Sorted Chase Detection Algorithm for MIMO System

In multiple-input multiple-output wireless communication system, the order of symbol detection in Chase framework is critical because of error propagation. In order to improve chase detector’s performance, sorted chase detection algortihm to reduce error propagation is proposed here. By setting parameters at different values, trade-off between performance and complexity can be obtained properly. Simulation experiment results show the validity of proposed algorithm. Introduction In multiple-input multiple-output (MIMO) wireless system, communication capacity can be increased enormously without increasing the bandwidth or transmitted power [1]. Serial data streams are converted to parallel and transmitted on different antenna in MIMO system. In order to decode symbols, efficient signal detection algorithms for MIMO systems have attracted much interest in recent years [2,3], and many detection techniques had been proposed such as line detection, maximum likelihood (ML) detection, Bell-Labs layered space-time (VBLAST) detection [4], etc. ML detection algorithm is the optimum detection algorithm at the performance of bit-error rate (BER), but the computational complexity growing exponentially with the order of modulation and the number of transmit-antennas, which makes the ML detection algorithm difficulty to use in practice. Other detections have low computation complexity comparing with ML detection; meanwhile the performance is also lower than ML detection. A lot of efforts have been put into the search of detection algorithms achieving ML or near-ML performance with lower complexity, such as tree search algorithm, lattice reduction, chase detector, and so on. Chase detector for MIMO detection is combined with a list detector and parallel banks of subdetectors [5]. Chase detector could be regarded as the unified framework of existing detectors including ML, successive interference cancellation detection (SIC), and VBLAST detection. From the detection mechanism of chase detector, it can be regarded as SIC detection algorithm in essence. When wrong symbol is selected in the first detection stage, it will lead to error propagation in later sub-detectors. In order to reduce error propagation and calculating complexity, a sorted chase detection algorithm is proposed here which use QR decomposition to create candidate list without calculation of pseudo-inverses of channel matrix and an adjustable parameters to restrain error producing further more. These schemes can reduce the error in initially detection step by selecting the symbols with minimum error into the list. Trade-off between performance and complexity can be obtained by proposed detection algorithm. Advanced Engineering Forum Online: 2012-09-26 ISSN: 2234-991X, Vols. 6-7, pp 279-283 doi:10.4028/www.scientific.net/AEF.6-7.279 © 2012 Trans Tech Publications, Switzerland All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of Trans Tech Publications, www.ttp.net. (ID: 54.218.61.141-15/01/16,19:26:21) Proposed Detection Algorithm System Model. Un-coded MIMO system is consisted of N transmit antennas at the transmitter and M antennas at the receiver ( M N ≥ ). The wireless channel is assumed to be quasi-static, so the received signal vector can be represented as ( ) ( ) ( ) ( ) t t t t = + y H x n (1) where ( ) ( ) ( ) H 1 ,..., N t x t x t =     x , ( ) ( ) ( ) H 1 ,..., M t y t y t =     y and ( ) ( ) ( ) H 1 ,..., M t n t n t =     n is the sent symbol, the received symbol and the noise symbol, respectively. The symbols ( ) n x t and the noise ( ) m n t are mutually uncorrelated, zero-mean random processes, which variances is ( ) { } 2 E 1 n x t = and ( ) { } 2 2 E m n t σ = , respectively. The element ij h of ( ) t H represents channel gains between the th j transmitter and the th i receiver antennas at the discrete time t. Original Chase Detection Framework. The Chase detector defines a framework for existing MIMO detection algorithms. Five steps are contained in Chase detector, as shown in Fig.1.