PSO-Based Resource Allocation in Cognitive Radio Ad-Hoc Network

Increasing demand for spectrum causes the emergence of technologies like Cognitive Radio (CR). Resources like bandwidth and energy are primarily shared by the primary and secondary users in the CR network. Resource utilization depends on the number of nodes, topology dimension, packet generation rate, and time of channel utilization. Therefore, optimizing resources in CR is a need of the hour. In the presented paper, a PSO-based resource allocation scheme is implemented. The input parameters like the number of secondary user nodes, packet generation rate, dimension of the network, and simulation time are targeted to get optimum results of packet delivery ratio, average throughput, average delay, and energy consumption. To implement CR, NS-2 is used. The fitness equations are obtained by varying the input parameters in a given range. Curve-fitting software is used to get fitness equations. These fitness equations are then used in the PSO algorithm, which is implemented in MATLAB. With implementing a PSO-based resource allocation scheme, the performance of packet delivery ratio, throughput, delay, and energy consumption increased by 22.15 %, 22.15 %, 67.83 %, and 32.18 %, respectively.