# Would the Trees Dim the Lights? Adopting the Intentional Stance for More-
Than-Human Participatory Design

Ned Cooper<EMAIL_ADDRESS>0000-0003-1834-279X Australian National
UniversityCanberraAustralia

(2022)

###### Abstract.

The 2019/20 Black Summer bushfires in Australia demonstrated the brutal and
disastrous consequences of changing the technological world without
considering linkages with the biophysical, ecological or human worlds. An
emerging more-than-human design philosophy encourages designers to consider
such interrelations between humans and non-human entities. Yet, the design
research community has focused on situated or embodied experiences for
designers, rather than developing processes to legitimate the perspectives of
non-human entities through participatory design. This paper explores how
adopting the ‘intentional stance’, a concept from philosophy, might provide a
heuristic for more-than-human participatory design. Through experimentation
with the intentional stance in the context of smart lighting systems, the
paper demonstrates that the approach has potential for non-human entities from
the ecological world, but less so for the biophysical world. The paper
concludes by encouraging critique and evolution of the intentional stance, and
of other approaches, to legitimate the perspectives of non-human entities in
everyday design.

More-than-human, posthuman, participation, smart cities

††journalyear: 2022††copyright: rightsretained††conference: Participatory
Design Conference 2022: Volume 2; August 19-September 1, 2022; Newcastle upon
Tyne, United Kingdom††booktitle: Participatory Design Conference 2022: Volume
2 (PDC 2022 Vol. 2), August 19-September 1, 2022, Newcastle upon Tyne, United
Kingdom††doi: 10.1145/3537797.3537799††isbn: 978-1-4503-9681-3/22/08††ccs:
Human-centered computing Participatory design

##  1\. Introduction

Climate variability and long-term climate trends increase the likelihood and
severity of catastrophic weather events. These weather events can have a
destructive impact on both the ecological and human worlds. The recent Black
Summer bushfires in Australia, for example, burnt over 24 million hectares of
land (Australia and Royal Commission into National Natural Disaster
Arrangements, 2020) and killed or displaced three billion animals (Lily M van
Eeden et al., 2020). At the same time, the bushfires directly caused 33 deaths
(Australia and Royal Commission into National Natural Disaster Arrangements,
2020), reduced air quality to hazardous levels for humans (Di Virgilio et al.,
2021), destroyed thousands of buildings and caused major disruption to
critical infrastructure networks, bringing society to a standstill in affected
areas (Filkov et al., 2020). Climate scientists link the severity of the
2019/20 bushfire season—the most destructive ever recorded in Australia—with
climate variability and long-term climate trends, which are themselves linked
to technological changes since the Industrial Revolution (Abram et al., 2021;
Canadell et al., 2021; van Oldenborgh et al., 2021). The Black Summer
exemplified, in a brutal and disastrous manner, the consequences of changes in
one world (technological) without considering linkages with other worlds
(biophysical, ecological or human).

Given the interdependence of the biophysical, ecological, human and
technological worlds, participatory design researchers are increasingly
concerned with the participation of entities beyond the human in the design of
technology. Scholars of ‘posthuman design’ and ‘more-than-human design’, for
example, are experimenting with design processes to shift design mindsets.
Experiments include situating designers in the environment in which a
technological artefact will operate (Bastian, 2018; Wakkary, 2021) and even
encouraging designers to embody non-human entities in those environments, to
consider the experience of other species or things (Clarke et al., 2019). Yet,
these experiments do not provide guidance on how to legitimate the
perspectives of non-human entities through participatory design, instead
focusing on situated or embodied experiences for designers to break down the
boundaries between those designers and non-human entities.

In 2020, I worked with the Queanbeyan-Palerang Regional Council (‘the
Council’), as part of a team of researchers, to review the plans and progress
of a smart city project in a region affected by the Black Summer bushfires.
Our report recommended the Council adopt a more-than-human design framework,
though we were unable to provide clear processes for the Council to enact the
framework. This gap in design practice led to the review of theories of non-
human behaviour from other disciplines, in particular philosophy and cognitive
science, and eventually to the ‘intentional stance’.

