Li Yun

A Novel Random Backoff Algorithm to Enhance the Performance of IEEE 802.11 DCF

The Probability Distribution of Slot Selection (PDoSS) of IEEE 802.11 DCF is extremely uneven, which makes the packet collision probability very high. In this paper, we propose a novel RWBO+BEB backoff algorithm for 802.11 DCF to make the PDoSS even and thus decrease the packet collision probability. A Markov model is built for analyzing RWBO+BEB’s PDoSS and saturation throughput. The model’s correctness is validated by simulation. The performance of RWBO+BEB is also evaluated by simulation in terms of PDoSS, saturation throughput, packet collision probability and packet delay. The simulation results indicate that RWBO+BEB can decrease the packet collision probability to a large extent, utilize the channel more efficiently, and make the packet delay jitter much lower comparing to 802.11 DCF. Moreover, we analyze the relation of saturation throughput and packet collision probability to walking probability (pd ) and contention windows (w), respectively. The analysis indicates that RWBO+BEB has a remarkable feature: its saturation throughput keeps high, and packet collision probability keeps very low (which under 0.1) in a large range of pd and w, this allows us to configure pd and w more flexibly.