# MU-MIMO MAC Protocols for Wireless Local
Area Networks: A Survey

Ruizhi Liao, Boris Bellalta, Miquel Oliver, and Zhisheng Niu R. Liao, B.
Bellalta and M. Oliver are with NeTS Research Group, Department of Information
and Communication Technologies, Universitat Pompeu Fabra, Barcelona, 08018,
Spain (e-mail: {ruizhi.liao, boris.bellalta, miquel.oliver}@upf.edu).Z. Niu is
with NiuLab, Department Of Electronic Engineering, Tsinghua Unisersity,
Beijing, 100084, China (e-mail: niuzhs@tsinghua.edu.cn).

###### Abstract

As wireless devices boom, and bandwidth-hungry applications (e.g., video and
cloud uploading) get popular, today’s Wireless Local Area Networks (WLANs)
become not only crowded but also stressed at throughput. Multi-user Multiple-
Input and Multiple-Output (MU-MIMO), an advanced form of MIMO, has gained
attention due to its huge potential in improving the performance of WLANs.

This paper surveys random access based MAC protocols for MU-MIMO enabled
WLANs. It first provides background information about the evolution and the
fundamental MAC schemes of IEEE 802.11 Standards and Amendments, and then
identifies the key requirements of designing MU-MIMO MAC protocols for WLANs.
After that, the most representative MU-MIMO MAC proposals in the literature
are overviewed by benchmarking their MAC procedures and examining the key
components, such as the channel state information acquisition, de/pre-coding
and scheduling schemes. Classifications and discussions on important findings
of the surveyed MAC protocols are provided, based on which, the research
challenges for designing effective MU-MIMO MAC protocols, as well as the
envisaged MAC’s role in the future heterogeneous networks, are highlighted.

###### Index Terms:

MAC, MU-MIMO, IEEE 802.11, WLANs, MUD, MUIC, CSI, Scheduling.

##  I Introduction

IEEE 802.11 is a set of Physical Layer (PHY) and Medium Access Control (MAC)
specifications for the prevalent Wireless Local Area Networks (WLANs). Current
IEEE 802.11 WLANs contribute to approximate $40\%$ of overall Internet traffic
[1]. As wireless devices rapidly increase, and the wireless transmission
evolves towards gigabits per second, IEEE 802.11 WLANs are set to dominate the
way of Internet access at homes and working places in the future.

Multi-user Multiple-Input and Multiple-Output (MU-MIMO), introduced by IEEE
802.11ac [2], is one of the most crucial techniques that lead WLANs towards
the gigabit era. Compared to Single-user MIMO (SU-MIMO), which focuses on
transmitting to a single destination, MU-MIMO holds the following three
advantages: (1) The increased throughput. By employing SU-MIMO, the
theoretical capacity gain can be manifested by a multiplicative factor of
$min\\{N_{\text{t}},N_{\text{r}}\\}$, where $N_{\text{t}}$ and $N_{\text{r}}$
are the number of transmitting and receiving antennas [3][4]; while in the
case of MU-MIMO, the multiplicative factor can be further extended to
$min\\{aN_{\text{t}},bN_{\text{r}}\\}$, where $a$ and $b$ are the number of
simultaneous transmitters and receivers; (2) The increased diversity gain. The
spatially distributed STAs make the MU-MIMO system more immune to the channel
rank loss and the antenna correlation [5], which may affect the SU-MIMO system
performance by limiting the available transmission rates; (3) The reduced
terminal cost. The MU-MIMO system supports multiple spatially separated STAs
(even only equipped with a single antenna) to simultaneously communicate with
the Access Point (AP), which makes the development of compact and low-cost
user terminals possible.

Considerable research efforts have been made to approach the MIMO capacity at
the PHY layer [6][7], and a comprehensive overview can be found in [8].
Following the PHY advance, corresponding MAC enhancements, especially the MU-
MIMO based ones, have sprung up.

MAC, used among multiple stations (STAs) to share a common wireless channel,
can be dated back to the pioneer protocols used in the ALOHA network in the
$1970$s [9] to the current Carrier Sense Multiple Access with Collision
Avoidance (CSMA/CA) based IEEE 802.11 Distributed Coordination Function (DCF).
Since the IEEE 802.11 MAC mechanism only supports one single transmission at a
time, which underutilizes the full potential of the spatial domain of MU-MIMO
transmissions, thus, MU-MIMO MAC proposals have tried to adapt the frame
structure, as well as their operation procedures to control the parallel
transmissions among STAs.

There are two main MAC categories: (1) the fixed-assignment one, where the
channel frequencies, the access time, mutually orthogonal codes or different
polarization is predefined for each STA, namely, Frequency Division, Time
Division, Code Division or Polarization Division Multiple Access (FDMA, TDMA,
CDMA and PDMA); and (2) the random access one, where each STA independently
determines when to compete for the channel, e.g., Aloha and CSMA/CA. It is
worth to note that Space Division Multiple Access (SDMA) is a medium access
scheme by exploring parallel spatial streams. In this sense, the MU-MIMO
transmission, where multiple spatially-separated nodes are involved in
parallel transmissions, is a form of SDMA. Thus, SDMA schemes and MU-MIMO
transmissions are used interchangeably in this paper.

Due to the following three reasons, the random access based CSMA/CA has
dominated the MAC mechanism of WLANs. First, the backward compatibility. The
initial WLAN traffic was sporadic, bursty, and asymmetrical between uplink and
downlink. Although in the past decade, the traffic load has increased
significantly, and the traffic pattern has evolved from mainly web browsing
and file transfers to a wide variety of applications, there are still vast
amount of legacy STAs based on CSMA/CA. Secondly, coexistence with other
networks. Neighbouring WLANs, wireless sensor networks and Bluetooth personal
area networks, that are all operating in the Industrial Scientific Medical
(ISM) band, present significant interference to each other. CSMA/CA offers a
simple but effective solution (i.e., listen before transmitting) to share the
unlicensed spectrum among competing networks. Thirdly, the implementation
simplicity. The implementation of a random access scheme is simpler compared
to others. Since there is no need to use accurate clocks for synchronization,
nor to execute complex functions for scheduling.

The central point of the paper is to study random access based MAC mechanisms
for MU-MIMO enabled WLANs. The main contributions of the paper are threefold.
(1) We report the IEEE bodies’ MAC progress, as well as survey and categorize
the most relevant MU-MIMO MAC proposals in the literature. (2) By doing such
review, we identify key requirements for designing efficient MU-MIMO MAC
protocols, such as the channel state information (CSI) acquisition, de/pre-
coding and scheduling schemes. These requirements are used to benchmark MU-
MIMO MAC proposals in the literature. (3) We provide highlights and
discussions on important findings and research challenges after each
subsection of the literature review, and give our thoughts about possible
future directions on the MU-MIMO MAC design, such as uplink MU-MIMO, new
backoff algorithms and full-duplex transmissions.

The rest of the paper is organized as follows. First, Section II briefly
overviews the evolution of IEEE 802.11 standards/amendments and their
fundamental MAC mechanisms to clarify the MAC development promoted by the IEEE
standard body. Next, Section III identifies the key requirements for designing
MU-MIMO MAC protocols in WLANs. Then, Section IV surveys and classifies the
most prominent MU-MIMO MAC protocols in the literature. Afterwards, Section V
discusses the research challenges and future directions. Finally, Section VI
concludes the paper.

TABLE I:  Terms and Abbreviations

Access Category (AC) Additive White Gaussian Noise (AWGN) Network Allocation
Vector (NAV) Access Point (AP) Aggregated MAC Protocol Data Unit (A-MPDU)
Orthogonal Frequency Division Multiplexing (OFDM) Acknowledgement (ACK)
Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) Quadrature
Amplitude Modulation (QAM) Backoff (BO) Channel State Information (CSI)
Quality of Service (QoS) Clear-to-Send (CTS) Code Division Multiple Access
(CDMA) Reduced Inter Frame Space (RIFS) Contention Window (CW) Direct Sequence
Spread Spectrum (DSSS) Short Inter Frame Space (SIFS) DCF Inter Frame Space
(DIFS) Distributed Coordination Function (DCF) Signal-Interference-Noise Ratio
(SINR) Dirty Paper Coding (DPC) Enhanced Distribution Channel Access EDCA
Signal-Noise Ratio (SNR) Explicit Compressed Feedback (ECFB) Frequency
Division Multiple Access (FDMA) Single-user Multiple-Input Multiple-Output
(SU-MIMO) First-in First-out (FIFO) Frequency Hopping Spread Spectrum (FHSS)
Software Defined Radio (SDR) High Throughput (HT) Minimum Mean Square Error
(MMSE) Successive Interference Cancellation (SIC) Maximum Likelihood (ML)
Multi-Packet Reception (MPR) Time Division Multiple Access (TDMA) Medium
Access Control (MAC) Multi-Packet Transmission (MPT) Transmit Opportunity
(TXOP) Physical Layer (PHY) Multi-user Detection (MUD) Very High Throughput
(VHT) Request-to-Send (RTS) Multi-user Interference Cancellation (MUIC)
Wireless Local Area Networks (WLANs) Station (STA) Mingle-user Multiple-Input
Multiple-Output (MU-MIMO) Zero Forcing Beamforming (ZFBF)

##  II The Evolution of IEEE 802.11 and MAC Schemes

This section presents an evolutionary overview of IEEE 802.11
standards/amendments, and also introduces how the IEEE 802.11 specified MAC
schemes work. This overview does not go through all aspects of IEEE 802.11
standards/amendments, but focuses on the background information that is
closely related to the topic of the paper, namely, medium access control. Due
to a considerable amount of technical terms and abbreviations have been used,
Table I is given to summarize important terms for the reader’s convenience.

###  II-A IEEE 802.11 Standards/Amendments

####  II-A1 Standards

Loosely speaking, both standards and amendments can be interchangeably used to
refer to different variants of IEEE standards or amendments. However, a more
strict nomenclature designates standards as documents with mandatory
requirements (denoted as IEEE 802.11 followed by the published year, e.g.,
IEEE 802.11-2012), and amendments as documents that add to, remove from, or
alter material in a portion of existing standards [10] (denoted as IEEE 802.11
followed by a non-capitalized letter or letters, e.g., IEEE 802.11n or
802.11ac).

