Probability-based Contention Window Retention Backoff with Freezing Algorithm
Yanping Yu, Qichao Cao and Chenhuan Zhu
Binary exponential backoff (BEB) is used as a main collision avoidance mechanism in IEEE 802.11 MAC protocol. In the BEB algorithm, the contention window (CW) is reduced to minimum whenever the packet is successfully transmitted and is doubled whenever a collision occurs to reduce collision probability. However, when the number of participating stations is large, the CW size is adjusted back and forth, thereby decreasing throughput whilst increasing the delay in a network dramatically. Thus, the BEB algorithm cannot be adapted to dense and heavy load networks. To solve these problems, an improved algorithm called probability-based CW retention backoff with freezing (PCWRBF) is proposed. In PCWRBF, the CW size of a station is adjusted according to a probability after a successful transmission. The value of CW is decreased to the minimum value with a certain probability r and remains at the current value with the rest of probability1-r. The freezing mechanism is also adopted to further reduce collision possibilities. Finally, the bi-dimensional Markov chain model is used in analysing the PCWRBF saturation throughput and average delay. Theoretical and simulation results show that the PCWRBF algorithm achieves high throughput and low latency without increasing complexity.
Keywords: Dense wireless local area networks with heavy load; MAC layer; Backoff; Contention window adjusting.