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首页> 外文期刊>Eurasip Journal on Wireless Communications and Networking >Distributed algorithms for sum rate maximization in multi-cell downlink OFDMA with opportunistic DF relaying
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Distributed algorithms for sum rate maximization in multi-cell downlink OFDMA with opportunistic DF relaying

机译:机会DF中继的多小区下行OFDMA中总速率最大化的分布式算法

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摘要

This paper considers a multi-cell orthogonal frequency division multiple access (OFDMA) downlink system with several decode-and-forward (DF) relay stations (RSs) aiding the base station (BS) transmissions. The problem considered is the maximization of the system sum rate with a total power constraint in each cell. An iterative semi-distributed resource allocation (RA) algorithm is first proposed to optimize mode selection (decision whether relaying should be used or not and which relay), subcarrier assignment (MSSA), and power allocation (PA), alternatively. During the MSSA stage, the problem is decoupled into subproblems which can be solved distributively in linear time. During the PA stage, an algorithm based on single condensation and Lagrange duality (SCLD) is designed to optimize PA with the tentative MSSA results. The convergence of the SCLD-based RA algorithm is theoretically guaranteed and an local optimum is reached after convergence. To solve the formulated problem autonomously, a modified iterative water-filling (IWF) algorithm is further proposed. Specifically, each cell autonomously optimizes its own sum rate with the estimated power values of the received interferences from the other cells. An optimum algorithm is proposed to solve the local RA problem in each cell. Through numerical experiments, the convergence of the two proposed algorithms as well as their benefits compared with a centralized algorithm (CA) are illustrated.
机译:本文考虑了一种具有多个辅助基站(BS)传输的解码转发(DF)中继站(RS)的多小区正交频分多址(OFDMA)下行链路系统。所考虑的问题是在每个单元中具有总功率约束的系统总和率的最大化。首先,提出一种迭代半分布式资源分配(RA)算法,以优化模式选择(决定是否应使用中继以及哪个中继),子载波分配(MSSA)和功率分配(PA)。在MSSA阶段,问题被分解为多个子问题,可以在线性时间内分布式解决。在PA阶段,设计了一种基于单缩合和拉格朗日对偶性(SCLD)的算法,以利用暂定MSSA结果优化PA。理论上保证了基于SCLD的RA算法的收敛性,收敛后达到了局部最优。为了自动解决所提出的问题,进一步提出了一种改进的迭代注水算法。具体地,每个小区利用从其他小区接收的干扰的估计功率值自主地优化其自身的求和率。提出了一种优化算法来解决每个小区的局部RA问题。通过数值实验,说明了两种算法的收敛性以及与集中式算法(CA)相比的优势。

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