View in EDS

Robust transceiver optimization for downlink coordinated base station systems: Distributed algorithm

Saved in:
Bibliographic Details
Title: Robust transceiver optimization for downlink coordinated base station systems: Distributed algorithm
Authors: Bogale, Tadilo Endeshaw, Vandendorpe, Luc, Chalise, B.K.
Contributors: UCL - SST/ICTM/ELEN - Pôle en ingénierie électrique, Villanova State University - EE dpt
Source: IEEE Transactions on Signal Processing, Vol. 60, no. 1, p. 337-350 (2012)
Publication Year: 2012
Collection: DIAL@USL-B (Université Saint-Louis, Bruxelles)
Subject Terms: Distributed optimization and convex optimization, Multiuser multiple-input multiple-output (MIMO), Joint transceiver design, Lagrangian dual, Matrix, Minimum mean-square-error, Mobile station, Multi user multiple input single outputs, Multi-user, Power constraints, Precoders, Robust designs, Robust transceiver, Total power, Transceiver optimization, Weighted Sum, Antennas, Base stations, Channel state information, Computer simulation, Convex optimization, Design, MIMO systems, Antenna correlation, Optimization, Transceivers, Algorithms, Centralized algorithms, Channel estimation errors, Computationally efficient
Description: This paper considers the joint transceiver design for downlink multiuser multiple-input single-output (MISO) systems with coordinated base stations (BSs) where imperfect channel state information (CSI) is available at the BSs and mobile stations (MSs). By incorporating antenna correlation at the BSs and taking channel estimation errors into account, we solve two robust design problems: 1) minimizing the weighted sum of mean-square-error (MSE) with per BS antenna power constraint, and 2) minimizing the total power of all BSs with per user MSE target and per BS antenna power constraints. These problems are solved as follows. First, for fixed receivers, we propose centralized and novel computationally efficient distributed algorithms to jointly optimize the precoders of all users. Our centralized algorithms employ the second-order-cone programming (SOCP) approach, whereas, our novel distributed algorithms use the Lagrangian dual decomposition, modified matrix fractional minimization and an iterative method. Second, for fixed BS precoders, the receivers are updated by the minimum mean-square-error (MMSE) criterion. These two steps are repeated until convergence is achieved. In all of our simulation results, we have observed that the proposed distributed algorithms achieve the same performance as that of the centralized algorithms. Moreover, computer simulations verify the robustness of the proposed robust designs compared to the nonrobust/naive designs. © 2006 IEEE.
Document Type: article in journal/newspaper
Language: English
Relation: boreal:107492; http://hdl.handle.net/2078.1/107492
DOI: 10.1109/TSP.2011.2170167
Availability: http://hdl.handle.net/2078.1/107492
https://doi.org/10.1109/TSP.2011.2170167
Rights: info:eu-repo/semantics/restrictedAccess
Accession Number: edsbas.6CBA52B0
Database: BASE
Description
Abstract:This paper considers the joint transceiver design for downlink multiuser multiple-input single-output (MISO) systems with coordinated base stations (BSs) where imperfect channel state information (CSI) is available at the BSs and mobile stations (MSs). By incorporating antenna correlation at the BSs and taking channel estimation errors into account, we solve two robust design problems: 1) minimizing the weighted sum of mean-square-error (MSE) with per BS antenna power constraint, and 2) minimizing the total power of all BSs with per user MSE target and per BS antenna power constraints. These problems are solved as follows. First, for fixed receivers, we propose centralized and novel computationally efficient distributed algorithms to jointly optimize the precoders of all users. Our centralized algorithms employ the second-order-cone programming (SOCP) approach, whereas, our novel distributed algorithms use the Lagrangian dual decomposition, modified matrix fractional minimization and an iterative method. Second, for fixed BS precoders, the receivers are updated by the minimum mean-square-error (MMSE) criterion. These two steps are repeated until convergence is achieved. In all of our simulation results, we have observed that the proposed distributed algorithms achieve the same performance as that of the centralized algorithms. Moreover, computer simulations verify the robustness of the proposed robust designs compared to the nonrobust/naive designs. © 2006 IEEE.
DOI:10.1109/TSP.2011.2170167