Entropy-Based Opportunistic Spectrum Access Algorithm in Cognitive Radio Networks

In this paper, we propose an opportunistic channel access scheme based on weighted residual entropy function in cognitive radio networks. This central decision scheme significantly improves spectrum utilization compared with random and first opportunistic spectrum access schemes. Particularly, in this mechanism, appropriate spectrum opportunity will be selected based on the usefulness of idle channel’s lifetime, which will be estimated through weighted residual entropy function of available licensed channels. We show that performance of the proposed spectrum decision technique in terms of channel utilization, channel collision and spectrum handoff rate are efficient in period of simulation time (1s). The simulation results confirm that the proposed Maximum Entropy Channel Access (MECA) scheme would be a viable spectrum decision technique in terms of channel utilization and energy consumption when compared with Random Channel Access (RCA), First Opportunistic Channel Access (FOCA), and Maximum Remaining Lifetime (MRL) schemes. Keywords— Channel Access, Cognitive Radio, Residual Entropy, Spectrum Utilization