2013/11/25 by Tadilo Endeshaw Bogale, Bogale, Tadilo Endeshaw, Luc Vandendorpe +1
Computer Science · Engineering · #Advanced MIMO Systems Optimization #Advanced Wireless Communication Techniques #Cooperative Communication and Network Coding #FOS: Mathematics #Optimization and Control (math.OC)
paper · pdf · doi:10.48550/arxiv.1311.6430
openalex publication_date 2013/11/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper considers linear transceiver design for downlink multiuser\nmultiple-input multiple-output (MIMO) systems. We examine different transceiver\ndesign problems. We focus on two groups of design problems. The first group is\nthe weighted sum mean-square-error (WSMSE) (i.e., symbol-wise or user-wise\nWSMSE) minimization problems and the second group is the minimization of the\nmaximum weighted mean-squareerror (WMSE) (symbol-wise or user-wise WMSE)\nproblems. The problems are examined for the practically relevant scenario where\nthe power constraint is a combination of per base station (BS) antenna and per\nsymbol (user), and the noise vector of each mobile station is a zero-mean\ncircularly symmetric complex Gaussian random variable with arbitrary covariance\nmatrix. For each of these problems, we propose a novel downlink-interference\nduality based iterative solution. Each of these problems is solved as follows.\nFirst, we establish a new mean-square-error (MSE) downlink-interference\nduality. Second, we formulate the power allocation part of the problem in the\ndownlink channel as a Geometric Program (GP). Third, using the duality result\nand the solution of GP, we utilize alternating optimization technique to solve\nthe original downlink problem. For the first group of problems, we have\nestablished symbol-wise and user-wise WSMSE downlink-interference duality.\n