The traditional orthogonal multiple access (OMA) is unable to satisfy the needs of large number of smart devices. To increase the transmission rate in the limited spectrum resource, implementation of both non-orthogonal multiple access (NOMA) and successive interference cancelation (SIC) is essential. In this paper, an optimal resource allocation algorithm in NOMA is proposed to maximize the total system rate in a multi-sector multi-subcarrier relay-assisted communication network. Since the original problem is a non-convex problem with mixed integer programming which is non-deterministic polynomial-time (NP)-hard, a three-step solution is proposed to solve the primal problem. Firstly, we determine the optimal power allocation of the outer users by using the approach of monotonic discrimination, and then the optimal user pairing is determined. Secondly, the successive convex approximation (SCA) method is introduced to transform the non-convex problem involving central users into convex one, and the Lagrangian dual method is used to determine the optimal solution. Finally, the standard Hungarian algorithm is utilized to determine the optimal subcarrier matching. The simulation results show that resource allocation algorithm is able to meet the user performance requirements with NOMA, and the total system rate is improved compared to the existing algorithms.

中文翻译：

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基于用户配对和子载波匹配的下行非正交多址网络资源分配

传统的正交多址访问（OMA）无法满足大量智能设备的需求。为了提高有限频谱资源中的传输速率，非正交多址（NOMA）和连续干扰消除（SIC）的实现都是必不可少的。本文提出了一种在NOMA中的最优资源分配算法，以最大化多扇区多子载波中继辅助通信网络中的总系统速率。由于原始问题是具有不确定的多项式时间（NP）-hard的混合整数规划的非凸问题，因此提出了三步解决方案来解决原始问题。首先，我们采用单调判别的方法确定外部用户的最优功率分配，然后确定最优用户配对。其次，引入逐次凸逼近法（SCA）将涉及中心用户的非凸问题转化为凸问题，并采用拉格朗日对偶法确定最优解。最后，使用标准的匈牙利算法来确定最佳子载波匹配。仿真结果表明，资源分配算法可以满足用户使用NOMA的性能要求，与现有算法相比，提高了系统总速率。