Particle Swarm Optimization-Based Energy Efficient Channel Assignment Technique for Clustered Cognitive Radio Sensor Networks

In a clustered cognitive radio sensor network (CRSN), the available free channels should be considered during cluster head (CH) election. Energy consumption desires have to be taken into consideration in order to improve the fairness. To meet these goals, this paper proposes a Particle Swarm Optimization-based Energy Efficient Channel Assignment (PSOEECA) technique for clustered CRSN. The election of CHs is based on the number of free channels and residual energy. At the beginning of each frame, the elected CH broadcasts a beacon signal about the selected operation mode to the cluster members (CMs). The CH performs channel assignment based on the predicted residual energy of the CMs using PSO technique. In the inter-cluster channel assignment, for transmission of data across multiple clusters, each CH exchanges the assigned channel information among them for scheduling transmission and ensuring the correctness of data delivered to the sink. Simulation results show that the proposed technique enhances throughput, network lifetime and minimizes delay and overhead.