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Weighted sum rate optimization for downlink multiuser MIMO systems with per antenna power constraint: Downlink-uplink duality approach

机译:具有每个天线功率约束的下行链路多用户MIMO系统的加权和速率优化:下行链路-上行链路对偶方法

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This paper considers weighted sum rate maximization constrained with a per base station (BS) antenna power problem for multiuser multiple-input multiple-output (MIMO) systems. For this problem, we propose new downlink-uplink duality based solution. We solve the problem as follows. First, by introducing additional optimization variables, we reformulate our problem into an equivalent problem that incorporates a weighted sum mean-square-error (MSE) term. Second, we establish novel weighted sum MSE duality. The duality is established by modifying the input covariance matrix of the dual uplink problem, and formulating the noise covariance matrix of the uplink channel as a fixed point function. Third, we optimize the introduced variables and powers in the downlink channel by a Geometric Program (GP) method. Fourth, using the duality result and the solution of GP, we apply alternating optimization technique to solve the original downlink problem. In our simulation results, we have observed that the proposed duality based solution utilizes less power than that of existing algorithms.
机译:本文考虑了针对多用户多输入多输出(MIMO)系统的受每个基站(BS)天线功率问题约束的加权和速率最大化。针对这个问题,我们提出了新的基于下行链路对偶性的解决方案。我们解决以下问题。首先,通过引入其他优化变量,我们将问题重新构造为包含加权和均方误差(MSE)项的等效问题。其次,我们建立了新颖的加权和MSE对偶。通过修改双上行链路问题的输入协方差矩阵,并将上行链路信道的噪声协方差矩阵公式化为定点函数,来建立对偶性。第三,我们通过几何程序(Geometric Program,GP)方法优化了下行链路信道中引入的变量和功率。第四,利用对偶结果和GP的解,我们采用交替优化技术来解决原始的下行问题。在我们的仿真结果中,我们已经观察到所提出的基于对偶性的解决方案比现有算法使用的功率更少。

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