuous-Wave (CW) vs. Impulse Radio (IR)

Wireless communication networks have been established and have grown dominated
by CW technologies. This means that the modulation is based on the
manipulation of the amplitude, phase, or other characteristics of a continuous
carrier wave at the desired frequency. Technology scaling has allowed to
increase the carrier frequency in the quest for higher bandwidths and device
miniaturization. Higher bandwidths are naturally attained as the carrier
frequency increases. Miniaturization is achieved because the antenna and other
passive elements, which are typically the largest components within RF
transceivers, scale with the inverse of the carrier frequency. As a simple but
illustrative example, the resonance frequency $f_{R}$ of a dipole antenna of
length $L$ surrounded by air is given by $f_{R}=\tfrac{c_{0}}{2L}$ where
$c_{0}$ is the speed of light.

The energy efficiency of CW transceivers in the THz band depends on several
factors such as the carrier frequency, the choice of modulation, or the
transmission range. Based on an analysis of recent transceivers from 0.06 to
0.43 THz [162, 159, 163, 164], Figure 9 shows how CW transceivers are reaching
10+ Gb/s speeds with around 1 pJ/bit for high-rate applications at the on-
chip, off-chip, and indoor scales. Such trend is expected to continue in the
THz band, where significant efforts are devoted to filling the so-called _THz
gap_ [158, 159, 160, 161, 19].

THz Physical Layer Protocols Pulse-based Modulations (Sect. VI-B) TS-OOK [165]
PHLAME [114] Shrestha _et al._ [166] SRH-TSOOK [167] ASRH-TSOOK [168] Vavouris
_et al._ [169] Zarepour _et al._ [170] Han _et al._ [171] Pulse-based Coding
(Sect. VI-C) Jornet _et al._ [172] MEC [173] Chi _et al._ [174] SBN [175] DS-
OOK [176] Beaming and Detection (Sect. VI-D) Hosseininejad _et al._ [177] Lin
_et al._ [178] Cid-Fuentes _et al._ [179] Singh _et al._ [180] Gupta _et al._
[181] Iqbal _et al._ [182] ;

Figure 8: Classification of physical layer protocol for THz nanocommunication
Figure 9: Energy efficiency of sub-THz and THz transceivers (from 0.06 to 0.43
THz) for short-range high-rate wireless applications. Each data point
indicates the power and data rate of a single transceiver prototype from the
literature for Wireless Personal Area Networks (WPAN, blue squares) and on-
chip communication applications (red circles). Purple diamonds correspond to
theoretical predictions made in the literature for future transceivers.
Finally, straight lines represent the frontiers of energy efficiency of 1, 2,
and 10 pJ per transmitted bit, so that transceivers located above (below) each
line are less (more) efficient than indicated by the frontier. Data extracted
from [164].

The existing scaling tendencies in CW transceivers are good news for on-chip
communication applications as multiprocessors demand very high transmission
speeds. Since the energy supply in computer systems is typically sustained,
classical CW modulation techniques can be used. Nevertheless, as described in
Section III-D, the scenario demands ultra-low latency and low power
consumption. Due to these factors and to the relatively immature state of THz
technology, high-order modulations or techniques requiring significant signal
processing are discouraged. Instead, most proposals advocate for simple
modulations such as OOK and non-coherent (i.e., amplitude) detection [162,
183]. The OOK modulation consists in transmitting silence when the symbol is
’0’ and the carrier wave when the symbol is ’1’. Such modulation can be
achieved by simply connecting the stream of bits to the circuit that generates
the carrier wave. This avoids the use of power-hungry circuits such as those
needed for coherent (i.e., phase) modulation and detection. It has been thus
shown that OOK can be 1.5X and 2.5X more energy efficient than BPSK and QPSK
in on-chip environments [162]. The downside of using low-order modulations is
that, to scale the transmission rates, one may need to resort to multiple
carriers to combat dispersion (i.e., a single carrier modulated at ultra-high
speeds leads to an ultra-high bandwidth signal very sensitive to multipath and
delay spread). Notably, Han _et al._ proposes a multi-carrier modulation that
adapts to the frequency-selective molecular absorption effects of the THz band
[184].

In applications where energy availability is intermittent and not guaranteed,
CW techniques cannot be used due to the cost of generating and using a carrier
signal. Therefore, IR-like modulations where the information is encoded in
short pulses instead of a carrier wave have been proposed instead. In the work
by Zarepour _et al._ [185], carrier-less pulse-based OOK, Binary Phase Shift
Keying (BPSK), Pulse Amplitude and Position Modulations (PAM and PPM,
respectively) were compared in order to assess their fitness for IoNT
applications. Using analytical models, it was concluded that although BPSK is
relatively more complex in terms of decoding logic, it is the most efficient
and reliable among all the contenders. OOK and PPM are simpler, but less
reliable and efficient than BPSK. The analysis discouraged the use of PAM due
to its low performance and efficiency.

