New algorithm for joint subchannel and power allocation in multi-cell OFDMA-based cognitive radio networks

In this study, the authors propose an efficient resource allocation algorithm in downlink of an orthogonal frequency division multiple access (OFDMA)-based multi-cell underlay cognitive radio network. A more realistic model in which multiple secondary users and primary users coexist in a multi-cell environment has been considered. The main challenge of this model is inter-cell as well as intra-cell interference. The proposed algorithm tackles the challenges by adaptively subchannel and power allocation in cognitive radio network. Firstly, based on initial power allocation and with taking throughput of secondary users and signal-to-interference plus noise ratio constraint of the primary users into account, subchannel allocation is done by Hungarian method. Then, an iterative water-filling is implemented to enhance the initialised power allocation. Simulation results demonstrate the strength of the authors proposed scheme compared with some other suboptimal algorithms. The proposed scheme provides significant improvement over the traditional fixed subchannel allocation scheme in terms of spectral efficiency. In addition, it has been shown that the proposed water-filling policy loads more power into secondary user´s band compared with an equal power allocation policy in order to achieve higher throughput.