Since 1997, IEEE has released four standards: 802.11-1997, 802.11-1999,
802.11-2007 and 802.11-2012. IEEE 802.11-2012 [11] is the latest and the only
version that is currently in publication. Standards are continuously updated
by amendments, e.g., 802.11-2012 is created by integrating ten amendments such
as 802.11n and 802.11p with the base standard 802.11-2007, which was replaced
since the release of 802.11-2012. In other words, each standard will be
superseded by its successor in its entirety.

####  II-A2 Amendments

In 1999, two amendments were first introduced: (1) IEEE 802.11a operates in
the $5$ GHz band using the Orthogonal Frequency Division Multiplexing (OFDM)
modulation with a maximum data rate of $54$ Mbps; (2) IEEE 802.11b operates in
the $2.4$ GHz band using the Direct Sequence Spread Spectrum (DSSS) modulation
with a maximum data rate of $11$ Mbps. Compared to 802.11-1997, 802.11b
substantially increases the data rate (from $2$ Mbps to $11$ Mbps) using the
same modulation technique and the frequency band, which made 802.11b the then-
definitive WLAN technology. In 2003, IEEE 802.11g, a new amendment working in
the $2.4$ GHz band was ratified. It extends 802.11b with a maximum data rate
of $54$ Mbps. IEEE 802.11n [12], ratified in 2009, operates in either $2.4$
GHz or $5$ GHz band, boosting the data rate to $150$ Mbps ($600$ Mbps by $4$
streams) by utilizing MIMO.

802.11ac [2] is the latest IEEE amendment approved in 2013. It is operating
exclusively in the $5$ GHz band. Driven by the need for higher speed, 802.11ac
aims to provide an aggregated multi-station throughput of at least $1$ gigabit
per second, namely, Very High Throughput (VHT) WLANs. Compared to 802.11n,
this significant improvement is achieved by introducing novel PHY and MAC
features, such as wider bandwidths ($80$ and $160$ MHz), a denser modulation
scheme ($256$-QAM: Quadrature Amplitude Modulation), a compulsory frame format
(A-MPDU: Aggregated MAC Protocol Data Unit), and most importantly, downlink
MU-MIMO transmissions (supporting simultaneous transmissions of up to $4$ STAs
with the maximum number of $8$ streams).

Although each amendment is revoked as it is merged into the latest standard,
the sign of IEEE 802.11a/b/g/n/ac is often employed by vendors to denote the
capability and compatibility of their products.

TABLE II:  Features of Related IEEE 802.11 Standards/Amendments

Version Description Frequency Max. Data Rate Modulation 802.11-1997 WLAN MAC
and PHY Specifications 20 (MHz) @ 2.4 (GHz) 2 (Mbps) DSSS, FHSS 802.11-1999
Part II WLAN MAC and PHY Specifications 20 @ 2.4 2 DSSS, FHSS a Higher Speed
PHY Extension 20 @ 5 54 OFDM b Higher Speed PHY Extension 20 @ 2.4 11 DSSS g
Further Higher Data Rate Extension 20 @ 2.4 54 OFDM, DSSS 802.11-2007 Standard
Maintenance Revision – – – n High Throughput 20, 40 @ 2.4, 5 150 x 4 OFDM
802.11-2012 Accumulated Maintenance Changes – – – ac Very High Throughput 20,
40, 80, 160 @ 5 866.7 x 8 OFDM ax High Efficiency WLAN (approx. 2019) Below 6
GHz - OFDM

####  II-A3 Next Amendment-802.11ax

In March 2014, IEEE created a new task group-802.11ax [13], aiming at
delivering High Efficiency WLANs (HEW) in both indoor and outdoor high density
scenarios. 802.11ax will operate in frequency bands between $1$ and $6$ GHz.
In terms of performance, the focus of the amendment has shifted from improving
the aggregated system throughput to the throughput observed by each STA,
targeting at at least four-time per-STA throughput increase comparing to the
existing standards and amendments. The ongoing amendment is in its early
stage, and is estimated to be finished in 2019. Currently, the study group is
discussing the 802.11ax usage models focusing on the dense deployment [14],
potential technologies such as full-duplex, uplink MU-MIMO and Massive MIMO
[15], and functional requirements such as the system performance, the spectrum
efficiency, the operation bands and the backward compatibility [16].

The key features of the above mentioned IEEE 802.11 standards/amendments are
given in Table II, where FHSS stands for Frequency Hopping Spread Spectrum.

####  II-A4 New Frequency Bands of IEEE 802.11

Besides the traditional frequency bands ($2.4$ and $5$ GHz), IEEE 802.11 has
extended to support other bands.

IEEE 802.11ad [17], another VHT WLAN amendment, will operate in the $60$ GHz
band and focus on multi-gigabits per second data transmissions in a short
range point-to-point links (around $10$ meters). A typical application
scenario of 802.11ad is the wireless transmission of lightly compressed or
uncompressed high-definition videos for home entertainment systems. Due to
$60$ GHz band’s characteristics of high propagation loss and high attenuation,
directional transmissions and receptions are required.

IEEE 802.11ah [18] will operate in the sub-GHz band. The main purposes of the
amendment are to introduce power saving and STA grouping mechanisms. A typical
use case is a smart metering network with many sensor nodes, where high
collision probability and hidden nodes are expected. 802.11ah will partition
nodes into groups to save power and to reduce the channel contention by
assigning the channel to nodes of a given group at a given time [19][20].

Due to the specific purpose of each amendment and unique features of the
employed frequency, the MU-MIMO MAC schemes designed for WLANs of the
traditional bands can not be directly applied to these new amendments. For
example, 802.11ah relies on the highly centralized medium access scheme, while
802.11ad has to utilize the beam sweeping technique to detect STAs rather than
the omnidirectional carrier sensing adopted by IEEE 802.11 DCF. Therefore,
this paper preserves its focus on MAC proposals for the traditional bands,
i.e., $2.4$ and $5$ GHz. However, the potential collaborations at the MAC
level between protocols of traditional and new bands will be discussed in
Section V-Future Directions.

###  II-B IEEE 802.11 Medium Access Control

Although IEEE 802.11 has specified three MAC mechanisms, namely, DCF, Point
Coordination Function (PCF) and Hybrid Coordination Function Controlled Access
(HCCA), this paper only focuses on the distributed and random access based MAC
schemes, because PCF and HCCA (i.e., the centralized schemes) are neither
widely adopted by the industry nor the academia.

####  II-B1 Distributed Coordination Function

DCF is the fundamental medium access scheme of IEEE 802.11 based WLANs. It
relies on CSMA/CA to detect and share the wireless channel among STAs. DCF can
either operate in the basic access scheme (Figure 1(a)) or the optional
Request-to-Send/Clear-to-Send (RTS/CTS, Figure 1(b)) scheme. DCF mandates STAs
to keep sensing the channel. If the channel has been idle for DCF Inter Frame
Space (DIFS), each STA starts decreasing a backoff (BO) timer chosen from its
Contention Window (CW) to compete for the channel. The STA with the lowest BO
wins the channel contention and starts to transmit frames. Collisions occur if
more than one STA happens to choose the same random BO. When a transmitted
frame is successfully received, the receiver waits for a Short Inter Frame
Space (SIFS) and then sends back an Acknowledgement (ACK). Note that as soon
as the winning STA sends out a frame, other STAs will notice the channel has
become busy, therefore immediately freeze their BO timers. These STAs will
wait the channel to be idle for another DIFS, and resume decreasing the
remaining BO timers. The STA who previously succeeded the channel contention
will have a new BO timer at its next transmission attempt.

Examples of a successful transmission for the basic access and the RTS/CTS
schemes are shown in Figure 1, where B denotes the channel is initially busy.
Please refer to the IEEE standard 802.11-2012 [11] for more details about DCF.

(a) A successful transmission of basic access

(b) A successful transmission of RTS/CTS

Figure 1: 802.11 DCF transmission procedures

####  II-B2 Enhanced Distribution Channel Access

IEEE 802.11e [21] proposes an extension to DCF-Enhanced Distribution Channel
Access (EDCA), as a response to the demand of Quality of Service (QoS) for
voice and video applications. The main differences between DCF and EDCA are
twofold. First, the former does not differentiate traffic from different
applications, while the latter classifies traffic into four Access Categories
(ACs) with different priorities: Voice (AC_VO), Video (AC_VI), Best Effort
(AC_BE) and Background (AC_BK). By doing so, EDCA is able to assign ACs with
different parameters. For example, the maximum Transmit Opportunity (TXOP, a
contention-free interval, during which a STA can transmit as many frames as
possible) for AC_VO and AC_VI are $1.504$ ms and $3.008$ ms, respectively.
Secondly, it is also different that the instant of time at which DCF and EDCA
mandate STAs to decrease the BO timer. In DCF, STAs decrease the BO timer at
the end of each slot, while in EDCA, the decrement occurs at the beginning of
each slot. Please refer to [11] and [22] for detailed comparisons of DCF and
EDCA, and [23] for QoS supports in WLANs.

##  III Requirements for Designing MU-MIMO MAC Protocols in WLANs

MU-MIMO transmissions in WLANs have two communication paths, the uplink one
(i.e., STAs simultaneously transmit frames to the AP, which is also referred
as the MIMO-MAC channel) and the downlink one (i.e., the AP sends data to a
group of STAs in parallel, which is also referred as the MIMO-broadcast
channel). The MU-MIMO uplink and downlink transmissions face different
challenges, and hence, have different requirements in designing MAC protocols.

###  III-A De/Pre-coding Schemes for Simultaneous Receptions/Transmissions

In the uplink, the AP needs to separate the simultaneously transmitted signals
from STAs, which is the Multi-user Detection (MUD) problem. In the downlink,
the AP has to, firstly, select a group of STAs based on a certain criterion
such as the queue occupancy, given that the selected STAs have to be spatially
non-correlated, which is the scheduling problem, and, secondly, precode the
outgoing frames to null the interference among concurrent spatial streams,
which is the Multi-user Interference Cancellation (MUIC) problem. An
illustration of MU-MIMO uplink and downlink transmissions is given in Figure
2.

