Research On Routing Technology In Wireless Mesh Networks Based On Cognitive Radio

As a new type wireless network, wireless mesh network has the advantages of high bandwidth, high speed, flexible networking and high network coverage ratio, making it received extensive attention in the industry. Cognitive radio technology allows users to access spectrum dynamically by the way of opportunistic occupation which alleviates the problem of spectrum shortage. In order to combine the advantages of these two technologies, overcome the shortcomings of the existing communication system, and provide an ideal solution to the problem of "the last mile access" to make communication "ubiquitous", cognitive radio technology is introduced to the wireless mesh network. In this paper, a joint optimization of channel allocation, power control and routing technology is researched according to the characteristics of wireless cognitive radio mesh network.Aiming at the problem of unicast routing in wireless cognitive radio mesh network, a unicast routing model combined with power control and channel allocation is presented, which quantifies communication power level of the nodes by considering channel assignment, power control, flow conservation, route scheduling and many other factors. With the goal of maximizing the network congestion avoidance coefficient, a unicast routing algorithm based on nested genetic algorithms is proposed. The outer genetic algorithm is used to complete the channel and power allocation by adopting integer coding. The inner genetic algorithm is applied to schedule all the routes and select the optimal path by using symbolic coding. Further, to solve the problem of network congestion and link failure, by introducing multipath routing technology, linear programming is applied to select the optimal routing path. To enhance the network flow ratio, a unicast routing algorithm based on genetic algorithm and linear programming is presented. Extensive simulation results verify the effectiveness of the proposed algorithms.To further improve the utilization rate of network resources, the multicast routing problem in cognitive wireless mesh network is researched in depth. Considering the link interference and noise interference in the network, the multicast routing optimization model is proposed on the basis of SINR interference model to minimize the transmission delay. A multicast tree optimization method is designed based on genetic algorithm. Based on the multicast tree constructed, a nested multicast optimization algorithm joint with channel allocation is proposed. Further to improve the transmission efficiency and reduce node interference, by quantizing the power control level of each node, a multicast routing algorithm with variable power is proposed based on the nested genetic scheme. Extensive simulation results are presented to demonstrate the effectiveness of our proposed algorithms.