Non-orthogonal multiple access (NOMA)-based cognitive radio (CR) networks have recently emerged as a promising solution to enhance the spectral efficiency and massive connectivity problems. In this paper, we investigate the error rate performance of relay-assisted NOMA with partial relay selection in an underlay cognitive radio network. In this setup, $K$ relays are used to assist in transmission between secondary NOMA users and a secondary base station (SBS), where the relay (R) with the strongest link with the SBS is selected to amplify-and-forward (AF) its received signals to the secondary receivers. We derive an accurate approximation for the pairwise error probability (PEP) of the secondary users with imperfect successive interference cancellation (SIC). Subsequently, the derived PEP expression is utilized to deduce a union bound, which is considered as an upper bound on the bit error rate (BER). We further formulate an optimization problem to calculate the optimum power coefficients that minimize the derived union bound. Numerical and Monte Carlo simulation results are presented to corroborate the derived analytical expressions and give some useful insights into the error rate performance of each user.

中文翻译：

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具有部分中继选择和干扰功率约束的基于 NOMA 的认知无线电网络的错误性能

基于非正交多址 (NOMA) 的认知无线电 (CR) 网络最近已成为提高频谱效率和大规模连接问题的有前途的解决方案。在本文中，我们研究了在底层认知无线电网络中具有部分中继选择的中继辅助 NOMA 的错误率性能。在此设置中，$K$ 中继用于辅助次要 NOMA 用户和次要基站 (SBS) 之间的传输，其中选择与 SBS 具有最强链路的中继 (R) 进行放大转发 (AF) ) 其接收到的信号到辅助接收器。我们推导出具有不完美连续干扰消除 (SIC) 的次级用户的成对错误概率 (PEP) 的准确近似值。随后，派生的 PEP 表达式用于推导出联合边界，这被认为是误码率 (BER) 的上限。我们进一步制定了一个优化问题来计算最小化导出联合边界的最佳功率系数。提供了数值和蒙特卡罗模拟结果以证实导出的分析表达式，并为每个用户的错误率性能提供一些有用的见解。