The design of MUD/MUIC schemes is beyond the topic of the paper. However, some
of the most popular MUD/MUIC schemes adopted in the surveyed papers, as well
as their strong points and drawbacks, are sampled (Table III).

Figure 2: Up/Down-link multi-user transmissions

####  III-A1 MUD Schemes for Simultaneous Uplink Receptions

##### Minimum Mean Square Error (MMSE)

Received signals at each antenna of the AP are multiplied by a complex weight
and then summed up. The weight is adjustable through minimizing the difference
between the summation of the output signal and a reference that is known by
both the AP and STAs. An example of the weight adjustment is to utilize the
steepest descending algorithm. The performance of the MMSE MUD scheme improves
as the number of AP’s antennas increases, and degrades as the network scales
up [24].

##### Maximum Likelihood (ML)

The ML MUD conducts an exhaustive search to extract the transmitted signals.
It provides the best detection performance, but comes with the highest
complexity that increases exponentially with the number of STAs, which makes
it infeasible in practical systems.

##### Sphere Decoding (SD)

Some SD based MUD algorithms have been proposed to reduce the complexity of
the pure ML MUD while to approach the performance of ML MUD. The idea is to
decrease the radius of the search scope by focusing on the vicinity of the ML
solution.

##### Successive Interference Cancellation (SIC)

The SIC MUD is an enhancement to MMSE. A detection algorithm is utilized by
estimating of the received power at the AP. The signal with the highest power,
which is the least interfered by others, is detected. This detected signal is
then subtracted from mixed signals, and the next highest signal is singled out
using the same process until the lowest STA signal is determined. The SIC MUD
tends to be erroneous at the signal classification stage. The false deduction
from composite STA signals may propagate the error to following calculations
[25].

####  III-A2 MUIC Schemes for Simultaneous Downlink Transmissions

Although simultaneous downlink transmissions from the AP to multiple STAs can
be seen as a combination of several single-user transmissions, STAs’ random
and independent locations make it very challenging to jointly null multi-user
interference at the STA side. Therefore, most proposals in the literature
precode outgoing signals at the AP to minimize interference among simultaneous
streams.

##### Zero Forcing (ZF)

In the ZF scheme, the original signal is multiplied by the pseudo-inverse of
the channel matrix to completely null the MUI. The conditions are (1) the AP
has the full CSI, and (2) the channel is invertible. By multiplying the
pseudo-inverse weight, the ZF scheme also increases the error rate (because
the noise vector is amplified). The amplified noise vector indicates that ZF
can only perform well in the high Signal-to-Noise Ratio (SNR) region. In
addition, the ZF scheme requires that the number of total receiving antennas
is not less than that of transmitting antennas [26].

In comparison, the MMSE scheme can minimize the overall error rate without
amplifying the noise. [25] and [26] show that the MMSE scheme performs better
than ZF in the low SNR region, and approaches the performance of ZF in the
high SNR region.

##### Block diagonalization (BD)

BD is a generalized channel inversion technique, especially when receivers
have multiple antennas [6]. Singular value decomposition (SVD) is employed to
remove unitary matrices, which makes the computational complexity of BD higher
than MMSE.

##### Dirty Paper Coding (DPC)

DPC is a non-linear precoding scheme firstly introduced by Costa [27], which
can achieve the optimum performance at the cost of significant computing
complexity. The idea is to add an offset (the negative value of the
interference that is known at the AP) to the transmitted signal, which hints
that (1) the AP has to know the interference in advance, and (2) the AP always
has available codewords, i.e., infinite length of codewords, which make DPC
not suitable for practical use.

TABLE III: Features of MUD/MUIC Schemes

Name Type Main Features Remarks Zero Forcing (ZF) Linear, MUD/MUIC Complete
interference cancellation with full CSI Noise amplified Minimum Mean Square
Error (MMSE) Linear, MUD/MUIC Complete interference cancellation with full CSI
Outperform ZF at low SNR Maximum Likelihood (ML) Nonlinear, MUD Performance
bound of MUD Exhaustive search; Exponential complexity Successive Interference
Cancellation (SIC) Nonlinear, MUD Trade-off between ML & MMSE Error
propagation Block diagonalization (BD) Linear, MUIC More complex than MMSE
SVD; Multi-antenna receivers; Generalized channel inversion Dirty Paper Coding
(DPC) Nonlinear, MUIC Performance bound of MUIC Infinite codewords;
Impractical for use

###  III-B Channel State Information Acquisition

MUD and MUIC schemes allow MU-MIMO systems to separate simultaneously
received/transmitted frames, and achieve the spatial multiplexing gain.
However, it is important to point out that, in the above discussion, the
possession of CSI is assumed at the AP.

Most proposals in the literature integrate the CSI acquisition into MAC
operations. There are generally two types of CSI: the statistical CSI and the
instantaneous one. The former employs the statistical characteristics of the
channel (e.g., fading distribution, average channel gain and spatial
correlation) to decide the CSI, which performs well in scenarios where the
channel has a large mean component (i.e., a large Rician factor) or strong
correlation (either in space, time, or frequency) [28].

The instantaneous CSI (or the short-term CSI) means the current channel state
is known, which enables the transmitter to adapt its outgoing signal. Because
wireless channel varies over time, the instantaneous CSI has to be estimated
repeatedly on a short-term basis. The acquisition of CSI can be done by
estimating a training sequence known by both transmitters and receivers. In
the uplink, the AP can easily extract the uplink CSI from the PHY preambles of
received frames. While, for transmissions in the downlink, the acquisition of
the CSI is not that straightforward. Depending on who computes the CSI, there
are two CSI feedback schemes: (1) the implicit feedback (Figure 3(a)), where
the AP computes the CSI by estimating training sequences sent from STAs, and
(2) the explicit one (Figure 3(b)), where STAs calculate the CSI by estimating
the training sequence sent from the AP, and then STAs feedback the calculated
CSI to the AP.

(a) Implicit CSI feedback scheme

(b) Explicit CSI feedback scheme

Figure 3: Implicit & Explicit CSI feedback procedures

By assuming the reciprocity of up/down-link channels, the implicit feedback
scheme produces less overheads compared to the explicit one. However, in a
practical WLAN system, the channel and interference seen by the STAs are
generally not the same as those seen by the AP due to their different
transmitting/receiving filters and PHY paths. Therefore, the antenna
calibration [2] is usually needed to reduce the distortion if implicit
feedback is adopted.

The explicit feedback scheme, i.e., STAs feedback the CSI, provides higher CSI
resolution, but also higher overhead. MAC control frames are usually extended
to support the CSI feedback in the literature, while an explicit compressed
Feedback (ECFB) scheme is introduced by IEEE 802.11ac to schedule and compress
the volume of CSI feedback.

No matter which CSI feedback scheme is applied, the implicit one or the
explicit one, the frequency of CSI feedback would significantly affect the
network performance. It is because the frequent CSI feedback increases
overheads, while the infrequent one results in the outdated CSI that leads to
interference among parallel streams. Please refer to [29] and [30] for more
details about implicit and explicit CSI feedback schemes.

###  III-C The Scheduling Scheme

Another key point for designing MU-MIMO MAC protocols is the scheduling
scheme. It is used to select a group of STAs or frames for transmissions,
which can optimize certain aspects of the system performance according to the
specific grouping criteria. The design of the scheduling scheme can be divided
into two parts: the scheduling in the uplink and downlink. The latter can be
easily categorized by different scheduling algorithms (e.g., the destination
based round-robin scheme or the frame based first-in first-out scheme), while
the characterization of the former is not straightforward. The reason and
categorization of the uplink scheduling schemes are as follows.

####  III-C1 Scheduling in the Uplink

In the uplink, it is very challenging to make a joint scheduling decision
among spatially distributed STAs. As shown in Figure 4, only three of surveyed
papers considered scheduling schemes, which will be described in details in
the protocol review Section IV.

Figure 4: Categories of uplink transmissions

Depending on whether the RTS/CTS exchanging process is employed (i.e., whether
the AP has played a coordinating role in exchanging control frames before
transmitting data), uplink transmissions are categorized into the coordinated
and the un-coordinated ones. In the un-coordinated scenario, STAs utilize the
random MAC mechanism to decide who will be allowed for transmissions, which
have two cases: synchronous [31] and asynchronous [32] data transmissions, as
shown in Figure 5. The synchronous scheme lets multiple STAs that
coincidentally choose the same BO to transmit data frames simultaneously,
while the asynchronous one allows STAs to transmit frames along with other
ongoing transmissions.

(a) Synchronous data transmissions

(b) Asynchronous data transmissions

Figure 5: Un-coordinated uplink channel access

In the coordinated scenario, STAs utilize the MAC random mechanism to contend
for the channel, while let the AP to decide who will be involved in the
followed parallel transmissions. The coordinated uplink access scheme implies
the involvement of the AP (as a coordinator) and the employment of RTS/CTS
exchanges [33]. The AP extracts the interested information from RTSs sent by
the contending STAs, and then makes scheduling decisions for simultaneous
frame transmissions (i.e., the scheduled transmissions), or the AP just
responds to the received RTSs to notify who have won the channel contention
(i.e., the un-scheduled transmissions). A general example of the coordinated
uplink access is shown in Figure 6, which can account for both scheduled and
un-scheduled cases depending on whether the CTS is extended to support
scheduling.

Figure 6: Coordinated uplink channel access

Although the un-coordinated uplink channel access requires fewer modifications
compared to the coordinated one, it is likely that the spatial domain will be
underutilized. The reason is that the concurrent uplink access of the un-
coordinated scheme is based on the randomness of the IEEE 802.11 backoff
mechanism. In comparison, the coordinated uplink channel access lets the AP to
mediate the uplink transmissions by either just notifying a group of STAs that
successfully won the channel contention or making a scheduling decision that
aims to optimize the system performance. Obviously, the coordinated scheme
will introduce overheads (e.g., extra fields in RTS/CTS) that are needed for
the AP to best exploit the spatial domain.

