Energy-efficient power allocation algorithm in cognitive radio networks

Most of traditional power allocation algorithms are often based on maximum capacity technology (MCT) in cognitive radio networks (CRNs) at the expense of higher energy consumption. The optimisation of energy efficiency power allocation schemes are important performance in green communication. This study investigates the energy efficient power allocation for orthogonal frequency division multiplexing based CRNs in underlay mode. The authors' scheme is obtained by optimising an objective function consisting of the users' performance degradation and the network interference, in the same time to track time-varying target of signal to inference plus noise ratio (SINR) under maximum transmit power for each cognitive user and interference power constraint from primary user. A convex optimisation problem is formulated where the tradeoff between energy consumption and transmission capacity is considered, and a distributed algorithm is developed to solve this problem. Simulation results show that the authors' proposed algorithm can guarantee an acceptable target SINR for all cognitive users and significantly improves energy efficiency compared with throughput per Joule and MCT schemes. Furthermore, the proposed algorithm with the introduced appropriate weight parameters can get higher transmission capacity.