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Optimal Resource Allocation for Power-Efficient MC-NOMA With Imperfect Channel State Information

机译:具有不完善信道状态信息的节能型MC-NOMA的最佳资源分配

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In this paper, we study power-efficient resource allocation for multicarrier non-orthogonal multiple access systems. The resource allocation algorithm design is formulated as a non-convex optimization problem which jointly designs the power allocation, rate allocation, user scheduling, and successive interference cancellation (SIC) decoding policy for minimizing the total transmit power. The proposed framework takes into account the imperfection of channel state information at transmitter and quality of service requirements of users. To facilitate the design of optimal SIC decoding policy on each subcarrier, we define a channel-to-noise ratio outage threshold. Subsequently, the considered non-convex optimization problem is recast as a generalized linear multiplicative programming problem, for which a globally optimal solution is obtained via employing the branch-and-bound approach. The optimal resource allocation policy serves as a system performance benchmark due to its high computational complexity. To strike a balance between system performance and computational complexity, we propose a suboptimal iterative resource allocation algorithm based on difference of convex programming. Simulation results demonstrate that the suboptimal scheme achieves a close-to-optimal performance. Also, both proposed schemes provide significant transmit power savings than that of conventional orthogonal multiple access schemes.
机译:在本文中,我们研究了多载波非正交多址系统的高能效资源分配。将资源分配算法设计公式化为非凸优化问题,该问题共同设计了功率分配,速率分配,用户调度和连续干扰消除(SIC)解码策略,以使总发射功率最小。所提出的框架考虑了发射机处的信道状态信息的不完善以及用户的服务质量要求。为了便于在每个子载波上设计最佳SIC解码策略,我们定义了信噪比中断阈值。随后,将考虑的非凸优化问题重铸为广义线性乘法规划问题,通过使用分支定界方法获得全局最优解。最佳资源分配策略由于其较高的计算复杂度而成为系统性能基准。为了在系统性能和计算复杂度之间取得平衡,我们提出了一种基于凸规划差异的次优迭代资源分配算法。仿真结果表明,次优方案实现了接近最佳的性能。而且,与常规的正交多址方案相比,两种提出的方​​案都提供了显着的发射功率节省。

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