####  III-C2 Scheduling in the Downlink

Compared to the uplink, the AP plays a more direct role in the downlink
scheduling, which can be classified into the packet based scheduling and the
STA based one. In principle, the following downlink scheduling schemes can be
applied to uplink transmissions. However, they are adopted in very few
proposals due to the difficulty and overheads to make uplink scheduling
decisions for spatially-distributed STAs.

The packet based scheduling algorithms utilize the packet queueing status at
the AP as the scheduling metric to assemble multiple packets for MU-MIMO
downlink transmissions. The relevant packet based scheduling algorithms
include First-in First-out (FIFO) [34, 35, 36, 37], weighted fair queue (WFQ,
weight based on the priority or the type of packets) [38, 39], earliest
deadline first (EDF, based on the delay or waiting time of packets), greedy
[40, 41], etc.

The STA based scheduling employs some criteria to identify a set of STAs for
simultaneous downlink transmissions. These criteria include the channel state
[42, 43, 44, 45, 46], spatial compatibility, fairness, etc. The pure channel
condition based scheduling is also called opportunistic scheduling that
singles out a set of STAs with best channel conditions by benefiting from the
multi-user diversity. A similar concept is applied by the spatial
compatibility based scheduling, which examines STAs’ spatial correlations to
minimize the interference. Neither of them has taken the fairness into
account, which is considered by the round-robin scheduling.

A combination of the above mentioned scheduling schemes is usually considered.
For example, the proportional fair scheduler usually considers a product of
the channel capacity and fairness. However, as we can see from the above, the
most commonly used scheduling schemes are FIFO and opportunistic, which are
followed by greedy and WFQ. The reasons could be as follows. Comparing to
cellular networks, (1) WLANs consist of fewer STAs, (2) WLAN STAs are more
stable in terms of moving speeds and residing environments, and (3) the AP is
usually less powerful than the base station.

The combination of several criteria hints that parameters from different
layers should be jointly considered [47], which is the concept of cross-layer
scheduling as shown in Figure 7, where $q(t)$ and $H(t)$ represent the
queueing and the channel states at the time $t$.

Figure 7: Queueing and channel based cross-layer scheduling

####  III-C3 Cross-layer Scheduling

The cross-layer scheduling has the promise to achieve the optimal system
performance by sharing and configuring parameters from different layers, such
as the channel information at the PHY layer, the queueing state at the MAC
layer and the routing information at the network layer. Unfortunately, the
cross-layer scheduling remains far more complex than simply combining these
parameters. The reason is that the interaction among the layers breaks the
conventional Open System Interconnection (OSI) layered structures and creates
tensions between the performance and the stability of systems, which could
lead to unexpected consequences as the wireless network scales up [48].

In general, together with the CSI acquisition and other layers’ key
parameters, the following points should be taken into account for the cross-
layer design.

  * •

System Complexity: As the cross-layer design breaks the conventional layered
structure, the new wireless system could be incompatible with conventional
ones. Besides, since the maintenance or upgrade of the cross-layer protocol is
no longer isolated within each layer, any parameter changes must be carefully
traced and coordinated [48].

  * •

Design Constraints: Various data rates are usually applied to spatially
distributed STAs, which may cause interferences from stronger signals to
weaker ones in the downlink or the near-far effect in the uplink. Therefore, a
power control or a data rate selection scheme needs to be considered with the
MAC design. In addition, some QoS metrics, such as the average delay and the
jitter, are traditionally not in line with the MAC focus (e.g., decreasing
collisions and increasing throughput). Sometimes, maximizing throughput means
sacrificing transmission opportunities of some low-rate STAs. Thus, the
tradeoff of different performance metrics needs to be jointly considered and
given different weights [49] [50].

##  IV Survey of MU-MIMO MAC Protocols for WLANs

In this section, we look into prominent MU-MIMO MAC proposals in the
literature by focusing on the required features, performance gains, evaluation
tools, as well as the key assumptions they made.

###  IV-A MAC Proposals for The Uplink

####  IV-A1 Un-coordinated Channel Access

##### Synchronous Data Transmissions

Jin et al. in [31] present a simple MU-MIMO MAC scheme that relies on the
simultaneous transmissions from STAs. The MAC procedure is the same as
illustrated in Figure 5(a). The authors assume each STA has an orthogonal
preamble so that the AP can estimate the channel coefficients and
differentiate STAs. Once the AP knows the channel, it employs the ZF scheme to
separate the received signals. The authors extend the Markov chain model
proposed by Bianchi in [51] to analyze the performance of the proposed MU-MIMO
scheme in saturated conditions. Compared with SU-MIMO, the numerical results
show that the proposed MU-MIMO scheme obtains lower collision probability,
shorter delay and higher throughput in the low SNR and small network
conditions.

##### Asynchronous Data Transmissions

Tan et al. in [52] present a practical Spatial Multiple Access (SAM) scheme
for WLANs. SAM relies on a distributed MAC scheme called Carrier Counting
Multiple Access (CCMA) to allow asynchronous concurrent transmissions. A chain
decoding technique to separate simultaneously received frames is adopted. Each
STA maintains a transmission counter by detecting other STAs’ frame preambles,
and decides whether to contend for the channel. SAM is evaluated in SORA, a
Software Defined Radio (SDR) platform developed by Microsoft [53]. Evaluation
results show that the proposal can increase the throughput by $70\%$ over the
default IEEE 802.11 DCF.

Babich et al. in [32] develop a Markov chain analytical model for asynchronous
Multi-Packet Reception (MPR), where a STA is allowed to transmit even if other
STAs are already transmitting. More specifically, a STA is allowed to decrease
its BO counter as long as the channel is empty or the sensed number of ongoing
transmissions is below a threshold. A generic error correction code is assumed
to protect data frames. The MAC procedure is shown in Figure 5(b). Based on
the results obtained from the presented theoretical model and simulations, the
authors claim that the asynchronous MAC scheme can provide considerable
performance gains compared to the synchronous one due to higher utilization of
the channel.

Ettefagh et al. in [54] present a cluster-based MAC protocol for MU-MIMO
transmissions called CB-CSMA/CA. In CB-CSMA/CA, STAs are grouped in clusters,
and the AP is assumed to have MPR capabilities. STAs belonging to the same
cluster share a common backoff counter, which allows simultaneous
transmissions from multiple STAs when the counter reaches zero. As a result of
this, the channel access is competed among clusters. Simulation and analytic
results show that CB-CSMA/CA outperforms a pure STA-based contention approach
since it increases the chance that more than one STA can transmit at the same
slot.

Mukhopadhyay et al. in [55] explore the ACK-delay problem that arises in
asynchronous MPR. The ACK-delay problem refers to that, due to different
transmission durations of asynchronous uplink transmissions, the delayed ACKs
sent by the AP to those earlier-finished STAs can trigger STAs’ ACK time-out
counters, which could interrupt the ACK’s transmission and degrade the network
performance. Since Babich et al. in [32] did not consider the ACK-delay
problem, the authors in [55] propose to change the ACK-waiting STAs’ backoff
timer to be decreased only when the channel has been idle for DIFS. The
simultaneous transmissions are assumed to be decodable by the AP, and a single
data rate is also assumed. By comparing with Babich’s and IEEE 802.11 standard
schemes, the results show that the proposed one not only decreases the frame
collision probability and the average delay, but also increases the
throughput.

Lin et al. in [56] propose a MIMO concurrent uplink transmission scheme called
MIMO/CON, which can support both asynchronous and synchronous data
transmissions. A compressive sensing technique [57] is utilized to estimate
CSI from multiple concurrently received preambles, and ZF is adopted to
separate the data frames. A delayed packet decoding mechanism, namely, using
partially retransmitted information to decode the collided frames, is devised
to avoid the complete retransmission of all corrupted frames. A fixed frame
length is assumed, and the optimal transmission probability is assumed to be
known by STAs. Tan’s CCMA [52] is implemented to compare with the proposed
MIMO/CON. The results show that CCMA outperforms MIMO/CON when the AP has
fewer antennas, while MIMO/CON scales better as the number of antennas at the
AP increases.

Wu et al. in [58] propose a throughput analytical model for asynchronous
uplink transmissions, which is based on the Bianchi Markov chain model [51]. A
beacon sent by the AP will announce the maximum number of STAs that are
allowed to transmit in parallel. The MAC procedure is similar to the one
described above, in [52]. A fixed data rate is assumed and the network is
saturated. Zero-forcing with successive interference cancellation (ZF-SIC) is
employed to decode parallel data streams. By numerically deriving the
contention window size and other network parameters, the uplink throughput is
maximized. With those parameters, the authors derive a threshold of the number
of antennas at the AP, which shows no throughput benefit can be achieved by
adding more antennas. The reasons for that are: (1) the available transmission
time decreases as the number of STAs involved in the parallel transmission
increases; and (2) the collision probability increases as more antennas are
employed at the AP.

Kuo et al. in [59] present a leader-based MAC protocol for uplink MU-MIMO
transmissions. Similar to other asynchronous proposals, each STA counts the
number of concurrent transmissions to decide if it can start a new
transmission. In case there are multiple on-going transmissions, the proposed
protocol requires them to finish at the same time. The main difference
compared with previous proposals is that only the first transmission is
randomly selected (i.e., a leader will follow the CSMA/CA rules). The
remaining STAs will only start a concurrent transmission if they overheard a
transmission from the leader. The STAs’ scheduling is determined by a user
matching solution developed in the paper aiming to both maximize the system
throughput and fairness.

Table IV summarizes the main characteristics of the surveyed un-coordinated
uplink MU-MIMO MAC protocols.

