Robust MMSE Beamforming for Multiantenna Relay Networks
Robust MMSE Beamforming for Multiantenna Relay Networks
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DOI：
10.1109/tvt.2016.2601344
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发表时间：
2017-05
影响因子：
6.8
通讯作者：
K. Cumanan;Z. Ding;Y. Rahulamathavan;M. Molu;Hsiao-Hwa Chen
中科院分区：
文献类型：
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作者：
K. Cumanan;Z. Ding;Y. Rahulamathavan;M. Molu;Hsiao-Hwa Chen
本文提出了一种稳健的基于最小均方误差(MMSE)的多天线中继广播信道波束形成技术，其中多天线基站通过多天线中继将信号传输到单天线用户。从基站到单天线用户的信号传输在两个时隙内完成，中继器在第一个时隙接收来自基站的信号，然后基于放大和转发(AF)协议将接收到的信号转发到不同的用户。针对中继器和用户之间存在不完全信道状态信息的和功率最小化问题，提出了一种稳健的波束形成技术。这个稳健的方案是基于最坏情况优化框架和纳米罗夫斯基引理，通过在CSI中加入不确定性而得到的。由于基站波束形成向量、中继放大矩阵和接收机系数的联合非凸性，将原优化问题分解为三个子问题。利用纳米罗夫斯基引理将这些子问题描述为一个凸优化框架，并通过交替优化每个具有信道不确定性的子问题来开发迭代算法。此外，我们还提供了一个优化框架来评估在给定的设计参数集下每个用户可达到的最坏情况均方误差(MSE)。仿真结果验证了该算法的收敛性能。
In this paper, we propose a robust minimum mean square error (MMSE)-based beamforming technique for multiantenna relay broadcast channels, where a multiantenna base station transmits signal to single antenna users with the help of a multiantenna relay. The signal transmission from the base station to the single antenna users is completed in two time slots, where the relay receives the signal from the base station in the first time slot, and it then forwards the received signal to different users based on amplify and forward (AF) protocol. We propose a robust beamforming technique for a sum-power minimization problem with an imperfect channel state information (CSI) between the relay and the users. This robust scheme is developed based on the worst-case optimization framework and the Nemirovski Lemma by incorporating uncertainties in the CSI. The original optimization problem is divided into three subproblems due to joint nonconvexity in terms of beamforming vectors at the base station, the relay amplification matrix, and receiver coefficients. These subproblems are formulated into a convex optimization framework by exploiting the Nemirovski Lemma, and an iterative algorithm is developed by alternatively optimizing each of them with channel uncertainties. In addition, we provide an optimization framework to evaluate the achievable worst-case mean square error (MSE) of each user for a given set of design parameters. Simulation results are provided to validate the convergence of the proposed algorithm.