To predict or explain the behaviour of other human or non-human entities,
people often refer to the mental states of the other entity (their beliefs,
desires or intentions) (Dennett, 1987). Dennett described this strategy of
referring to the mental states of others to predict or explain their behaviour
as “adopting the intentional stance” (Dennett, 1987). This paper explores how
the intentional stance might be repurposed to legitimate the perspectives of
non-human entities from the biophysical and ecological worlds, if those
entities were to participate in the design process. Two questions guide the
paper:

  * •

How does adopting the intentional stance as a heuristic enable designers to
account for the perspectives of non-human entities?

  * •

What non-human entities could designers consider by adopting the intentional
stance?

Each question is considered by reflecting on the smart city project. The paper
builds on previous work with the Council, imagining how adopting the
intentional stance might offer a process for the Council to enact the more-
than-human design framework in the context of smart lighting systems. Through
a process of experimentation and evaluation, the paper explores the potential
of one approach (adopting the intentional stance) to clarify design processes
for more-than-human participation.

##  2\. Background

This section shares definitions of each of the ‘worlds’, outlines posthuman or
more-than-human design, and discusses the intentional stance.

###  2.1. Biophysical, Ecological and Human Worlds

The biophysical world is defined in this paper as the four spheres that
support the existence of living things: the atmosphere (gases around the
earth), the hydrosphere (water on earth), the lithosphere (rocks, soils and
the earth’s crust) and the biosphere (the sum of all ecosystems). The
ecological world, on the other hand, is defined in this paper as living things
on earth—plants and non-human animals—at the level of individuals, species, or
individual ecosystems. Finally, the human world refers to individual humans
and human societies.

The theme for the 2022 Participatory Design Conference (PDC) encourages
authors and participants to explore how entities from worlds other than the
human world may participate in design. This paper focuses on the connections
between the biophysical, ecological, and human worlds, and explores how
adopting the intentional stance could enable the participation of entities
from the biophysical and ecological worlds in addition to the human world.

###  2.2. Posthuman Design and More-Than-Human Design

Design has been dominated by a ‘human-centred’ or ‘user-centred’ paradigm
since at least the 1980s (Forlano, 2017; Wakkary, 2021). These paradigms focus
the attention of designers on the needs of individual human users and/or
collectives of human users of technology, rather than technology itself.
Recently, however, rapid transformation of the technological world alongside
changes in the biophysical and ecological worlds have prompted a shift in the
attention of designers towards the interrelations between human and non-human
entities. An emerging posthuman design agenda encourages consideration of the
non-human in the design process, including non-human animals and plants along
with ‘things’ and the artificial (Forlano, 2017; Giaccardi and Redström,
2020). As Forlano (Forlano, 2017) outlines, posthuman design has been
influenced by theoretical approaches such as actor-network theory, feminist
new materialism, object-oriented ontology, and transhumanism. Inheriting from
these fields, the emerging posthuman design agenda encourages designers to
transcend the limited focus of human-centred or user-centred design on human
entities and consider a broader set of relations. Another term used to
describe this emerging design philosophy is more-than-human design. Scholarly
publications referring to more-than-human design have focused particularly on
the design of smart cities (e.g., Clarke et al., 2019; Loh et al., 2020;
Yigitcanlar et al., 2019). More-than-human design scholars have also drawn on
principles of relationality as understood in Indigenous epistemologies, which
may enable designers to respectfully accommodate the non-human (Lewis et al.,
2018; Escobar, 2018; Akama et al., 2020).

####  2.2.1. Participation of Non-Human Entities

For PDC 2022 we must ask – what might be considered ‘participation’ by non-
human entities? Scholars of more-than-human design have experimented with two
processes for non-human participation. In the first, designers are situated in
the biophysical and ecological environment in which technology they design
will operate, and encouraged to engage with non-human entities in that
environment as part of the design process (Wakkary, 2021; Springgay and
Truman, 2017; Bastian, 2018). This act is intended to break down barriers
between the design process and the biophysical and/or ecological worlds in
which designed technology will operate. Secondly, at PDC 2018 in Hasselt,
Belgium, a group of designers undertook several experiments including
embodying non-human animals as the designers navigated the city (Clarke et
al., 2019). This act was intended to encourage designers to “see the city”
from the perspectives of non-human entities, which might then inform smart
city design processes. However, as Akama et al. (Akama et al., 2020) note,
participation implies the equivalent of “human voice, rights, representation
and structures of decision-making.” While situated or embodied experiences for
human designers may enable designers to ‘see’ other worlds more clearly, there
is a need to build on these experiments to design processes that legitimate
the perspectives of non-human entities through participatory design, as we
have for human entities.