TABLE IV:  Un-coordinated uplink MU-MIMO MAC protocols

Remarks Evaluation Tool CSI Scheme MUD Key Assumption Scheduling Jin [31],
compare SU and MU-MIMO, 2008 Analysis Implicit feedback Zero forcing
Orthogonal preambles - Tan [52], carrier counting, 2009 Testbed Implicit
feedback Chain decoding - - Babich [32], asynchronous MPR, 2010 Analysis - -
Code correction scheme - Ettefagh [54], cluster-based MU-MIMO, 2011 Simulation
+ Analysis Implicit feedback - Ideal channel - Mukhopadhyay [55], ACK-aware
MPR, 2012 Simulation + Analysis - - MPR frames decodable - Lin [56], delay
packet decoding, 2013 Simulation + Testbed Compressive sensing Zero forcing
Fixed frame length - Wu [58], throughput model, 2014 Simulation + Analysis
Implicit feedback ZF-SIC Fixed data rate - Kuo [59], leader-based contention,
2014 Simulation + Analysis Implicit feedback ZF-SIC Rayleigh fading User
matching

####  IV-A2 Coordinated Channel Access

##### Scheduled Data Transmissions

Huang et al. in [42] present an MPR MAC protocol that utilizes CDMA to
separate the compound frames. When the STA’s backoff counter reaches zero, a
function that considers the number of STAs in the network, the current channel
state and the MPR capability of the AP is used to schedule STAs. The MAC
procedure is illustrated in Figure 6. The CSI is claimed to be obtained from
the downlink transmission. Data frames are assumed to have the same length.
The analysis is based on the Bianchi’s model [51], and the optimal
transmission probability is obtained by one-dimensional search procedure, such
as Bisection and Newton-Raphson method [60]. Results obtained from the
analytic model and simulations show that the proposed scheme reduces
collisions and avoids considerable transmission errors.

Tandai et al. in [43] propose a synchronized access scheme coordinated by the
AP. On receiving applying-RTSs (A-RTSs) from STAs, the AP responds with a
pilot-requesting CTS (pR-CTS) to expect pilots. Based on the CSI estimated
from the sequential pilots, the AP sends a Notifying-CTS (N-CTS) to inform the
selected STAs for parallel transmissions. A unique subcarrier is assumed to be
allocated to each STA to differentiate A-RTSs, and the MMSE decoder is adopted
to separate the simultaneously received signals. According to the simulation
results, the proposed scheme can reduce the overhead and increase the
throughput.

Li et al. in [61] present a coordinated MAC protocol to improve Channel
Utilization in both Time and Spatial domain (CUTS). In the considered
approach, the AP first sends a grant packet to all STAs. Those backlogged STAs
reply to the AP with a transmission request. Then, the AP analyzes all the
information received, selects and signals those allowed STAs to transmit
simultaneously. The main innovation is that the channel contention is done in
the frequency domain. In CUTS, each STA selects one of the available
subcarriers to transmit a predefined signal, which is used by the AP to
identify the winning STAs. Both experimental and simulation results show the
significant gains achieved by CUTS.

##### Un-scheduled Data Transmissions

Zheng et al. in [33] propose a MU-MIMO MAC protocol called MPR-MAC, which
extends CTS and ACK to accommodate multiple transmitters. The MPR-MAC
procedure is the same as illustrated in Figure 6, where the STAs that won the
channel contention will transmit RTSs at the same time. The AP then replies
with an extended CTS that grants concurrent transmissions to the requesting
STAs. A set of orthogonal training sequences are assigned to STAs by the AP to
facilitate the channel estimation. A Finite Alphabet (FA) based blind
detection scheme is adopted for the frame separation. The network is assumed
to be saturated, and all data frames have the same length. The throughput
analytic model is based on Bianchi’s work [51], and the best transmission
probability is obtained via numerical techniques (i.e., a derivation
function). The authors claim that the throughput increases nearly linearly
with the number of antennas at the AP.

Since the MPR-MAC follows the conventional IEEE DCF access scheme, the
probability of more than one STA choosing the same random BO is low. In order
to increase the number of parallel transmissions, an enhancement called Two-
Round RTS Contention (TRRC, Figure 8) is also proposed in [33]. Compared to
MPR-MAC, TRRC has two RTS contention rounds. Namely, instead of sending a CTS
after the first RTS round, the AP waits for an extra round to recruit more
RTSs. The results show that TRRC obtains a further $7\%$ throughput increase.

Figure 8: TRRC: Two-Round RTS Contention

Barghi et al. in [62] present an MPR-aware MAC protocol for receiving two
concurrent frames by introducing a waiting time window ($t_{\text{w}}$) at the
AP. Specifically, when the AP receives a first RTS, it will wait for a time
period of $t_{\text{w}}$ to recruit a second RTS for double-frame receptions.
CTS and ACK are extended with an extra address field to accommodate two STAs.
A space-time code scheme is adopted to detect multiple frames. The channel is
assumed to be error-free and channel coefficients are assumed to be known.
Based on the obtained results, the authors claim that, by widening
$t_{\text{w}}$, (1) the probability of double-frame transmissions increases,
while the probability of collision (i.e., the probability that the number of
transmitted RTSs is more than two) increases as well; and (2) the performance
of the proposed MPR-aware MAC scheme improves significantly compared to that
of the IEEE 802.11 standard one.

Zhou et al. in [63] propose a two-round channel contention mechanism, which
divides the MAC procedure into two parts. The two parts, namely, the random
access and the data transmission, are illustrated in Figure 9. The random
access finishes as soon as the AP receives $M_{\text{random}}$ (the maximum
number of STAs that can transmit simultaneously) successful RTSs, and then the
data transmission starts. In the random access part, the AP delivers two types
of CTSs: Pending CTS (PCTS) and Final CTS (FCTS). The former responds to RTS
and the latter notifies all STAs about the start of data transmissions. Those
STAs, who have sent RTSs within a predefined time threshold
($T_{\text{timeout}}$), will transmit simultaneously. If the number of
contending users is less than $M_{\text{random}}$, the $T_{\text{timeout}}$
will trigger data transmissions as well. The AP obtains the CSI from RTSs, and
utilizes the MMSE detector to separate STAs’ signals. Data frames are assumed
to be of fixed length. Both simulation and analytic results show that the two-
round contention scheme outperforms the IEEE 802.11 single-round one in terms
of throughput and delay.

(a) Without timeout

(b) With timeout

Figure 9: Two-round MAC procedures, $M_{\text{random}}=3$

A similar work with two contention rounds is presented in [64]. Compared to
[63], [64] devises a shorter second contention round, where a single message
is used to reply all successfully received RTSs. In addition, a special focus
is placed on $2$-nd round Contention Window ($CW_{\text{2nd}}$), a parameter
making the length of the second contention round elastic. By evaluating the
proposal in simulations, a set of optimal $CW_{\text{2nd}}$ values that can
obtain the highest system performance are identified.

Zhang in [65] further extends two contention rounds to multiple rounds, which
give STAs more opportunities to compete for the channel using a threshold
derived from an optimal stopping algorithm [66]. Meanwhile, an auto fall-back
to single-round scheme is also proposed in case the traffic is low and the
single-round scheme can provide higher throughput. Frame arrivals are assumed
to follow the Poisson distribution. Results obtained from simulations and the
analytical model show the multi-round contention can increase the channel
utilization rate in a small to moderate network.

Jung et al. in [67] present a coordinated uplink MPR scheme, which extends the
work in [32] to allow both synchronous and asynchronous transmissions by
employing an additional feedback channel. The proposed MAC procedure is shown
in Figure 10. On receiving an RTS from STA$2$, the AP replies with a CTS that
includes the MPR vacancy (the remaining space for parallel uplink
transmissions). STAs who overhear the MPR vacancy will compete for the channel
to transmit along with STA$2$. Once a STA finishes transmitting ahead of the
other one, the AP immediately sends an ACK with the updated MPR vacancy
information through the additional channel to allow other STAs to compete for
the newly available MPR space. The authors assume an orthogonal training
sequence is included in the preamble of each frame for estimating the channel.
Based on results obtained from the Markov chain analytic model and
simulations, the authors claim that the proposed scheme achieves higher
channel efficiency in scenarios where the frame size and transmission rates
are dynamically varying.

Figure 10: Asynchronous data transmissions with one MPR vacancy

Table V summarizes the main characteristics of the surveyed coordinated uplink
MU-MIMO MAC protocols.

TABLE V:  Coordinated Uplink MU-MIMO MAC Protocols

Remarks Evaluation Tool CSI Scheme MUD Key Assumption Scheduling Huang [42],
SNR based MPR, 2008 Simulation + Analysis Downlink estimation CDMA Fixed data
length Optimal SNR Tandai [43], TDMA signalling, 2009 Simulation Implicit
feedback MMSE Unique subcarrier Best CSI Li [61], subcarrier contention, 2014
Simulation + Testbed Implicit feedback - Error-free channel Subcarrier Zheng
[33], DCF based MPR, 2006 Analysis Implicit feedback Blind detection Fixed
data length - Barghi [62], MPR-aware MAC, 2011 Simulation + Analysis - STC
Perfect channel - Zhou [63], two-round contentions, 2010 Simulation + Analysis
Implicit feedback MMSE Fixed data length - Liao [64], elastic $2$-nd round,
2012 Simulation Implicit feedback - Error-free channel - Zhang [65], multi-
round contentions, 2010 Simulation + Analysis - - Poisson arrivals - Jung
[67], asynchronous MPR, 2012 Simulation + Analysis Implicit feedback - Extra
ACK channel -

####  IV-A3 Discussions on Uplink MU-MIMO MAC Proposals

Here, we conclude this subsection by providing highlights, open aspects and
next steps after reviewing the uplink MU-MIMO MAC proposals in the literature.

##### Highlights

  * •

In the un-coordinated category, by simply considering the number of summarized
papers, the asynchronous access has got more attention than the synchronous
one. This is because, in the synchronous case, we can only benefit from the
simultaneous multi-frame transmissions when several STAs end their backoff at
the same time. One point that seems not fully solved by asynchronous solutions
is how reliable the distributed counter of concurrent transmissions at each
node is, as which may negatively affect the network performance by causing
collisions. In addition, it is unclear how such carrier sense should be
implemented, as the nodes need to identify the exact number of on-going
transmissions.