Zarepour  _et al._ revisited a widely regarded trade-off between complexity
and performance. BPSK and, by extension, other signaling schemes such as
Transmitted Reference (TR) [186], are preferable over OOK but may not be
affordable in extreme scenarios. In such cases, in fact, even conventional OOK
may be prohibitive. As a result and as we see next, the physical layer
research has continued to push the efficiency and simplicity boundaries of
pulse-based modulations.

###  VI-B Pulse-based Modulations

One of the first works to discuss modulations suitable for nanoscale wireless
communication was [165]. The proposed scheme is named Time-Spread On-Off
Keying (TS-OOK) and is a pulse-based modulation. The main characteristics are
that (i) pulses are around 100-fs long, thus leading to bandwidths in the THz
range, and that (ii) the separation between pulses is much larger than the
duration of the pulse. This scheme retains the simplicity of conventional OOK
and, by having such a large separation between pulses, it is compatible with
applications where energy is very limited or needs to be harvested. Moreover,
by knowing the time between pulses, synchronization is only needed at the
preamble and can be kept throughout the communication. The work in [165],
besides proposing the modulation, confirms that the achievable capacity is in
the order of Tbps and also opens the door to simple multi-user approaches that
exploit the long time between pulses to interleave other communication. The
authors provide an interference model that, in subsequent works, have been
validated experimentally [187].

Figure 10: Comparison between the different variants of pulse-based OOK found
in the literature [165, 114, 166, 168, 169].

The seminal work by Jornet _et al._ has been followed by several variants that
optimize or particularize TS-OOK for different scenarios as graphically
summarized in Figure 10. For instance, in [114, 166] the authors tackle one of
the weaknesses of TS-OOK: if multiple users transmit with the same rate and
collide in one pulse, they are bound to collide in all pulses. In the multi-
user scheme proposed in [114], referred to as Rate Division Multiple Access
(RDMA), users are assigned co-prime transmission rates during handshake to
minimize interference at a reduced cost. In [166], the RDMA scheme is
generalized for both ad hoc and infrastructure-based networks and the choice
of prime numbers is further justified. Later, Mabed _et al._ argued that RDMA
leads to rate imbalance as users are assigned different effective rates. To
overcome this issue, they proposed to employ pseudo-random time-hopping
sequences to determine the time between pulses that, on average, would yield
similar rate for all users [167] or capable of adjusting the rate to the user
needs [168]. Finally, Singh _et al._ propose a completely different approach
to accommodate multiple users, which is to combine OOK with sender-
distinguishing direct sequence codes [176]. In this case, energy efficiency is
sacrificed to achieve higher performance.

Another TS-OOK variant in the literature is [169]. In this case, the authors
aim to maximize energy efficiency and, to that end, propose to combine TS-OOK
with PPM. The approach consists of the modulation of a symbol as the time
between pulses, which is at all times much larger than the pulse duration. It
is demonstrated that when increasing the symbol order, multiple bits can be
encoded as a silence between pulses, therefore improving the energy efficiency
at the cost of a degradation of the data rate. The PPM variant has also been
combined with time-hopping in [188], where a thorough evaluation is carried
out assuming non-coherent detection and multiple modulation orders.

Finally, it is worth mentioning proposals that also adapt to the
particularities and new features of wireless communication in the THz band. On
the one hand, Zarepour _et al._ propose the use of frequency-hopping as a
means of overcoming the problem of dynamic molecular absorption in
composition-varying channels [170]. The _blind_ use of frequency-hopping
eliminates the need for channel state observation, simplifying the modulation,
while still ensuring that the transmission will succeed with a given
probability. This is opposed to [171], which assumes static channel
composition and proposes to estimate distance between transmitter and receiver
to select the most appropriate waveforms or frequencies for transmission. On
the other hand, we also highlight the work of Lin _et al._ which hinges on the
use of graphene-based directional agile antennas in the THz band. More
specifically, they propose to use beam hopping to switch among spatial
channels during transmission [178], a technique that can further reduce
interference among users in TS-OOK scenarios.

###  VI-C Pulse-based Coding

Coding to reduce power consumption and interference without increasing the
transceiver complexity has been another hot topic in nanocommunication
research. Jornet _et al._ first proposed the use of low-weight coding together
with TS-OOK [189, 172]. Rather than utilizing channel codes to detect and
correct transmission errors, this simple mechanism exploits silences to save
power and mitigate interference without reducing the transmission rate of each
individual user.

