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Power and discrete rate adaptation in BER constrained wireless powered communication networks

机译:BER受限的无线通信网络中的功率和离散速率自适应

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Optimal system throughput is a crucial design issue in wireless powered communication networks. Unlike related literature, this study considers the problem of maximising throughput (MTP) for a practical scenario, in which each user node (UN) selects its own rate from a discrete rate set and controls its transmission power according to its own channel state. The MTP with a bit-error-rate constraint is investigated based on two general uplink access methods. The formulation size is exponentially large with respect to the problem input. A novel greedy algorithm based on the column generation method (GA-CGM) is proposed to solve the problem efficiently. The GA-CGM decomposes the problem into a master problem and a subproblem. The master problem is solved by the simplex method. The subproblem is solved by a greedy algorithm due to its non-linearity programming model. The max-min throughput problem (MMTP) is also considered, because of the `doubly near-far' phenomenon which leads to the unfair throughput among different UNs. Experimental results demonstrate that the proposed solutions are close to the optimal solutions for MTP and MMTP problems. They also show increasing the transmission power of a base station or decreasing the path-loss exponent improves the throughput performance.
机译:最佳的系统吞吐量是无线通信网络中的关键设计问题。与相关文献不同,本研究在实际情况下考虑了最大化吞吐量(MTP)的问题,其中每个用户节点(UN)从离散速率集中选择其自己的速率,并根据自己的信道状态控制其传输功率。基于两种通用的上行接入方法,研究了具有误码率约束的MTP。相对于问题输入,配方大小成倍增长。提出了一种基于列生成方法的贪心算法(GA-CGM),以有效地解决该问题。 GA-CGM将问题分解为主要问题和子问题。主要问题是通过单纯形法解决的。该子问题由于其非线性编程模型而由贪婪算法解决。还考虑了最大-最小吞吐量问题(MMTP),因为存在“双近距离”现象,导致不同联合国之间的吞吐量不公平。实验结果表明,所提出的解决方案接近于MTP和MMTP问题的最佳解决方案。它们还显示出增加基站的传输功率或减小路径损耗指数可提高吞吐量性能。

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