  * •

In the coordinated category, the AP may schedule (scheduled) or not schedule
(unscheduled) what STAs to transmit. It is surprising to see that there are
more unscheduled proposals. The reason could be (1) the difficulty and
overheads behind the uplink scheduling, and (2) simply keeping the
”decentralized” access philosophy for WLANs.

##### Open aspects

  * •

Comparison between different proposals is still difficult because of the
different considered scenarios (e.g., channel models, CSI assumptions and STAs
placement). Therefore, an open challenge is to present a comparative analysis
framework to benchmark the most relevant and promising proposals.

  * •

Most of the uplink proposals assume implicit CSI. However, calibration
problems, due to the presence of heterogeneous devices and channel conditions,
make the implicit CSI difficult to be implemented.

  * •

It is likely that, in the next generation 802.11 standard, an extended RTS/CTS
exchange will be used to signal and protect MU-MIMO frames, which would mean
the AP-coordinated approach will be adopted. Solutions to further reduce the
handshaking overheads must be considered.

##### Next steps

  * •

The IEEE 802.11ax study group is discussing to include uplink MU-MIMO
[68][69]. At the current stage, it is not clear yet how such mechanism will be
implemented. In our perspective, uplink MU-MIMO would follow a coordinated and
scheduled approach controlled by the AP. This judgement is made based on the
following two reasons. First, the AP is playing a central role in collecting
CSI from all STAs for downlink MU-MIMO transmissions in 802.11ac. We believe
this explicit CSI feedback mechanism will be kept in 802.11ax for the backward
compatibility. Additionally, by playing a central role, the AP can ask for
buffer and other information from STAs, enabling it to make the best
scheduling decision in the dense scenario.

  * •

Regarding the CSI of the uplink, in our opinion, 802.11ax could extend and
reuse the explicit CSI scheme periodically conducted by 802.11ac for the
downlink MU-MIMO transmissions. For example, the AP can estimate the uplink
channel coefficients from the same packets that carry the downlink channel
coefficients.

  * •

802.11ax should place STAs in virtual groups, and poll the STAs in each group
based on the CSI information as well as the estimation of the buffer occupancy
of the STAs to reduce overheads.

###  IV-B MAC Proposals for The Downlink

A commonly used MAC procedure for MU-MIMO downlink transmissions is
illustrated in Figure 11. The AP firstly sends out a modified RTS containing a
group of targeted STAs. On receiving the RTS, those listed STAs estimate the
channel, integrate the CSI into the extended CTS and send it back. As soon as
the AP receives all successful CTSs, it precodes the outgoing frames based on
the feedback CSI.

Figure 11: A successful downlink MU-MIMO transmission

####  IV-B1 Downlink MU-MIMO MAC Proposals

Cai et al. in [38] propose a distributed MU-MIMO MAC protocol with extended
RTS/CTS frames. The CSI is obtained from the RTS/CTS exchange. An additive
white Gaussian noise (AWGN) channel is assumed, and a leakage-based precoding
scheme is utilized to cancel interference. The authors adopt a queue based
scheduling scheme, which prioritizes frames with the longer waiting time in
the AP buffer. The results derived from the queue-based unsaturated model [70]
and simulations show the proposed multi-user MAC substantially outperforms the
single-user one.

Kartsakli et al. in [44] propose four multi-user scheduling schemes for
concurrent frame transmissions, namely, MU-Basic, MU-Deterministic, MU-
Threshold Selective, and MU-Probability. The opportunistic beamforming that
selects STAs with the highest signal-to-interference-plus-noise ratio (SINR)
for each randomly generated beam is utilized. The CSI is fedback by STAs
during the channel contention phase. A block fading channel is assumed, which
means the channel remains constant during a frame transmission time. Based on
simulation results, the authors argue that the proposed schemes achieve
notable gains against the single-user case, although there is still
considerable space for improvements compared to the theoretical capacity.

Gong et al. in [39] propose a modified CSMA/CA protocol with three different
ACK-replying mechanisms, namely, the polled ACK response, the scheduled ACK
response and the failed ACK recovery. A weighted queueing mechanism that
associates ACs with the value of contention window is also proposed to address
the fairness concern. The MMSE precoding scheme is adopted and the CSI is
assumed to be known. The simulation results show that the proposed protocol
provides a considerable performance improvement against the IEEE 802.11n
beamforming based approach when the SNR is high.

Zhang et al. in [40] present a One-Sender-Multiple-Receiver (OSMR)
transmission scheme for WLANs. The authors firstly implement an OSMR prototype
using Universal Software Radio Peripheral (USRP) [71] to explore the
feasibility of OSMR at the PHY level. Then, based on the study of the OSMR PHY
characteristics, they modify the RTS/CTS frames to support the channel
estimation. Simulations of the proposed extension are conducted at the MAC
level. A greedy scheduling algorithm is used to transmit as many frames as
possible in a TXOP with the urgent frames being prioritized over the normal
ones. The ZF precoding scheme is adopted, while a flat fading channel is
assumed. The simulation results show that a significant performance gain is
achieved by employing OSMR transmissions.

Liao et al. in [34] present a MAC protocol for downlink MU-MIMO transmissions,
where frames are scheduled to each STA by FIFO. The CSI is obtained through
estimating the training sequence included in the CTS preamble. The channel is
assumed to be error-free and independently fade from frame to frame, which
creates independent channels from the AP to STAs. Simulation results show that
a significant throughput gain is obtained by exploiting the spatial domain of
the channel.

Bellalta et al. in [35] explore the performance of downlink MU-MIMO with the
packet aggregation, and look into the interplay between the buffer size and
the number of antennas at the AP. The impact of these two parameters on the
system throughput and packet delay is also investigated. The proposed
scheduler tries to maximize the number of transmitted packets in each stream,
and also balance the duration of all streams. RTS/CTS control frames are
modified for the CSI estimation, and ZF is used to null the interference. The
analytical model is based on the work presented in [72], assuming packets’
Poisson arrival in a non-saturated network. Both simulation and analytical
results show the performance of the proposed system is close to optimal.

Redieteab et al. in [73] investigate three different transmission schemes in a
PHY and MAC cross-layer platform, which are SU-MIMO, MU-MIMO with multi-user
interference and MU-MIMO without multi-user interference. An IEEE 802.11ac
channel model [74] is utilized to emulate channel variations. The MAC layer is
made to be compliant with the 802.11ac specification draft, and the amendment
defined ECFB protocol is assumed to be employed to obtain the CSI. The ZF
channel-inversion precoding scheme is used to decode frames. Based on the
simulation results, the authors conclude that multi-user interference has
important effects on MU-MIMO transmissions, e.g., it results in less
throughput. Therefore, an automatic switching algorithm between SU-MIMO and
MU-MIMO is suggested by the authors.

Cha et al. in [75] compare the performance of downlink MU-MIMO to Space Time
Block Coding. The ZF precoder is utilized, and the CSI is obtained at the AP
by receivers’ feedback. A Rayeigh fading and error-free channel is assumed.
The results show that the downlink MU-MIMO scheme produces a higher throughput
than the STBC one if transmitted frames are of similar length, while the
results reverse in a fast-varying channel due to the high overheads of the CSI
feedback .

Balan et al. in [76] implement a distributed MU-MIMO system that consists of
several multi-antenna APs, which are connected and assumed to be synchronous
by a coordinating server. The authors employ Zero Forcing Beamforming (ZFBF)
for the frame separation. The CSI is acquired from uplink pilot symbols. Blind
Interference Alignment (BIA) is used when the CSI is unavailable. The system
is evaluated in the Wireless Open-Access Research Platform (WARP) platform
[77]. The experimental results show that the presented MU-MIMO system can
achieve high data rates and approach the theoretical maximum throughput.

Zhu et al. in [78] investigate the required modifications for TXOP to support
multi-user transmissions. The proposed scheme, called multi-user TXOP (MU-
TXOP), enables a STA whose AC won the TXOP to share the transmission period
with MPDUs of other ACs. The authors assume all STAs can be grouped for multi-
user downlink transmissions. Simulation results show that the proposed scheme
not only obtains a higher throughput, but is also more fair compared to the
conventional one.

Ji et al. in [79] present a cooperative transmission scheme that addresses the
redundant Network Allocation Vector (NAV) setting and the outdated SINR
problems. The redundant NAV setting usually occurs at STAs located in the
overlapped areas of neighboring WLANs, while the outdated SINR problem is
caused due to the delay between the channel estimation and the data
transmission. The authors utilize reserved bits in control frames to announce
the last frame in a transmission to synchronize the NAV setting, and employ
STAs’ ACKs to re-estimate and correct the SINR. The analysis model assumes
frames that arrive to STAs to follow the Poisson process. The results obtained
from the model and simulations show the enhanced scheme can achieve noticeable
performance gains compared to the sampled one.

Table VI summarizes the main characteristics of the surveyed downlink MU-MIMO
MAC protocols.

TABLE VI:  Downlink MU-MIMO MAC Protocols

Remarks Evaluation Tool CSI Scheme MUIC Key Assumption Scheduling Cai [38],
reduce AP-bottleneck effect, 2008 Simulation + Analysis Explicit feedback
Leakage coding AWGN channel Priority queue Kartsakli [44], $4$ scheduling
schemes, 2009 Simulation Explicit feedback Beamforming Block fading Highest
SINR Gong [39], ACK-replying schemes, 2010 Simulation - MMSE Assume CSI known
Weighted queue Zhang [40], OSMR, 2010 Simulation + Testbed Explicit feedback
Zero Forcing Flat fading Greedy Liao [34], throughput and delay gain, 2011
Simulation Implicit feedback - Error-free channel Per-STA FIFO Bellalta [35],
packet aggregation, 2012 Simulation + Analysis Explicit feedback Zero Forcing
Poisson arrival Per-STA FIFO Redieteab [73], PHY+MAC platform, 2012 Simulation
Explicit feedback Zero Forcing - - Cha [75], STBC & MU-MIMO, 2012 Analysis
Explicit feedback Zero Forcing Error-free channel - Balan [76], multi-AP
system, 2012 Simulation + Testbed Implicit feedback ZFBF, BIA Phase
synchronous - Zhu [78], multi-user TXOP, 2012 Simulation - - All STAs
groupable - Ji [79], outdated NAV and SINR, 2014 Simulation + Analysis
Explicit feedback - Poisson arrival -

####  IV-B2 Discussions on Downlink MU-MIMO MAC Proposals

##### Highlights

  * •

Regarding the CSI acquisition, some assume the channel reciprocity [34][76],
which allows the AP to obtain the CSI directly from frames transmitted by the
STAs, while most papers adopt the explicit way, though none of them follow the
approach defined in IEEE 802.11ac. However, it is worth to point out that no
papers discuss or justify whether a SIFS interval is long enough for STAs to
process received preambles and estimate the channel.

