Traffic aware resource allocation for throughput optimization in cognitive radio wireless mesh networks

Resource allocation plays an important role for the performance of cognitive radio based wireless mesh networks that are capable of multiple channel access. In order to maximize the entire network throughput, the interference aware resource allocation model including channel assignment and link scheduling to satisfy all routing requirements is presented. A novel genetic algorithm based channel assignment combined with a heuristic algorithm is proposed to solve the minimum scheduling period. In order to ensure the individual validity and fast convergence, the link based encoding rules and population evolution strategies are designed. Numerical results show that the performance given by our algorithms can eliminate the interference between the wireless mesh routers and maximizes the transmission concurrency of all routing sessions efficiently.