An energy efficient resource allocation in cognitive radio networks with pairwise NBS optimization for multi-secondary users

In this paper, we focus on an energy efficient resource allocation in the multi-secondary user (SU) cognitive radio networks with network coding based cooperative transmission (NcCT). We set up a framework for multi-SU resource allocation game with Nash bargaining solution (NBS) under the cognitive radio scenario (CR-MSU-NBS game) where the sum of pairwise NBS function with pairing strategy is exploited as the network optimization objective and context conditions as constraints. Thereby, the network performance is improved by pairwise SUs´ win-win cooperation on both system throughput and fairness. Since the CR-MSU-NBS game is NP-hard, we resolve it by a heuristic method. After testifying the global network NBS optimization pairing method, we propose the energy efficient suboptimal resource allocation scheme for multi-SUs. The simulation results show that the proposed scheme achieves a good tradeoff between fairness and efficiency and outperforms the familiar distance-pairing schemes; meanwhile, it achieves a 33.4% energy efficiency improvement but only 7.8% fairness loss averagely to the high computation complexity optimal method with ergodic search.