关键词: 认知无线Mesh网络；拥塞反馈；跨层设计；随机搜索遗传算法；最大最小公平策略

Abstract:

Due to the difference of link load caused by the variation of channel status，congestion is an important factor for system performance in cognitive radio wireless mesh network. To solve this problem, a congestion feedback algorithm based on max-min fairness strategy is proposed. Through the comprehensive analysis of the resource allocation constraints of multi-rate encoding/decoding modulation based on the random search-genetic algorithm, the channel allocation mechanism of multi-data-flow and the optimized routing mechanism, we build a crosslayer model and calculate the network congestion. Meanwhile, through congestion feedback this algorithm realizes the associated cross-layer optimization in physical layer,link layer and network layer respectively,and avoids congestion to the greatest extent.The simulation results show that this algorithm has better convergence when congestion occurs,and it can avoid congestion and improve the throughput.

Key words: cognitive radio wireless Mesh network;congestion feedback;cross-layer design;random search-genetic algorithm;max-min fairness strategy.