Optimal Transceiver Design for Interference Alignment Based Cognitive Radio Networks

Interference alignment (IA) can effectively eliminate the interference among users in cognitive radio (CR) networks. Nevertheless, to further increase the transmission rate of the primary user (PU) and guarantee its priority, we propose an optimal transceiver design (OTD) scheme for IA-based CR networks in this letter. In the OTD scheme, two partial-IA based algorithms are proposed to design the precoding matrices of SUs, in which the interference is aligned at the primary receiver with much lower overhead and complexity. Then the PU's precoding matrix is designed to maximize its throughput accordingly. To further improve the performance of SUs, their decoding matrices are re-designed. Simulation results are presented to show the effectiveness of the proposed scheme.