Low-Complexity Energy-Efficient Spectrum Allocation Algorithm for Cognitive Radio Networks

In Cognitive Radio (CR) networks, Secondary Users (SUs) compete for the channels that are underutilized due to the erratic usage by Primary Users (PUs). One of the key objectives of CR networks is to maximize the network's utilization by increasing the number of SUs while reducing their interference experienced by PUs and SUs. In this paper, we investigate the energy-efficient channel allocation in CR networks. Energy efficiency is defined as the number of bits transmitted per Joule of energy. We propose an efficient algorithm, Maximum-SINR Algorithm (MaxEEA), which has a low time complexity O (NSlog(S)). MaxEEA exploits the information sent by SUs to perform energy-efficient spectrum allocation using a single parameter (i.e. SNR Reduction Factor). The performance of MaxEEA is compared with two greedy algorithms and a fine-tuned metaheuristic, Binary Harmony Search Algorithm (BHSA). Experimental results show that MaxEEA has performance within 1% of that of the fine-tuned BHSA, and better than two benchmark heuristics tested.