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Resource Allocation in Decode-and-Forward Cooperative Communication Networks With Limited Rate Feedback Channel

机译:具有有限速率反馈信道的解码转发协作通信网络中的资源分配

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In this paper, we propose a limited rate feedback scheme for decode-and-forward (DF) relay-assisted networks. It is assumed that the cellular user is far from the base station such that the direct communication is impossible and communication is performed with the help of a DF relay. To study the limited feedback channel, two cases are proposed: Perfect channel distribution information (CDI)-quantized channel state information (CSI) and quantized CDI-quantized CSI. While in the former, the space of channel gains is quantized into a finite number of regions, in the latter case, the space of CDI parameters is also quantized. We formulate the proposed resource allocation into an optimization problem whose objective is to maximize the average achievable rate under an average transmission power constraint. To solve the proposed optimization problems, we adopt the block coordinated descent algorithm, which is based on the space of variables partitioning into finite sets, and particle swarm optimization (PSO), which is an evolutionary computation technique. To solve the optimization problem for quantized CDI-quantized CSI case, we consider an approach based on the Lloyd algorithm. We also model and study the error in the feedback channel. Finally, the impact of different system parameters on the performance of the proposed scheme is investigated through simulations.
机译:在本文中,我们为解码和转发(DF)中继辅助网络提出了一种有限速率反馈方案。假定蜂窝用户远离基站​​,使得直接通信是不可能的,并且在DF中继的帮助下进行通信。为了研究有限反馈信道,提出了两种情况:完善信道分配信息(CDI)量化的信道状态信息(CSI)和量化CDI量化的CSI。在前者中,通道增益的空间被量化为有限数量的区域,在后者情况下,CDI参数的空间也被量化。我们将提出的资源分配公式化为一个优化问题,其目标是在平均传输功率约束下最大化平均可达到的速率。为了解决所提出的优化问题,我们采用了块协调下降算法,该算法基于将变量空间划分为有限集的方法,而粒子群优化(PSO)是一种进化计算技术。为了解决量化的CDI量化CSI情况的优化问题,我们考虑一种基于Lloyd算法的方法。我们还对反馈通道中的误差进行建模和研究。最后,通过仿真研究了不同系统参数对所提方案性能的影响。

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