NDLI: Robust sum rate maximization in the multi-cell MU-MIMO downlink

Content Provider	IEEE Xplore Digital Library
Author	Fritzsche, Richard Fettweis, Gerhard P.
Copyright Year	2013
Description	Author affiliation: Technische Universität Dresden, Vodafone Chair Mobile Communications Systems, Germany (Fritzsche, Richard; Fettweis, Gerhard P.)
Abstract	This paper studies linear precoding designed for the multi-cell multi-user multiple-input-multiple-output (MU-MIMO) downlink. The objective is to maximize the weighted sum rate (WSR) under imperfect channel state information (CSI) conditions and per base station (BS) transmit power constraints. The expectation of the WSR over the CSI error can be lower bounded by minimizing the expected weighted sum mean square error (MSE) assuming minimum MSE (MMSE) receive filters. The problem can be solved by an iterative algorithm which alternately calculates the MMSE receive filters given a fixed precoding matrix and vice versa. The algorithm converges to a local optimum. For the optimization of the precoding matrix under per BS power constraints, we present two robust solutions. The first one is based on the transmit Wiener filter solution under a sum power constraint combined with a consistent scaling to satisfy each per BS power constraint. In the second solution the problem is transformed into a second order cone program (SOCP) where per BS power constraints can be directly included. Simulation results show performance gains compared to robust and non-robust state of the art schemes.
Starting Page	3180
Ending Page	3184
File Size	334739
Page Count	5
File Format	PDF
ISBN	9781467359382
ISSN	15253511
e-ISBN	9781467359399
e-ISBN	9781467359375
DOI	10.1109/WCNC.2013.6555071
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-04-07
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	MIMO Optimization Robustness Covariance matrices Signal to noise ratio Vectors Downlink
Content Type	Text
Resource Type	Article

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