Adaptive Binary Negative-Exponential Backoff Algorithm Based on Contention Window Optimization in IEEE 802.11 WLAN

Abstract

IEEE 802.11 medium access control (MAC) employs the distributed coordination function (DCF) as the fundamental medium access function. DCF operates with binary exponential backoff (BEB) in order to avoid frame collisions. However it may waste wireless resources because collisions occur when multiple stations are contending for frame transmissions. In order to solve this problem, a binary negative-exponential backoff (BNEB) algorithm has been proposed that uses the maximum contention window size whenever a collision occurs. However, when the number of contending stations is small, the performance of BNEB is degraded due to the unnecessarily long backoff time. In this paper, we propose the adaptive BNEB (A-BNEB) algorithm to maximize the throughput regardless of the number of contending stations. A-BNEB estimates the number of contending stations and uses this value to adjust the maximum contention window size. Simulation results show that A-BNEB significantly improves the performance of IEEE 802.11 DCF and can maintain a high throughput irrespective of the number of contending stations.

Adaptive Packet Scheduling Scheme to Support Real-time Traffic in WLAN Mesh Networks

“…On one hand, in order to enhance the QoS support in 802.11 WLANs, IEEE 802.11e [21] developed a new enhancement contention-based channel access mechanism called enhanced distributed channel access (EDCA) for service differentiation. And many literatures focus on modeling and analyzing the IEEE 802.11 carrier sense multiple access with collision avoidance (CSMA/CA) and EDCA protocol [22] [23], which analyzed the throughput performance of IEEE 802.11 MAC protocol. Kong et al [24] presented a three dimensional discrete time Markov chain model to describe IEEE 802.11e EDCA, which took into account the backoff timer, freeze and virtual collision policy.…”

Applying Deep Reinforcement Learning to Improve Throughput and Reduce Collision Rate in IEEE 802.11 Networks

“…Accordingly, selecting the appropriate CW size is very important. Related studies try to increase network performance by proposing several algorithms in the references [8][9][10][11][12]. Syed and Roh [8] proposed an adaptive backoff algorithm for the CW (ABA-CW), in which the number of active stations was estimated by observing the channel status.…”

“…Karaca et al [11] proposed the backoff freezing mechanism that claimed to achieve the maximum network throughput under the populated networks. Choi et al [12] proposed the adaptive binary negative-exponential backoff (A-BNEB) to adjust the maximum CW size based on the number of competing stations.…”