###  2.3. The Intentional Stance

Dennett first proposed the intentional stance in 1971 (Dennett, 1971) and
included the idea in his book of the same name in 1987 (Dennett, 1987).
Dennett argues that when we predict or explain the behaviour of an entity
(humans, animals, artifacts—any object or system), we view that entity at
varying levels of abstraction. In the first level, the physical stance, we
predict the behaviour of an object or system based on its physical structure.
We may abstract from the physical stance to the design stance, predicting the
behaviour of a system based on our experience and knowledge of how the system
is designed. Marchesi et al (Marchesi et al., 2019) outline a useful example
of adopting the design stance with respect to a car—we can predict that a car
will slow down when we press the brake pedal based on our knowledge of the
design of a car, rather than on our knowledge of the precise physical
mechanisms that make up the braking system in a car. The most abstract of all
the stances, the intentional stance, requires no knowledge of either physical
structure or design. We predict the behaviour of another system from our
explanations or interpretations of the beliefs and desires of the other
system. Dennett (Dennett, 1987) explains how we use this strategy as follows:

> Here is how it works: first you decide to treat the object whose behavior is
> to be predicted as a rational agent; then you figure out what beliefs that
> agent ought to have, given its place in the world and its purpose. Then you
> figure out what desires it ought to have, on the same considerations, and
> finally you predict that this rational agent will act to further its goals
> in the light of its beliefs. A little practical reasoning from the chosen
> set of beliefs and desires will in many—but not in all—instances yield a
> decision about what the agent ought to do; that is what you predict the
> agent will do.

Adopting the intentional stance might be a useful way to predict the behaviour
of an entity if it were to participate in design activities, by treating the
entity as if it had mental states. This does not lead to a theory of the
operation of the internal mechanisms of any agent, and it does not require
proof of the true intentionality of an agent. Rather it is a strategy for
interpreting the behaviour of an entity as if it were a rational agent that
governed its choice of action by considering its beliefs, desires or
intentions—or mental states (Dennett, 1987). The strategy builds on the
tendency of humans to attribute mental states to the entities whose behaviours
we intend to interpret. For this paper, then, there is a question as to the
conditions under which an entity from either the biophysical or ecological
world could be considered to have a mental state discernible to human
designers.

##  3\. Speculative Case Study: More-Than-Human Participation for Smart
Lighting Systems

In 2020, I worked as part of a team of researchers to review the plans and
progress for the Queanbeyan Smart City Precinct (’smart city project’). Our
report to the Council, overall, recommended an evolution in the design
framework—from a techno-centred framework to a framework based on more-than-
human design. While the overall recommendation was well received, the report
lacked specific recommendations on how to enact the renewed framework. Our
report encouraged the Council to think of the tensions between the interests
of residents in a smart city and the interests of non-human entities in the
ecological world, drawing on the lessons of the Black Summer bushfires. We
also encouraged the Council to engage with Indigenous design practitioners
during future design phases, to consider the relationality between smart city
technologies and the people and places in which those technologies are
embedded. Yet, we were unable to provide a clear process for Council staff
themselves to consider the perspectives of entities within the region other
than those of human residents, non-resident visitors or other humans managing
the smart city. Without such a process, it is difficult to envisage the
translation of the theories of posthuman or more-than-human design outside
academic research contexts and into the everyday practice of smart city
design. The lack of a clear design process to recommend to the Council led to
the review of other disciplines, such as philosophy and cognitive science, for
theories or heuristics that might translate into design processes. The section
below presents an imagination of how adopting such a heuristic—the intentional
stance—could legitimate the perspectives of two non-human entities towards the
design of smart lighting systems in Queanbeyan.

