InterferenceAware Adaptive Beam Alignment for HyperDense IEEE 802.11ax InternetofThings Networks
Abstract
:1. Introduction
2. Related Work
3. IEEE 802.11ax Features
3.1. PPDU Frame Structure
3.2. Error Correction and Modulation
4. Proposed Opportunistic Medium Access
4.1. System Model and Assumptions
 Each STA has exactly the same performances with OFDMA and MUMIMO for mathematical performance analysis.
 In addition, antennas which are installed in each IEEE 802.11ax IoT device are fullduplex vouching simultaneous U/DL transmission.
 Detailed parameter setting of antennas for beamforming including azimuth, half power beam width (HPBW), and antenna gains are not associated with the proposed algorithm.
 U/DL MU transmissions are considered in this paper.
 In our proposed algorithm, NAV is set to 0 if the corresponding AP is idle and vice versa.
4.2. Beam Direction Selection and Beamforming Algorithm
Algorithm 1 Proposed beamforming algorithm 
Input:$H{R}_{dir}^{a}\phantom{\rule{2.84526pt}{0ex}}or$ 〈$H{R}_{dir}^{e}$, $CS{I}_{A{P}_{CS}^{e}}$〉, $\omega $, ${\theta}_{ed}$, $dir$

Algorithm 2 Joint searching for direction and CSI 
Input:$L{R}_{dir}^{a}$, $H{R}_{dir}^{a}$, $A{P}_{CS}^{a}$, $CS{I}_{A{P}_{CS}^{e}}$, $H{R}_{dir}^{e}$, ${d}_{\alpha}$, ${d}_{\beta}$ Output: Appropriate $direction$ for beamforming

4.3. Analytical Model
4.3.1. Total Elapsed Time of D/UL MU Transmission
4.3.2. Expected Lost Time, ${l}_{t}$
4.3.3. Expected Throughput Loss, ${E}_{Th}$
4.3.4. Jain’s Index $\mathcal{J}$ for Fairness
5. Performance Evaluation
5.1. Simulation Setting and Overview
5.2. Simulation Results and Discussions
6. Conclusions Remarks and Future Work
Author Contributions
Funding
Conflicts of Interest
References
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IEEE 802.11ac  IEEE 802.11ax  

Band (GHz)  5  2.4 and 5 
Channel bandwidth (MHz)  20, 40, 80, 80 + 80, 160  20, 40, 80, 80 + 80, 160 
Modulation  BPSK, QPSK, 16QAM, 64QAM, 256QAM  1024QAM is newly added 
FFT size  64, 128, 256, 512  256, 512, 1024, 2048 
Subcarrier spacing (KHz)  312.5  78.12 
Symbol duration (us)  3.2  12.8 
CP (us)  0.4 and 0.8  0.8, 1.6, and 3.2 
FEC  BCC, LDPC (optional)  LDPC 
Spatial stream (SS)  Up to 8 SS for each AP  Up to 8 SS for each AP 
Up to 4 SS for each STA  Up to 4 SS for each STA  
MUMIMO  DL MUMIMO  UL/DL MUMIMO 
Proposed  [21]  [22]  [23]  [24]  

MU transmission  ✓  ✓  ✓  ✓  ✓ 
MU access  ✓  ✓  ✓  ✓  ✓ 
MU diversity  ✓  ✓  
Simple signal exchange  ✓  ✓  ✓  ✓  
CSI measurement  ✓ 
Parameter  Description 

${N}_{A}$  Number of APs 
${N}_{S}$  Number of STAs 
${U}_{\mathrm{mu}}$  Number of MU STAs 
$\tau \left(x\right)$  Return time when $x=0$ 
NAV${}_{i}$  ith interBSS NAV 
NAV${}_{m}$  intraBSS NAV 
${L}_{c}$  Length of control frame 
${L}_{d}$  Length of data frame 
${B}_{r}$  Beamforming search rate 
${x}_{i}^{t}$  Throughput of ith STA in time t 
n  Required count to find appropriate beamformees 
${V}_{s}$  Number of SUMIMO spatial streams per STA 
${V}_{m}$  Number of MUMIMO spatial streams per STA 
$R({V}_{s},{B}_{\mathrm{ru}})$  Data rate 
${B}_{\mathrm{ru}}$  Bandwidth of RU 
${L}_{D}$  Packet size 
${P}_{a}$  Number of aggregated packets in AMPDU 
Parameter  Description 

B  160 MHz 
FFT  256 
${L}_{d}$  1460 bytes 
${P}_{a}$  256 
$C{W}_{min}$  32 
$C{W}_{max}$  1024 
SIFS  16 $\mathsf{\mu}$s 
aSlotTime  9 $\mathsf{\mu}$s 
$\rho $  16 $\mathsf{\mu}$s 
${N}_{A}$  8 
${N}_{S}$  from 8 up to 64 
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Kwon, D.; Kim, S.W.; Kim, J.; Mohaisen, A. InterferenceAware Adaptive Beam Alignment for HyperDense IEEE 802.11ax InternetofThings Networks. Sensors 2018, 18, 3364. https://doi.org/10.3390/s18103364
Kwon D, Kim SW, Kim J, Mohaisen A. InterferenceAware Adaptive Beam Alignment for HyperDense IEEE 802.11ax InternetofThings Networks. Sensors. 2018; 18(10):3364. https://doi.org/10.3390/s18103364
Chicago/Turabian StyleKwon, Dohyun, SangWook Kim, Joongheon Kim, and Aziz Mohaisen. 2018. "InterferenceAware Adaptive Beam Alignment for HyperDense IEEE 802.11ax InternetofThings Networks" Sensors 18, no. 10: 3364. https://doi.org/10.3390/s18103364