  * •

In terms of the MUIC scheme, the Zero Forcing approach is the most common one
due to its simplicity and efficiency.

##### Open aspects

  * •

Performance comparisons of different solutions, including the approach
considered by IEEE 802.11ac, are still missing. It is of special interest to
compare if it is better to obtain the CSI for each specific transmission,
which guarantees the CSI is fresh, or only periodically, at the risk that the
CSI may be outdated, hence creating higher interference between the different
spatial streams. First works on this direction can be found in [80][81],
though more efforts are still required.

  * •

In addition, analytical models on understanding the interactions between the
CSI state, the number of active users, the buffer size, and other specific
mechanisms such as packet aggregation, need more exploration. A first work is
presented in [35], where the authors evaluate the impact of the finite buffer
size with random arrivals at the AP in a donwlink MU-MIMO system.

##### Next steps

Since the IEEE 802.11ac amendment has already been standardized, research on
downlink MU-MIMO should focus on how the 802.11ac approach can be extended or
optimized towards the next amendment-IEEE 802.11ax. Next steps could emphasize
on tuning the downlink MU-MIMO mechanisms of 802.11ac, such as the CSI
acquisition process (e.g., the rate of requests and the set of sampled nodes),
scheduling algorithms considering both the instantaneous traffic and QoS
requirements, and the integration with other IEEE 802.11 mechanisms (e.g.,
multi-cast video communications, as defined by IEEE 802.11aa [82].

###  IV-C MAC Proposals for Integrated Up/down-link

Only a few works have considered both MU-MIMO uplink and downlink
transmissions in a single MAC protocol.

####  IV-C1 Integrated Up/down-link MU-MIMO MAC Proposals

Kim et al. in [83] devise a down/up-link back-to-back transmission scheme to
synchronize STAs. The scheme is called Per-flow MAC (PF-MAC, Figure 12), where
RIFS stands for Reduced Inter Frame Space. The AP first sends a Group-RTS
(GRTS) that includes a list of STA addresses to initiate the downlink
transmission. As soon as the AP received expected CTSs, it sends data frames
to the listed STAs. The STAs who received frames then send back ACKs
sequentially. Through the downlink transmission and a Ready to Receive (RTR)
frame from the AP, STAs are synchronized for the parallel uplink transmission.
The CSI is estimated from uplink frames. The limitation of the proposal is
that the uplink transmission can only be started by the downlink one, which
may not be desirable in some scenarios where the uplink access is urgent. Note
that the proposal is just a conceptual model without any simulation or
analytic results.

Figure 12: PF-MAC: Per-flow MAC

Zhao et al. in [45] propose an opportunistic MU-MIMO MAC protocol for Multi-
channel Multi-radio WLANs. In the downlink, a Group RTS is used to signal the
selected STAs, which reply sequentially with a CTS before the AP transmits to
them simultaneously. In the uplink, after the RTS/CTS exchange, the STAs are
signalled to start transmissions using a Group CTS message. Note that both
uplink and downlink transmissions can be done simultaneously as they use
different channels. A common control channel is used to exchange information
about the packet status and the set of available channels for next
transmissions. The CSI is assumed available at the AP. The results show the
proposal is able to outperform other multi-channel MAC schemes.

Li et al. in [46] propose a Multi-user MAC (MU-MAC) protocol, which supports
Multi-Packet Transmission (MPT) in the downlink and multiple control packets
(e.g., CTSs or ACKs) reception in the uplink. OFDM preambles are utilized to
facilitate the CSI extraction from the simultaneously received control frames.
The frame errors are assumed to come from collisions only, and all frames are
transmitted with the same rate. The scheduling scheme jointly considers the
CSI history, the AP’s queueing state and the frames’ application categories.
The analytic model is based on and extended from [38]. By observing the
results, the authors claim that MU-MAC outperforms MPT-only MAC in terms of
the maximum number of supported STAs, and this gain will further increase as
the AP employs more transmitting antennas.

Shen et al. in [41] present a High Throughput MIMO (HT-MIMO) MAC protocol that
utilizes frequency signatures to differentiate simultaneously received control
frames. HT-MIMO works in the PCF mode, hence both uplink and downlink
transmissions can only be initiated by the AP. The CSI is obtained by a
channel measurement method. The uplink and downlink channels are assumed to be
symmetrical. A greedy scheduling algorithm is adopted with the consideration
of fairness and the queue occupancy. By comparing with Cai’s proposal [38],
the analysis results show that the HT-MIMO MAC outperforms the 802.11n SU-MIMO
and Cai’s MU-MIMO schemes.

Liao et al. in [36] propose a unified MU-MIMO MAC protocol (Uni-MUMAC) for
IEEE 802.11ac WLANs by integrating both uplink and downlink enhancements. An
analytic model is developed based on [51]. The implicit CSI acquisition scheme
is adopted by assuming the channel reciprocity. Through adaptively tuning
$CW_{\text{2nd}}$ (a parameter controls the $2$nd uplink contention), and
comparing with Li’s proposal [46], the authors conclude that (1) Uni-MUMAC
performs well in both the traditional downlink-dominant and the emerging
down/up-link balanced traffic scenarios; (2) one-side enhancement (e.g., the
uplink enhancement) does not bring the same benefits to the other side.

Yun et al. in [37] present a multi-point to multi-point MIMO system, where the
uplink multiplexing is implemented in the SORA platform, while the downlink is
implemented in the USRP platform. Multiple APs are coordinated by a
controller, and connected via an Ethernet cable. A leader concept is adopted
for both the uplink and downlink medium access. A trigger frame that includes
co-senders’ addresses is sent out by the leader who first won the channel
contention. Then, the co-senders transmit preambles sequentially as specified
in the trigger frame for the CSI estimation. The downlink scheduling is based
on the packet arrival time and the length of waiting time in the queue, while
the co-senders’ selection in the uplink is randomly made. ZF is employed in
both the uplink and downlink for frames’ de/pre-coding.

Table VII summarizes the main characteristics of the Up/down-link MU-MIMO MAC
protocols.

TABLE VII:  Integrated Up/down-link MU-MIMO MAC Protocols

Remarks Evaluation Tool CSI Scheme MUD & MUIC Key Assumption Scheduling Kim
[83], back-to-back transmissions, 2008 Conceptual model Implicit feedback - -
- Zhao [45], multi-radio WLANs, 2009 Simulation - - CSI known Opportunistic Li
[46], MU-MAC, 2010 Simulation + Analysis Explicit feedback - Error-free
channel History CSI Shen [41], control frames’ encoding, 2012 Analysis - -
Symmetrical channel Greedy Liao [36], unified up/downlink MAC, 2013 Simulation
+ Analysis Implicit feedback - Channel reciprocity FIFO Yun [37], multi-APs to
multi-STAs, 2013 Testbed Sequential preambles Zero Forcing - FIFO

####  IV-C2 Discussions on Integrated Up/down-link MAC

  * •

The comments detailed in previous subsections are also valid here. Regarding
integrated up/down-link MU-MIMO MAC protocols, we would like to remark that
there are still too few works to allow us to categorize them. A first simple
classification can be made based on if the AP governs both downlink and uplink
communication [41][46][83], or the random access is still considered to
initiate transmissions from STAs [36][37].

  * •

Following the IEEE amendment evolution towards 802.11ac, we believe the AP
will also play a coordinating role in scheduling uplink MU-MIMO transmissions.

  * •

However, there is another major issue that requires further research, which is
the need for a joint design of up/down-link MU-MIMO MAC protocols, rather than
just simply combining solutions designed independently. The reason is that
one-side enhancement could negatively affect the other side. For instance, as
pointed out in [36], the optimal parameter for uplink MU-MIMO transmissions
does not bring the same benefit to the downlink.

##  V Future Directions

The goal of all the surveyed MAC proposals is to improve MAC efficiency in
essence. More specifically, they try to convert the raw data rate brought by
the PHY advance (i.e., MU-MIMO) to the MAC throughput as efficiently as
possible.

With this goal in mind, we discuss possible future research directions for MU-
MIMO MAC protocols through a micro perspective and a macro perspective,
respectively. In the former, we discuss some important performance-affecting
aspects that have not been specified in IEEE 802.11ac; we also identify key
factors that make the conversion from the PHY data rate to the MAC throughput
inefficient, and then give our thoughts on possible ways to improve the MAC
efficiency. In the latter, we envisage the MAC’s role in facilitating the
integration of the future heterogeneous networks.

###  V-A The Micro Perspective: Within MU-MIMO Based WLANs

####  V-A1 What Does 802.11ac Not Specify?

The downlink MU-MIMO transmission is one of the most significant features
introduced by IEEE 802.11ac. In order to perform multi-user transmissions, the
amendment proposes the ECFB scheme to feedback the required CSI, and devises a
group identifier (Group-ID) field in the PHY preamble to facilitate grouping
STAs. However, the following two important factors are not specified in the
amendment.

  * •

Scope and frequency of CSI feedback: [80] and [81] have shown the significant
impact of the CSI feedback on the system performance. A clear dilemma
regarding the scope and the frequency of the CSI feedback is that a large
scale (e.g., all STAs in the network) or frequent CSI requests will introduce
huge overheads, while the opposite way leads to that the rendered channel
information might be outdated. Therefore, adaptive algorithms are needed to
dynamically adjust the scope and the frequency of CSI feedback.

