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Resource Allocation Based on User Pairing and Subcarrier Matching for Downlink Non-Orthogonal Multiple Access Networks

机译:基于用户配对和下行链路非正交多址网络的子载波的资源分配

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摘要

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.
机译:传统的正交多次访问(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,非正交多次访问(NOMA)和连续干扰消除(SIC)的实现是必不可少的。在本文中,提出了一种利纳数的最佳资源分配算法,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非确定性多项式 - 时间(NP)的混合整数编程的非凸面问题,因此提出了一种三步解决方案来解决原始问题。首先,我们通过使用单调辨别方法确定外部用户的最佳功率分配,然后确定最佳用户配对。其次,引入了连续的凸近似(SCA)方法以将涉及中央用户进入凸面的非凸面问题,并使用拉格朗日双方法来确定最佳解决方案。最后,使用标准的匈牙利算法来确定最佳的子载波匹配。仿真结果表明,资源分配算法能够满足NOMA的用户性能要求,与现有算法相比,改善了总系统速率。

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