Orthogonal Frequency Division Multiple Access resource unit allocation algorithms for IEEE 802.11AX medium access control protocol

The exponential growth of IoT devices necessitates efficient Medium Access Control (MAC) protocols for large networks with low-power devices. Orthogonal Frequency Division Multiple Access (OFDMA) allows multiple users to transmit data simultaneously over the same frequency band. IEEE 802.11ax Uplink OFDMA (UORA) enhances random channel access in Wireless Local Area Networks (WLANs), with performance heavily dependent on the OFDMA Contention Window (OCW) range and the number of contending stations (STAs). However, accurately estimating the number of contending STAs without specific signalling is challenging for Access Points (APs). Using a fixed number of Resource Units (RUs) for the OFDMA backoff (OBO) counter can lead to higher collisions and underutilization. Each STA selects a random OBO counter value from the OCW range and decreases it by the number of available RUs when transmitting a frame, with the OCW value determining the waiting time before transmission. The OBO control mechanism adjusts transmission attempts based on previous success or failure, using a self-tunable parameter, α. This research proposes three ideas to improve UORA performance. First is the Versatile Shuffle Recomputation Resource Units (VSR-RUs), which use the Fisher-Yates shuffling algorithm to optimize RU utilization and reduce collisions. The second proposed idea is the Correlated Real-Time RUs and OFDMA Backoff (CRT-RUs OBO), which utilizes real-time RUs for lower backoff and early misbehaviour detection. The final proposed idea is the Effectual Contention Window (ECW) Computation that makes CW size adaptable by applying the modulo operation to available RUs, enhancing channel access efficiency. Extensive Discrete Event Simulation (DES) has been used as a quantitative research tool to evaluate these algorithms using the following metrics: average throughput, collision probability, channel efficiency, and average channel access delay. The simulation results demonstrated that the proposed algorithms significantly outperformed the benchmark algorithms across several metrics. Specifically, VSR-RUs improved the average throughput results by 23.91%, the CRT-RUs OBO algorithm improved by 5.32%, and the ECW algorithm improved the performance by 63.47% (RU 8), 50.45% (RU 16), and 55.58% (RU 32). Regarding collision probability, the VSR-RUs algorithm again surpassed the benchmarks, yielding 5.41% and 54.47% better results for the CRT-RUs OBO algorithm, and 7.84% (RU 8), 42.31% (RU 16), and 43.49% (RU 32) for ECW algorithm. For channel efficiency, the VSR-RUs algorithm showed superior performance with improvements of 8.54% and 70.83% better results on the CRT-RUs OBO algorithm, and 84.93% (RU 8), 86.05% (RU 16), and 87.32% (RU 32) over ECW algorithm. Lastly, regarding average channel access delay, the VSR-RUs algorithm achieved better results by 8.89% and 13.09% in the first 5ms and 10.59% by the end of the simulation for the CRT-RUs OBO algorithm. For the ECW algorithm, the improvements were 62.29% (RU 8), 43.97% (RU 16), and 58.93% (RU 32). Results show that all the proposed algorithms show significant improvements, which are higher in data throughputs, maintain improved collision probabilities and channel efficiencies among the stations with lower average channel access delays, and thus produce better overall network performance.

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