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Joint Resource Allocation and Cooperative Transmission in Distributed Wireless Powered Communication Networks

机译:分布式无线电力通信网络中的联合资源分配和协作传输

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In this paper, a distributed wireless powered communication network (WPCN) which consists of a center processor(CP), multiple hybrid remote radio heads (RRHs) and multiple terminal nodes is studied. Firstly, all terminal nodes harvest the wireless energy broadcast by RRHs and send their information bits to the associated RRHs by time-division-multiple-access (TDMA). Then, each RRH sends information bits received from terminal nodes to CP via wireless fronthaul links. We jointly optimize the terminal-RRH associations and the transmit power and transmission time of RRHs and terminals to minimize the transmission completion time. The original problem is a mixed-integer nonlinear programming and we solve it by Generalized Benders Decomposition (GBD) which can get the optimal solution by generating a series upper bounds and lower bounds. When terminal-RRH associations are fixed, we speed up the resource allocation algorithm by Alternating Direction Multiplier Method (ADMM) in which the solutions to small local subproblem are coordinated to find a solution of the global problem. Simulation results reveal the influence of the average power and the number of RRHs on the spectral efficiency.
机译:本文研究了由中央处理器(CP),多个混合远程无线电头(RRH)和多个终端节点组成的分布式无线通信网络(WPCN)。首先,所有终端节点收集由RRH广播的无线能量,并通过时分多址(TDMA)将其信息比特发送到关联的RRH。然后,每个RRH通过无线前传链路将从终端节点接收到的信息比特发送到CP。我们共同优化了终端-RRH关联以及RRH和终端的发送功率和发送时间,以最大程度地缩短发送完成时间。最初的问题是混合整数非线性规划,我们通过广义Benders分解(GBD)解决了该问题,可以通过生成一系列上限和下限来获得最优解。固定终端-RRH关联后,我们通过交替方向乘数法(ADMM)加快了资源分配算法的速度,在该算法中,对局部小问题的解决方案进行了协调,以找到全局问题的解决方案。仿真结果揭示了平均功率和RRH数量对频谱效率的影响。

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