Efficient MAC protocols optimization for future high density WLANS

Abstract

Recently, the High Efficiency WLAN or simply HEW study group was created within IEEE 802.11 working group. This study group considers the improvement of spectrum efficiency to enhance the system's area throughput in high density scenarios. Subsequently, this led to the creation of a new task group called 802.11ax, which is expected to deliver the next Wi-Fi generation. A key perspective considered by the recent discussions is increasing the spatial reuse using Physical Carrier Sensing (PCS) adaptation. While Transmit Power Control (TPC) has always been the chosen technique when targeting spatial reuse improvements, this work investigates the weakness points in TPC especially outside centralized network architectures. On the other hand, the incentives behind adopting the PCS approach are discussed. Accordingly, a new algorithm is proposed to adapt the PCS dynamically. The performance of this proposal is compared to that of TPC using OPNET simulations. For a dense IEEE 802.11n network topology, simulation results show that PCS outperforms TPC (120% versus 66% of throughput gain respectively). Particularly, the PCS approach is more robust when there are some nodes that are not implementing the PCS nor the TPC adaptation.

A Deep Reinforcement Learning Framework for Contention-Based Spectrum Sharing

“…In response, the receiving node (e.g. a UE) sends a Clear-to-Send (CTS) frame if the received Signal-to-Interference Ratio (SINR) of the RTS frame was above a certain threshold [9]. However, RTS-CTS can inhibit potentially successful transmissions, and introduces significant additional overhead and latency [10].…”

“…Note how X j [n] also depends on the action a i [n] of all BSs i = j in (7). The probabilistic nature of the transition from s[n] to s[n + 1] is captured by the noise term n ij in (9). The function f in ( 9) is used to convey a first order Markov chain representation of a channel model, known to be sufficient for modelling very slow fading channels [30].…”

Damysus: A Practical IEEE 802.11ax BSS Color Aware Rate Control Algorithm

“…The authors in [15] introduce the K-APCS algorithm that incorporates the IEEE 802.11k radio resource management to obtain the metrics required for adjusting the carrier sensing threshold. Another approach for tuning the carrier sensing threshold suitable only for the Stations (STAs), is by recording the Received Signal Strength Indicator (RSSI) from the beacon frames transmitted from the associating AP [16]. Dynamic Sensitivity Control (DSC) [17] is the algorithm proposed for the IEEE 802.11ax STAs, where STAs tune the carrier sensing threshold.…”

SDN-Based Centralized Downlink Scheduling with Multiple APs Cooperation in WLANs

“…In [16], the authors focus on CST (Carrier Sensing reshold) adaptation while maintaining optimal data rate to achieve high aggregate throughput. Because the CST adaptation can detect Signal of Interest formed by short communication links in dense network and eventually avoid collisions; in [17], they further propose another CST adaptation scheme that eliminates hidden terminal and exposes terminal problems by considering margin value. However, these two CST adaptation schemes can result in starvation for some nodes in dense environment.…”