It was later observed in [190] that minimizing only the average weight does
not ensure minimum energy. Following this argument, the authors derive optimal
codebooks that minimize the energy of transmissions for arbitrary codeword
lengths. Further, Kocaoglu _et al._ extend the discussion to account for
arbitrary input probability distributions and keeping the codeword length
unconstrained, arguing that minimum energy coding with high reliability is
achieved in all cases [173]. Later, the authors in [174] add the property of
prefix freedom and the constraint of maximum average codeword length to the
problem of minimum energy coding. Prefix-free codes ensure that no codeword is
contained within any other codeword, allowing instantaneous decoding of
information. The concept of simple block nanocodes is applied in [175] to add
reliability with very small cost in nanonetworks. The same authors provide a
comprehensive comparison between the different proposed coding schemes in
[191], evaluating energy efficiency, bandwidth expansion, robustness, and
interference.

TABLE V: Summary of physical layer protocols Protocol | Functionality | Distinct Features | Potential Applications | Evaluation Metrics
---|---|---|---|---
TS-OOK [165] | Modulation |  | \- pulse-based
---
\- time spread 100-fs pulses
\- sync only in preamble
| \- body-centric communication
---
\- wireless robotic materials
| \- energy consumption
---
\- user inf. rate
\- aggregated inf. rate
PHLAME [114] | Modulation |  | \- TS-OOK with co-prime rates
---
\- minimizes collisions
| \- body-centric communication
---
\- wireless robotic materials
| \- energy consumption
---
\- collision probability
\- network throughput
Shrestha _et al._ [166] | Modulation |  | \- TS-OOK with co-prime rates
---
\- enhanced & generalized co-prime generation
| \- body-centric communication
---
\- wireless robotic materials
| \- collision probability
---
\- aggregated inf. rate
SRH-TSOOK [167] | Modulation |  | \- based on TS-OOK
---
\- random time between pulses
\- uniform average rate across users
| \- body-centric communication
---
\- wireless robotic materials
| \- collision probability
---
\- packet loss
\- network throughput
ASRH-TSOOK [168] | Modulation |  | \- based on TS-OOK
---
\- random time between pulses
\- adaptive rate per user
| \- body-centric communication
---
\- wireless robotic materials
| \- collision probability
---
\- packet loss
Vavouris _et al._ [169] | Modulation |  | \- PPM with time-spread pulses
---
\- extreme energy efficiency
| \- body-centric communication
---
\- wireless robotic materials
| \- energy consumption
---
\- information rate
Zarepour _et al._ [170] | Modulation |  | \- frequency hopping to
---
avoid absorption peaks
| \- body-centric communication
---
\- wireless robotic materials
| \- signal-to-noise ratio
---
\- bit error rate
\- capacity
Multi-band OOK [162] | Modulation |  | \- continuous-wave OOK in multiple bands
---
\- high rates with simple transceivers
\- on-chip communication |  | \- energy consumption
---
\- information rate
\- silicon area
DAMC [184] | Modulation |  | \- continuous-wave multi-carrier
---
\- bands chosen depending on distance
\- on-chip communication | \- information rate
Han _et al._ [171] | Modulation |  | \- pulse-based version of DAMC
---
\- waveforms chosen based on distance
| \- on-chip communication
---
\- software-defined metamaterials
| \- SINR
---
\- bit error rate
\- throughput
Jornet _et al._ [172] | Coding |  | \- low-weight channel coding
---
\- minimizes energy in TS-OOK
| \- body-centric communication
---
-wireless robotic materials
| \- information rate
---
\- codeword error rate
MEC [173] | Coding |  | \- minimum energy channel coding
---
\- assumes multi-carrier OOK
| \- on-chip communication
---
\- software-defined metamaterials
| \- energy consumption
---
\- transmission rate
\- error probability
Chi _et al._ [174] | Coding |  | \- minimum energy coding
---
\- prefix-free codes
| \- body-centric communication
---
\- wireless robotic materials
\- energy consumption
SBN [175] | Coding |  | \- simple block codes
---
\- efficiency-reliability trade-off
| \- body-centric communication
---
\- wireless robotic materials
| \- bit error rate
---
\- energy efficiency
DS-OOK [176] | Coding | \- direct sequence + OOK |  | \- on-chip communication
---
\- software-defined metamaterials
| \- multi-user interference
---
\- bit error rate

Finally, we highlight the recent work by Yao _et al._ [192], which goes beyond
existing forward error correction strategies and adopts a hybrid mechanism
suitable for energy harvesting. Their proposed error control strategy is
compatible with low-error codes, but incorporates probing packets. Before
starting data transmission, the source sends probing packets. The receivers
then acknowledge the probe only if they anticipate to have enough energy to
receive the data packets; otherwise, they remain silent. This way, data
packets are not sent if receivers are in a state of low energy, which is PHY-
layer dependent.

###  VI-D Beaming and Detection

Beaming at the transmitter side (both beam switching and beam forming) and
detection at the receiver side are two functions that deserve attention due to