###  3.1. Adopting the Intentional Stance to Legitimate the Perspectives of
Trees and Air

Many smart cities include smart lighting systems, including the smart city
project administered by the Council. The lights in Queanbeyan shine brighter
when pedestrians are in the vicinity of the lighting system, to create “more
vibrant areas with a feeling of safety” (Queanbeyan-Palerang Regional Council,
2019). In Queanbeyan, then, human and non-human entities must co-exist with
artificial light at night, in variable intensities. The impact of artificial
light on humans is well researched (e.g., Hölker et al., 2010; Cho et al.,
2015). Ecologists have also raised the alarm about the impact of artificial
light on some non-human animals, such as sea turtles at the hatchling stage
(Salmon, 2003). However, the impacts on plants and elements of the earth are
largely unexplored. This section explores how adopting the intentional stance
might allow designers to predict the behaviour of these entities, in the
absence of definitive scientific guidance.

Plants possess chlorophyll which absorbs light to sustain their existence, but
they also use light as a source of information (Bennie et al., 2016). The
natural cycles of light guide plants to regulate circadian rhythms and
seasonal phenology, and also affect phenotypic variation (including variation
in growth and resource allocation) (Bennie et al., 2016). However, the
widespread use of artificial lighting by human societies outdoors alters these
cycles (Gaston et al., 2014). Illumination from street lighting is brighter
than and inconsistent with natural cycles of moonlight, resulting in many
plants experiencing artificial light at night at levels consistent with
physiological effects (even if in short duration) (Bennie et al., 2016).

If we adopt the intentional stance towards trees located in an area proposed
for a smart lighting system (entities from the ecological world), we would
treat those trees as rational agents. Based on the points raised in the
paragraph above, one might say that trees would believe in the importance of
growth and resource allocation consistent with natural daily and seasonal
cycles of light. The trees’ desires and intentions, then, could include
absorbing light within the optimal spectrum in natural cycles to optimise
photosynthesis. Following the process outlined by Dennett for the intentional
stance, a designer would predict that a tree ought to seek out light within
that spectrum and during those cycles. By extension, trees located within an
area proposed for a smart lighting system, participating in the design of the
smart city, would advocate for minimal disruption to lighting within those
parameters.

We might also wish to consider the perspectives of particles of air
surrounding a smart lighting system—entities from the biophysical world.
Excess artificial light at night can contribute to air pollution by
interfering with chemical reactions that naturally clean the air during the
night (Stark et al., 2010). Chemicals emitted from a variety of human
activities are broken down by a form of nitrogen oxide called the nitrate
radical, which only occurs in darkness as sunlight destroys the naturally
occurring chemical (Brown and Stutz, 2012). We might use this information to
try and predict how particles of air would act to avoid such disruption to air
filtration. Yet it is difficult to discern the mental states of particles of
air that would motivate such behaviour—what does a particle of air believe,
desire or intend to do, other than exist? Adopting the intentional stance
first requires identifying such mental states, which may not be possible for
non-living entities. In addition, it is difficult to identify individual,
localised entities in the atmosphere—could the intentions of individual air
particles be determined separately from the air as a whole? If not, how can we
identify entities from the atmosphere that should participate in the design of
a particular smart lighting system or smart city?

##  4\. Discussion

This section discusses the usefulness and limitations of the intentional
stance as a heuristic for more-than-human participatory design, and briefly
presents alternatives for consideration.

###  4.1. The Intentional Stance as a Heuristic

For the ecological world, this paper demonstrates through experimentation with
the example of a smart lighting system that the intentional stance could
become a heuristic for designers to predict the behaviour of some non-human
entities, such as non-human animals and plants. Drawing on the case study, the
Council could consider the perspectives of trees alongside the perspectives of
human stakeholders in the smart city—residents, non-resident visitors, and
those involved in the management of the smart city. The goal of such a process
is not to exclude the perspectives of human stakeholders, but to balance the
perspectives of humans alongside those of entities from other worlds. For
example, residents and non-resident visitors may desire that the pavement in a
certain area is illuminated alongside tree cover to improve accessibility and
promote safety. Following the process enabled by adopting the intentional
stance, designers may then consider tensions between the interests of human
stakeholders and those of trees, as outlined earlier. On the other hand,
interpreting the mental states of an element that makes up part of the
biophysical world—the air—was not straightforward. For the biophysical world,
then, adopting the intentional stance loses value as a simple heuristic for
designers (or anyone practicing design) to predict the behaviour of non-human
entities.

