Low Complexity Green Cooperative Cognitive Radio Network With Superior Performance

Ensuring total rate maximization whilst keeping Greenhouse gas emission (GHGE) at a minimum in green cooperative cognitive radio networks (GCCRNs) is key to achieving maximum network efficiency. This study employs the lexicographic multiobjective optimization methods to overcome the challenge posed by rate maximization, GHGE minimization, and relay selection in GCCRNs simultaneously. First, through application of a technique for throughput maximization, a complex nonconvex optimization problem is transformed into its simplified convex programing equivalent. Next, the GHGE minimization is tackled by convex programing and finally a mathematical relay selection procedure is presented based on zero-norm principle which provides an effective technique to obtain a minimum node selection. Simulation results backed by a theoretical analysis confirm the superiority of the proposed approach in terms of network performance and complexity compared to some of the well-known schemes investigated in this study.