Green Metric Optimization in Cooperative Cognitive Radio Networks With Statistical Interference Parameters

We study an energy efficiency (EE)-optimized power allocation technique for a source and a relay in a cooperative cognitive radio network. We formulate the optimization problem with the constraint on probabilistic interference parameters and throughput as a fractional programming problem. The problem is quasi-convex, for which a local optimal solution may not be guaranteed as a global optimal solution. Hence, we transform the problem into an equivalent convex programming problem using the Charnes–Cooper transformation technique to obtain an optimal solution. We analyze the channel access probability, EE, and total power performance of the cooperative cognitive green radio network via simulation.