  * •

Conditions to group/re-group STAs: Although it can be argued that the way of
grouping STAs depends on the specific application, a smart grouping algorithm
has to be designed to identify those STAs that can be co-scheduled, or on what
conditions STAs’ re-grouping would be triggered.

####  V-A2 How to Improve MAC Efficiency?

As shown in the paper, significant research efforts have been made to adapt
IEEE 802.11 MAC to advances such as the multi-antenna technique. However, the
MAC throughput is still much lower than the PHY raw rate (lower than $70\%$ in
most cases [84]). The throughput loss mainly comes from the so-called
overheads, which include the management frames (e.g., association
requests/responses), the compulsory idle duration (e.g., the random BO,
DIFS/SIFS), control frames (e.g., RTS/CTS/ACK) and frame headers (e.g., PHY
preambles, PHY/MAC headers). Other non-overhead factors contributing to the
throughput loss include frame collisions and the airtime unfairness caused by
low rate STAs that monopolize the channel. These fundamental IEEE 802.11
mechanisms and features limit the MAC efficiency. In a packet capture test
conducted in a dense area of Tokyo [85], the results show that data frames
only account for $23\%$ of all types of frames ($46\%$ management frames,
$30\%$ control frames, $1\%$ others); moreover, most of management frames are
in the 802.11b format and transmitted at $1$ Mbps to ensure the
interoperability.

The newly created High Efficiency WLAN study group-802.11ax is still at its
early stage. Here, we give our thoughts on possible solutions to improve the
MAC efficiency.

  * •

Cooperation among multiple bands: Management frames, control frames and frames
headers are necessary to facilitate correct receptions of data. They can not
be eliminated in the current 802.11 communication architecture. At least the
evolution from IEEE 802.11-1997 to 802.11ac, what we have seen is an ever-
increasing length of PHY preamble. Cooperation among multiple bands could be
an effective way to control overheads. Specifically, a future smart device is
likely to be equipped with multiple interfaces operating in multiple bands
[86]. Thus, 802.11ac at $5$ GHz, could be a candidate for the carrier sense
and data transmissions across rooms; 802.11ah below $1$ GHz, could be utilized
to transmit management and control frames; while 802.11ad at $60$ GHz, could
be used for very high speed data transmissions in the line of sight. [87] has
suggested a possible usage model using 802.11ah for signalling among APs,
while 802.11ac for data frames.

  * •

Revision of the backoff scheme: The random BO scheme is a key function
employed by IEEE 802.11 to avoid collisions. Unfortunately, collisions can not
be eliminated and remain as one of the most degrading factors to the system
performance. [88] proposes a collision-free solution, where STAs adopt a
deterministic BO instead of a random one after successful transmissions for
single-antenna based WLANs. On the other side, works in [61] and [89] suggest
to shift the random BO countdown from the time domain to the frequency one by
treating OFDM subcarriers as integers. These innovative ideas can be
considered to support multi-antenna based WLANs in both downlink and uplink.

  * •

Uplink MU-MIMO transmissions: The Internet traffic has evolved from web
browsing and file transfers to a wide variety of applications, which include
considerable amount of content-rich files generated by users, such as the
video conferencing, social networks and cloud uploading services. Although the
enhancement for uplink transmissions has recently gained attention, there is
still much space for improvements since the latest amendment-IEEE 802.11ac
does not support uplink MU-MIMO transmissions. In addition, there are only a
few works that unify MU-MIMO downlink and uplink protocols into a single
communication system.

  * •

Orthogonal FDMA: OFDMA is currently under consideration for next-generation
WLANs to improve the system efficiency [15]. The interest on OFDMA is
originated from the efficiency loss caused by the 802.11ac channel bonding (up
to $160$ MHz). Transmitting over wider channels reduces the transmission
duration, though it also magnifies the negative impact of the overheads, since
the duration of inter-frame spaces and control packets are constant regardless
of the channel width. OFDMA enables WLANs to multiplex transmissions from/to
different STAs over a single channel by assigning a different OFDM subcarrier
to each transmission. The result is that, transmissions last longer, as they
are transmitted at lower rates, but the efficiency of the system is improved,
as more data are transmitted in parallel. Regarding MU-MIMO transmissions,
using OFDMA would have a positive impact on overheads, since STAs only need to
feedback a lower amount of CSI, which is only proportional to the subcarriers
of the used subchannel.

  * •

Full-duplex transmissions: The current form of communications in WLANs is
half-duplex, namely, transmissions and receptions are allocated to different
time slots or frequency bands. The full-duplex transmission has the potential
to double the channel capacity by allowing simultaneous transmissions and
receptions with the same frequency [90][91]. In addition, the coming of full-
duplex transmissions hints us to rethink the IEEE 802.11 fundamental MAC
mechanism-CSMA/CA, which is employed based on the long-held assumptions that
(1) wireless devices can not transmit and receive at the same time, and (2)
wireless devices can not detect collisions while transmitting [92]. The
research on full-duplex transmissions has just started in recent years.
Although the challenging part is to cancel self-interference at the full-
duplex transceiver, the MAC scheme needs to be revised as well [93][94].

  * •

Massive MIMO transmissions: Having MU-MIMO already been integrated in the
latest standards (e.g., IEEE 802.11ac and 4G LTE), and in order to further
reap the benefits of MIMO in a much greater scale, Massive MIMO, with orders
of magnitude more antennas equipped at the transmitter, has recently attracted
much research attention. Massive MIMO has the promise to increase the spectral
efficiency to tens of hundreds of bps/Hz, and simultaneously improve the
energy efficiency [95][96], which enables it to be a very good technology
candidate for next-generation wireless standards that target highly-dense user
scenarios. The first challenge of employing Massive MIMO is the limited space
at the AP, since antennas are required to be placed at the least half
wavelength apart. The second challenge is the overhead. IEEE 802.11ac uses
ECFB-the explicit way to feedback CSI. The channel sounding time and the CSI
volume are proportional to the number of AP’s antennas, which would occupy
considerable amount of time and bandwidth, especially in the Massive MIMO
case. The first challenge is out of the scope of the paper, while the second
one needs more research efforts on the precoding, the antenna selection, and
exploring the antenna correlation to reduce the channel sounding time and the
CSI volume.

###  V-B The Macro Perspective: Integration with Heterogeneous Networks

It seems to be a trend that in the future there will be a huge and smart
network that integrates heterogeneous networks (e.g., WLANs, broadband mobile
networks and sensor networks), which means individual network will have to
collaborate with others to provide services, rather than just coexist.
Obviously, the integration or the inclusion of WLANs require unique changes at
the MAC layer.

####  V-B1 How, who and when to collaborate?

With the PHY layer’s focus on the air interface and the network layer’s focus
on the routing, the MAC layer plays a role in deciding how to collaborate, who
to collaborate and when to collaborate [97][98]. For example, imagining a
scenario that a sink of a smart metering sensor network requests an AP to
forward the collected data to a user’s mobile phone, the AP first checks
whether the mobile phone is in its vicinity to decide whether to forward the
data by itself or to relay the data to other APs. And then, the AP checks the
channel condition and the queueing status to decide who and when to transmit
the data. Regardless the scale and the type of collaborations, exchanging
management frames and control frames are needed to build connections with
other entities. Note that today’s device-to-device communications already
account for a significant part of total wireless traffic, and they are
regarded as one of the most important challenges for $5$G networks [99][100].
Therefore, the MAC scheme for the integrated network has to take how, who and
when to collaborate into account.

####  V-B2 Multi-hop Cooperative MAC

In addition to the above consideration, it is inevitable for MAC protocols of
integrated networks to support multi-hop indirected links. A typical
cooperative scenario is that a receiver at the edge of the transmitter’s range
can benefit from its neighbours’ relaying. This opens research questions as
follows. First, the selection of optimal relay: (1) who will make the
selection, the source or the destination? (2) what is the criteria to choose
the optimal relay, signal strength, energy level or security issues? (3)
whether the chosen one will agree or be able to relay? Secondly, the timing of
relay: (1) immediately after the source transmission, or (2) compete for the
channel and then relay. Thirdly, the format of relay: (1) amplify-relay,
decode-relay or compress-relay, and (2) single relay or multiple relays [101].
Other issues, such as the hidden-node problem, cooperative diversity, MPT/MPR
functionalities and the joint MAC-routing design, also need to be considered
[102][103].

####  V-B3 Outdoor and mobile WLANs

The inclusion of WLANs to outdoors presents some significant challenges to the
traditional MAC, as which is designed to support limited mobility. First, due
to the user movement and the large scale fading, the outdoor channel is
varying faster than that of indoors, even with the same moving speed [104].
For that reason, the CSI feedback scheme needs to be reconsidered to report
the channel state timely, while maintaining low channel estimation overheads.
Secondly, the cellular operators may offload traffic to public or proprietary
WLANs (e.g., the carrier class Wi-Fi [105]) in a dense public stadium, in
which case, the seamless transfer and the QoS promised by the cellular network
need to be assured at the MAC layer.

##  VI Concluding Remarks

The uplink and downlink MU-MIMO MAC protocols for WLANs are investigated and
categorized in the paper. Some typical MUD and MUIC techniques for de/pre-
coding are sampled, and the requirements for designing MU-MIMO MAC protocols
are identified. Based on the study, discussions are carried out to clarify
what challenges and future directions could be for designing effective MU-MIMO
MAC protocols.

Despite considerable research has been conducted, there still exists under-
explored areas toward simple, yet highly efficient MAC protocols for MU-MIMO
based WLANs, especially in the context of the rapid growth of wireless
devices. Therefore, we have given some of our thoughts in that regard. We hope
this survey paper would help the readers to summarize the current research
progress and inspire their future work.

## Acknowledgment

This work has been supported by the Spanish Government and the Catalan
Government under projects TEC2012-32354 (Plan Nacional I+D) and SGR2009#00617.

The authors are also grateful for the useful technical discussions with Xu
Zhang and Shan Zhang at NiuLab of Tsinghua University.

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