Entities from different worlds may require different methods or processes to
enable their legitimate participation in technology design. However, we must
not wait for an all-encompassing approach to participatory design for any non-
human entity. The design of technological systems continues apace, guided by
techno- or human-centred design philosophy, and heuristics may assist the
practice of everyday design to contribute, now, to avoiding ecocidal futures.
Instead, I encourage application, critique and re-imagination of the
intentional stance for entities from the ecological world, just as this paper
was developed on the foundation set by earlier experiments in more-than-human
design.

###  4.2. Limitations of the Intentional Stance

There are several limitations to adopting the intentional stance for the
participation of non-human entities from the ecological world, notwithstanding
its potential as a heuristic. Firstly, non-human entities may not act within
the rational dynamic assumed by the intentional stance. In the case of humans,
social psychology has documented our irrationality for decades (Tversky and
Kahneman, 1974). More recently, affective neuroscience has demonstrated the
centrality and importance of emotions to human decision making (Mlodinow,
2022). Further research might consider how non-human entities, from either the
biophysical or ecological worlds, act outside the bounds of rationality, and
how that behaviour may be incorporated into or considered separately from the
process prescribed by adopting the intentional stance.

Secondly, the intentional stance is focused on predicting the behaviour of an
individual agent or aggregates of individual agents, but not collectives of
agents. As shown in this paper, we may adopt the intentional stance to discern
the mental states and predict the behaviour of a tree, but what about a
forest? How might the perspective of a forest conflict with the perspective of
an individual tree? What additional processes are required, or how can the
intentional stance be amended, to consider the perspectives of collectives?

Thirdly, adopting the intentional stance for more-than-human participatory
design assumes that humans can and should ‘speak for’ non-human entities. The
perspective of a non-human entity predicted by a designer following such a
process will inevitably be imbued with the perspective of the designer towards
the non-human entity. For example, the information presented in the case study
on the physiology of trees, and how physiology might be affected by artificial
light, relied solely on desktop research conducted for this study. The
perspective of the tree was informed by an assessment of the validity and
reliability of evidence available in academic research publications. Further
research may add steps to the process to guide reflexive practice by designers
adopting the intentional stance—identifying sources of information and
interrogating positionality—to enable outsiders to contextualise human
predictions of non-human behaviour.

Finally, the case study adopts the intentional stance to interpret the
perspectives of a limited set of entities—entities within the immediate
vicinity of a smart lighting system. Further research could extend the
boundary of analysis to consider how such a design process might include
consideration of the impact of a smart lighting system more broadly. For
example, one could extend the analysis to consider the perspectives of
entities impacted by the supply chain for the smart lighting system (e.g., the
factory producing sensors that manage the intensity of light and the source of
energy for the Council area).

###  4.3. Alternatives to the Intentional Stance

####  4.3.1. Direct Sensing As Participation

For a more direct approach to more-than-human participatory design than
adopting the intentional stance, we could consider using environmental sensors
to capture signals from ecological or biophysical worlds to inform design
processes, or to convert signals from sensors into inputs for the operation of
a technological system. One might argue that using trees, for example, as
networked elements of a technological system reflects a techno-centred design
philosophy. However, identifying a ‘goal state’ for a tree (e.g., defining
indicators of a thriving tree), assessing the physiological health of trees in
Queanbeyan against those metrics over time, and adjusting the operation of
technology in response to signals might be one way to procure ‘participation’
of non-human entities.

####  4.3.2. Engaging With Indigenous Epistemologies

The growing engagement with Indigenous epistemologies in design research is a
welcome expansion of cultural perspectives in our research community. As
argued by Akama et al.(Akama et al., 2020), there is much for more-than-human
design to learn from cultural perspectives that prioritise pluriversal and
relational thinking and being. The quest for simple heuristics to guide
everyday designers to enact a more-than-human design framework is not intended
to limit or distract from the embrace of Indigenous epistemologies. Rather, it
is intended as a compliment to those efforts and is, indeed, informed itself
by the relational perspectives of those epistemologies. In addition, I
encourage critique of the heuristic proposed in this paper from Indigenous
perspectives.

