Abstract
The performance improvement in IEEE 802.11 WLANs in widely fluctuating network loads is a challenging task. To improve the performance in this saturated state, we develop an adaptive backoff algorithm that maximizes the system throughput, reduces the collision probability, and maintains a high fairness for the IEEE 802.11 DCF under dense network conditions. In this paper, we present two main advantages of the proposed ABA-CW algorithm. First, it estimates the number of active stations and then calculates an optimal contention window based on the active station number. Each station calculates the channel state probabilities by observing the channel for the total backoff period. Based on these channel states probabilities, each station can estimate the number of active stations in the network, after which it calculates the optimal CW utilizing the estimated active number of stations. To evaluate the proposed mechanism, we derive an analytical model to determine the network performance. From our results, the proposed ABA-CW mechanism achieved better system performance compared to fixed-CW (BEB, EIED, LILD, and SETL) and adaptive-CW (AMOCW, Idle Sense) mechanisms. The simulation results confirmed the outstanding performance of the proposed mechanism in that it led to a lower collision probability, higher throughput, and high fairness.
Highlights
Wireless local area networks (WLANs) are becoming the most popular and widely deployed networks worldwide
If the status is busy during the interval, the station defers its access to the channel for a backoff period, which is determined by Tbo = rand(CW) × Tslot, where Tbo and Tslot denote the time for the backoff period and slot time, respectively
We aim to develop a new adaptive and robust backoff algorithm that improves the performance in terms of maximizing the system throughput, reducing the collision probability, and ensuring good fairness for the distributed coordination function (DCF) in an IEEE 802.11 WLAN under dense network conditions
Summary
Wireless local area networks (WLANs) are becoming the most popular and widely deployed networks worldwide. We aim to develop a new adaptive and robust backoff algorithm that improves the performance in terms of maximizing the system throughput, reducing the collision probability, and ensuring good fairness for the DCF in an IEEE 802.11 WLAN under dense network conditions. We present two main contributions of the proposed adaptive backoff algorithm for the contention window, named ABA-CW It estimates the number of active stations and calculates an optimal CW based on the number of active stations. For the estimated number of active stations, the proposed scheme achieved an optimal CW value that gives a good network performance in terms of high throughput, low collision probability, better channel utilization, and good fairness as the number of stations on the network varies.
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