Performance analysis of opportunistic spectrum access based on partially observable Markov decision process

Abstract To maximize the throughout of AD hoc system with opportunistic spectrum access (OSA) among multiple secondary users is analyzed. Two distributed learning and allocation schemes are studied by using greedy and random approach, which can maximize the cognitive system throughput or equivalently minimize the total regret in distributed learning and allocation. The simulation results show that the performance of OSA in AD hoc system are affected by package arrival rate and the number of second users. When the second users are less than six, or the package arrival rate is less than 0.06, the throughput of greedy approach is higher than that of random approach, and greedy approach is recommended to be adopted in the design of OSA in AD hoc system.