##  5\. Conclusion

Posthuman and more-than-human design scholars are shifting the attention of
the design community from the prevailing techno- or human-centred design
paradigms towards the interrelations between humans and non-human entities.
This shift is urgent—the biophysical and ecological worlds that sustain us
physically and spiritually are rapidly transforming due, at least in part, to
our insensitivity to the interdependencies of life on earth. To translate
renewed design philosophies from the realms of academic research contexts into
the everyday practice of design, we need to develop clear processes to enact
more-than-human design. This paper explored the usefulness of adopting the
intentional stance—a strategy for interpreting the behaviour of non-human
entities drawn from philosophy—as a heuristic for more-than-human
participatory design. I encourage application, critique, re-imagination and,
even, formalisation of the intentional stance to enable the participation of
non-human animals and plants from the ecological world, considering the
limitations raised in this paper. Further research on methods of participation
for entities from the biophysical world is also encouraged, along with
consideration of alternative approaches to legitimate the perspectives of
entities from the ecological world. Without developing such heuristics for
everyday design, visions of more-than-human design for smart cities proffered
by our research community risk being sidelined in the practice of technology
design.

###### Acknowledgements.

My sincere thanks to Alex Zafiroglu, Elizabeth Williams, Ben Swift, Josh
Andres, Danny Bettay and anonymous reviewers for thoughtful feedback and
comments. Thank you also to members of the Queanbeyan-Palerang Regional
Council and my colleagues from the Australian National University—Lorenn
Ruster, Nischal Mainali and Teffera Teffera—who engaged in the project that
preceded this paper.

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# Multi-Band mm-Wave Measurement Platform Towards Environment-Aware Beam
Management

Aleksandar Ichkov, Aron Schott, Niklas Beckmann, Ljiljana Simić  Institute for
Networked Systems, RWTH Aachen University
Kackertstrasse 9, 52072 Aachen, Germany
{aic, asc, nbe<EMAIL_ADDRESS>
###### Abstract

Agile beam management is key for providing seamless millimeter wave (mm-wave)
connectivity given the site-specific spatio-temporal variations of the mm-wave
channel. Leveraging non radio frequency (RF) sensor inputs for environment
awareness, e.g. via machine learning (ML) techniques, can greatly enhance RF-
based beam steering. To overcome the lack of diverse publicly available multi-
modal mm-wave datasets for the design and evaluation of such novel beam
steering approaches, we demonstrate our software-defined radio multi-band mm-
wave measurement platform which integrates multi-modal sensors towards
environment-aware beam management.

##  I Introduction

Providing high rate connectivity in the millimeter-wave (mm-wave) bands is
predicated on robust beam steering to overcome the effects of beam
misalignment and blockage [1]. However, current state-of-the-art mm-wave beam
steering protocols are restricted to radio frequency (RF) based operations
with stringent requirements for accurate channel state information (CSI), and
are thus susceptible to the spatio-temporal variations of the sparse mm-wave
channel, resulting in poor real-world performance due to the overhead/latency
constraints of CSI acquisition [2]. To better adapt to the site-specific mm-
wave channel, lower complexity out-of-band approaches have been explored,
utilizing both RF-based multi-band transmissions and non-RF-based sensor
information (see [3] and references therein). In particular, integration of
multi-modal sensor inputs such as camera, radar, LiDAR, and GPS, can directly
improve RF-based beam steering by e. g. reducing the number of candidate beams
during beam sweeping and providing robustness to channel estimation errors.
Furthermore, integrating machine learning (ML) can help extract information
from the multiple sensor modalities to model the complex channel dynamics and
adapt beam steering decisions via environment-awareness in real-time.

Figure 1: Schematic of the multi-band mm-wave measurement platform with
connection types and signals:
(1) samples, (2) I–Q baseband signal (bandwidth support up to 400 MHz), (3) RF
signal ($f_{c}$ = 28/60 GHz),
(4) 2048$\times$128 point cloud, (5) 360° video stream, (6) 3D position
(latitude, longitude and altitude).

