Fading performance evaluation of a semi-blind space-time equaliser for frequency selective MIMO systems


Cheng, Huiting and Chen, Sheng (2011) Fading performance evaluation of a semi-blind space-time equaliser for frequency selective MIMO systems. Journal of the Franklin Institute, 348, (10), 2823-2838.

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Description/Abstract

A semi-blind adaptive space–time equaliser (STE) has recently been proposed based on a concurrent gradient-Newton(GN) constant modulus algorithm (CMA) and soft decision-directed (SDD) scheme for dispersive multiple-input multiple-output (MIMO) systems that employ high-throughput quadrature amplitude modulation signalling. A minimum number of training symbols, approximately equal to the dimension of the STE, is used to provide a rough initial estimate of the STE’s weight vector. The concurrent GN based CMA and SDD blind adaptive scheme is then adopted to adapt the STE. This semi-blind STE has a complexity similar to that of the training-based recursive least squares (RLS) algorithm. For stationary MIMO channels, it has been demonstrated that this semi-blind adaptive STE is capable of converging fast to the optimal minimum mean square error STE solution. In this contribution, we investigate the performance of this semi-blind adaptive STE operating in Rayleigh fading MIMO systems. Our results obtained show that the tracking performance of this semi-blind adaptive algorithm is close to that of the training-based RLS algorithm. Thus, this semi-blind adaptive STE offers an effective and practical means to successfully operate under the highly dispersive and fading MIMO environment.

Item Type: Article
Divisions: Faculty of Physical and Applied Science > Electronics and Computer Science > Comms, Signal Processing & Control
Item ID: 272969
Date Deposited: 31 Oct 2011 09:29
Last Modified: 25 Aug 2012 02:55
Contributors: Cheng, Huiting (Author)
Chen, Sheng (Author)
Date: December 2011
Status: Published
Further Information:Google Scholar
ISI Citation Count:2
URI: http://eprints.soton.ac.uk/id/eprint/272969

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