Cognitive radio access based on multiparameter matching ability estimation

In this paper, we focus on the channel usage efficiency for secondary user in cognitive radio networks. We formulate the optimization objective as the total reward maximization by Partially Observable Markov Decision Processes (POMDPs). The total reward is maximized by considering multidimensional context parameters including allowable channel transmission rate, queue delay and arrival rate. Match Ability is proposed considering above context parameters. A heuristic greedy algorithm is proposed for each secondary user to access sensed channels based on the local maximum match ability. By combining the utility function of average waiting time with match ability, we improve the global scheduling delay fairness. We demonstrate by simulation results that as the average arrival rate of secondary user increases, the large stable region of low delay can be efficiently maintained by varying utility function of the average waiting time.