1
Enhance the Edge with Beamforming: Performance
Analysis of Beamforming-Enabled WLAN
Wen Wu
∗
, Qinghua Shen
∗
, Khalid Aldubaikhy
∗
, Nan Cheng
∗
, Ning Zhang
†
and Xuemin (Sherman) Shen
∗
∗
Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario, Canada
†
Department of Computing Sciences, Texas A&M University at Corpus Christi, TX, USA
Email: {w77wu, q2shen, kaldubai, n5cheng, sshen}@uwaterloo.ca
∗
, ning.zhang@tamucc.edu
†
Abstract—The ultra-dense edge networks with mmWave and
beamforming are envisioned as a potential solution to satisfy
the high rate and capacity requirements in 5G networks. In
IEEE 802.11 ad, which is the first beamforming-enabled WLAN
standard, all stations (STs) contend for beamforming (BF)
training opportunities in associated beamforming training (A-
BFT) slots. However, due to limited number of A-BFT slots, BF
training suffers from a severe collision issue, especially in dense
networks, which results in a low channel utilization in the A-
BFT stage. To achieve the maximum channel utilization, it is of
significance to allocate A-BFT slots efficiently. Therefore, in this
paper, we propose an analytical model to analyze IEEE 802.11
ad medium access control (MAC) protocol in BF training stage.
In particular, we analyze the successful transmission probability
and channel utilization of IEEE 802.11 ad MAC protocol in the
dense network. Based on theoretical analysis, we provide the
optimal number of A-BFT slots. In addition, theoretical analysis
indicates that the maximum channel utilization in the A-BFT
stage is barely e
−1
which is the same as that of slotted ALOHA
protocol. Simulation results are provided to validate the accuracy
of the analytical model and theoretical analysis.
I. INTRODUCTION
The foreseeable future is expected to witness the exponen-
tially increase in both wireless data traffic and computation
requirements due to emerging data-hungry and computation-
intensive applications, such as the high definition video trans-
mission, cordless virtual reality (VR) gaming, self-driving, in-
dustrial Internet of things (IoT), etc [1]. To satisfy the require-
ments of high data rate, massive connectivity and intensive
computation, in 5G networks, the mobile edge network has
been proposed, which is featured by edge computing, caching,
and network densification [2]. As one potential technology to
enhance the data rate in ultra-dense networks, millimeter wave
(mmWave) WLAN can offer a fiber-like wireless transmission
for short range communications, by exploiting multi-GHz un-
licensed bandwidth [3], [4]. The success of mmWave WLAN
has fueled IEEE 802.11 ad, which is the first ratified standard
operating in the unlicensed 60 GHz band and can provide a
data rate up to 6.75 Gbit/s [5].
To compensate high free-space path loss in the mmWave
band, beamforming (BF) is widely considered as a pivotal role
in establishing reliable communication links [6], [7]. Beam-
forming, which is a narrow beam, focuses radio frequency
(RF) power towards a narrow direction to provide a signal-to-
noise (SNR) gain. To achieve this SNR gain, the transmitter
and receiver must perform BF training to align their beams
before data transmission [8]. Without well-aligned beams, data
rate decreases significantly in mmWave systems.
As standardized in IEEE 802.11 ad, all stations (STs)
have to perform BF training with an access point (AP) in
the associated beamforming training (A-BFT) stage before
data transmission. IEEE 802.11 ad defines a contention-based
BF training protocol that all STs contend for BF training
opportunities in A-BFT slots. One A-BFT slot only provides
BF training opportunity for one ST. However, IEEE 802.11
ad can only support at most 8 A-BFT slots [5]. Hence, this
contention-based BF training protocol can suffer from high
collision probability, especially in the dense network, which
renders low channel utilization in the A-BFT stage. Intuitively,
increasing the number of A-BFT slots is one of the possible
solutions to alleviate the collision probability and improve
channel utilization. However, improper increasing A-BFT slots
can result in low utilization of A-BFT slots and increases the
overhead of BF training stage. Thus, it is crucially to study
how to efficiently allocate A-BFT slots in the dense network
is a key problem.
Performance analysis plays a vital role for improving the
efficiency of IEEE 802.11 ad. Recently, several works analyze
the medium access control (MAC) protocol in IEEE 802.11 ad
in the data transmission stage. Hemanth et al. in [9] proposed
an analytical model to analyze hybrid MAC in IEEE 802.11
ad. Considering the effect of number of sectors in directional
transmission, the performance of IEEE 802.11 ad MAC is an-
alyzed in [10]. A directional cooperative MAC protocol which
is compatible with IEEE 802.11 ad is proposed and analyzed
in [11]. However, few work analyzes the performance of IEEE
802.11 ad MAC protocol in the BF training stage, which has a
great impact on the overall performance. Due to the directional
propagation characteristics of mmWave systems, IEEE 802.11
ad defines a new MAC protocol in the BF training stage.
This MAC protocol is totally different from traditional carrier-
sense multiple access (CSMA) mechanism in current WLAN
systems. Thus, analytical model of previous WLAN systems
is not suitable for IEEE 802.11 ad and a new analytical model
is needed.
In this paper, we make following contributions:
• We propose an analytical model to analyze the perfor-
mance of IEEE 802.11 ad MAC protocol in the BF
training stage. Based on the proposed model, theoretical
analysis obtains the successful transmission probability
in the dense network. To the best of our knowledge, this
Authorized licensed use limited to: Hong Kong Baptist University. Downloaded on September 07,2024 at 13:20:39 UTC from IEEE Xplore. Restrictions apply.
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