Towards this, several research groups are directly working on acquiring multi-
modal mm-wave datasets, e. g. [4, 5]. However, the design of practical
environment-aware beam steering requires a large number of open, comparable
datasets from a multitude of site-specific network deployments in order to
train/test ML approaches and most importantly, assess the generalization
performance beyond the pre-defined scenario(s). To address this need, we
demonstrate our multi-band mm-wave measurement platform which integrates
multi-modal sensor inputs, for evaluation of novel beam steering protocols
that intelligently adapt to the site-specific channel environment. In contrast
to [4, 5], we implement a packetized directional-TX/directional-RX mm-wave
link and several state-of-the-art beam steering protocols, supporting
technology-agnostic, wideband, multi-band RF transmissions. Our software
defined-radio (SDR) based measurement platform relies solely on commercial-of-
the-shelf components, making our system reasonably affordable, readily
customizable (in contrast to e. g. FPGA-based platforms [6]), and easily
extendable with additional sensor devices and mm-wave RF front-ends. To
support other research groups in leveraging our measurement platform design
for generating open, multi-modal mm-wave datasets, we plan to release our GNU
Radio framework implementation via [7] as open-source code, once a stable code
version is approved.

##  II Multi-Band mm-Wave Beam Steering Support

We implement a multi-band mm-wave packetized communication link with beam
steering capabilities using a 8$\times$2 + 8$\times$2 TX/RX phased antenna
array evaluation kit EVK02001 [8] (operating in the 28 GHz band, i.e. 5G-NR
FR2-1) and a 8$\times$4 + 8$\times$4 TX/RX phased antenna array evaluation kit
EVK06003 [9] (operating in the 60 GHz band, i. e. 5G-NR FR2-2 and IEEE
802.11ad/ay) by Sivers Semiconductors (_cf._ Fig. 1). In principle, our setup
allows simultaneous multi-band communication and data collection.

Host PC 1 generates a packet and sends the modulated baseband waveform samples
to the SDR (USRP X410), which generates an analog signal with sampling rate
$f_{s}$ at baseband frequency $f_{bb}$ and feeds it to the EVK. The code
implementation enables any candidate (standard-compliant) waveform to be
streamed via the USRP X410 with bandwidth support of up to 400 MHz. We note
that other USRP models are also supported, e.g. X310/N310 but with lower
bandwidth support of up to 160/100 MHz. The EVK directly upconverts the
baseband signal to the carrier frequency $f_{c}$ and transmits it over the
air. On the RX side, the received signal is downconverted by the EVK, sampled
and streamed by the USRP X410 to the host PC 2 where the packet is decoded.

We implement a number of state-of-the-art beam steering protocols that sweep
the full azimuth/elevation angular space by changing the TX/RX beam
orientations using a combination of electronic (i.e. 22 beam codebook entries
over $[-45^{\circ},45^{\circ}]$ azimuth range for both EVK02001/EVK06003) and
mechanical beam steering by a custom-made 3D turntable to cover the complete
azimuth and elevation range. We can thus collect measurements over fine-
grained 3D antenna orientations, estimating the received signal strength and
phase and frequency offsets for the respective TX and RX beam entries, which
is used for the link establishment and link recovery decision process.

##  III Environment-Awareness via Multi-Modal Sensor Inputs

The Ouster OS-1 LiDAR [10] with 128/2048 vertical/horizontal channels (200 m
maximum range and 20 Hz frame rate) and a GoPro MAX camera [11] (360∘
horizontal field-of-view at 30 fps) serve for capturing the 3D environment and
object detection. A GPS antenna obtains the 3D position at a rate of 1 Hz. The
sensors are connected to the TX/RX host PC, running the Robot Operating System
(ROS) in a Docker container [12], continuously collecting and time-stamping
the sensor measurements. To ensure data synchronization for post-processing
purposes, the host PC clock is used as a common reference to synchronize the
packetized communication link as well as the built-in clock of the GoPro MAX
camera.

## Acknowledgment

We thank L. Reiher at the Institute for Automotive Engineering (ika, RWTH) for
support with the LiDAR framework. This work has received funding by the German
BMBF in the course of the 6GEM research hub, grant number 16KISK038.

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