In this study, the problem of joint relay selection and power allocation (J-RS-PA) for NOMA-based multicast cognitive radio networks is considered. In particular, the aim is to simultaneously maximise the end-to-end SINR/SNR of the primary and secondary transmitter–receiver (TR) pairs, subject to quality-of-service (QoS) constraints. Communication between the primary and secondary TR pairs is performed over two-phases, namely, the broadcasting phase, and the cooperation phase. In the broadcasting phase, the primary and secondary transmitters broadcast their data symbols; while in the cooperation phase, the selected relay forwards the decoded symbols to their intended receivers. However, the formulated J-RS-PA problem happens to be non-convex, resulting in computationally-prohibitive complexity. Consequently, an optimal low-complexity two-stage relay selection and power allocation (TS-RS-PA) algorithm is devised, which is based on the solution of linear programming problem reformulations. Simulation results are presented to validate the proposed TS-RS-PA algorithm, which is shown to yield the optimal SINR/SNR values in comparison to the J-RS-PA scheme, but with lower computational complexity, while satisfying QoS constraints.

中文翻译：

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基于NOMA的组播认知无线电网络的联合中继选择和功率分配

在这项研究中，考虑了基于NOMA的组播认知无线电网络的联合中继选择和功率分配（J-RS-PA）问题。特别是，其目的是在服务质量（QoS）约束下，同时使主要和次要收发器（TR）对的端到端SINR / SNR最大化。主要和次要TR对之间的通信是在两个阶段执行的，即广播阶段和协作阶段。在广播阶段，主要和次要发射机广播其数据符号；而在合作阶段，所选中继将已解码符号转发到其预期的接收者。但是，制定的J-RS-PA问题恰好是非凸的，从而导致计算上的复杂性。所以，基于线性规划问题重构的解决方案，设计了一种最优的低复杂度二级继电器选择和功率分配算法。给出仿真结果以验证所提出的TS-RS-PA算法，与J-RS-PA方案相比，该算法可产生最佳SINR / SNR值，但计算复杂度较低，同时满足QoS约束。