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Distributed weighted sum-rate maximization with multi-cell uplink-downlink throughput duality

机译:具有多小区上行链路-下行链路吞吐量对偶性的分布式加权总和速率最大化

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The weighted sum-rate maximization (WSRMax) problem is important for the radio resource allocation in wireless networks. In this paper, we focus on solving the WSRMax optimization problem in a Home eNodeB (HeNB) wireless network for the multiple input single output (MISO) downlink transmission. Based on an ameliorated max-min multi-cell uplink-downlink throughput duality, we design a distributed algorithm which contains Loop1 and Loop2 associating with the max-min procedure, respectively. Especially, in Loop2 procedure, we propose a new distributed iteration scheme with the complete proof. During the implementation of the proposed algorithm, randomly deployed HeNBs only need to share information with their neighboring nodes. Simulation results show that the two processes can converge to a stable state, and the network capacity is dramatically improved with the coordination among HeNBs.
机译:加权和率最大化(WSRMax)问题对于无线网络中的无线电资源分配很重要。在本文中,我们专注于解决家庭eNodeB(HeNB)无线网络中针对多输入单输出(MISO)下行链路传输的WSRMax优化问题。基于改进的最大-最小多小区上行链路-下行链路吞吐量对偶性,我们设计了一种分布式算法,该算法包含分别与最大-最小过程关联的Loop1和Loop2。特别是,在Loop2程序中,我们提出了具有完整证明的新的分布式迭代方案。在所提出算法的实施期间,随机部署的HeNB仅需要与其相邻节点共享信息。仿真结果表明,这两个过程可以收敛到一个稳定的状态,并且通过HeNB之间的协调,网络容量得到了显着提高。

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