Sub-carrier allocation algorithm based on maximum likelihood ratio spectrum detection in cognitive radio

In cognitive radio (CR) systems with multi-carrier modulation, sub-carrier allocation is the premise for the realization of spectrum sharing for Primary Users (PUs) and Secondary Users (SUs). A sub-carrier allocation algorithm based on maximum likelihood ratio detection (MLD) in cognitive OFDM is introduced and studied. SUs detect the occurrence and spectrum gap of PU signals with MLD model in a distributive way, while the system allocates sub-carriers to SUs dynamically. Cognitive base station (CBS) makes the final decision by combining each sub-carriers local sensing result with special fusion rule. The upper and lower bound of the decision region, detection probability and false alarm probability of the MLD model are derived, and a performance comparison between MLD and energy detection (ED) is presented. Simulation results indicate that, compared with ED, the decision threshold of MLD is related to the average received SNR at the sub-carrier, and that the detection performance adapts to channel variation. Therefore, applied to sub-carrier allocation in CR multi-carrier modulation, MLD can enhance the cognitive OFDM sub-carrier spectrum sensing performance significantly and realize the utilization of limited spectrum resource efficiently, thus, meeting the requirements of “green communication” could be achieved effectively.