A new efficient optimization approach for Green Cognitive Radio-based Cooperative Networks

In this paper, as the first step we apply a new optimization algorithm to the problem of source/relay power allocation in green cooperative cognitive radio (GCCR) networks. This algorithm is based on Newton’s law of cooling, which will be called Thermal Exchange Optimization (TEO) algorithm. We use shared-band amplify-and-forward (SBAF) relaying for cooperative communication in this problem. The proposed source/relay power allocation performs power allocation in GCCR while optimizing two conflicting objectives: The first one is to maximize the total rate, and the second one is to minimize the greenhouse gas (GHG) emissions in GCCR networks. Because of using weighted sum method (WSM), power is not optimized completely. To solve this issue as the second step, an efficient water-filling algorithm is used. We present simulation results that verify the effectiveness of the proposed TEO method combined with water-filling algorithm for source/relay power allocation. This effectiveness is shown in terms of fitness, throughput gain and emission effect.