This article is part of the series Advances in Propagation Modeling for Wireless Systems.

Open Access Research Article

Reduced Complexity Channel Models for IMT-Advanced Evaluation

Yu Zhang1*, Jianhua Zhang1, PeterJ Smith2, Mansoor Shafi3 and Ping Zhang4

Author Affiliations

1 Wireless Technology Innovation Institute, Beijing University of Posts and Telecommunications, P.O. Box 92, Beijing 100876, China

2 Department of Electrical and Computer Engineering, University of Canterbury, Private Bag 4800, 8140 Christchurch, New Zealand

3 Telecom New Zealand, P.O. Box 293, 6001 Wellington, New Zealand

4 Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, P.O. Box 92, Beijing 100876, China

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EURASIP Journal on Wireless Communications and Networking 2009, 2009:195480 doi:10.1155/2009/195480


The electronic version of this article is the complete one and can be found online at: http://jwcn.eurasipjournals.com/content/2009/1/195480


Received:31 July 2008
Revisions received:6 November 2008
Accepted:26 February 2009
Published:7 April 2009

© 2009 The Author(s).

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Accuracy and complexity are two crucial aspects of the applicability of a channel model for wideband multiple input multiple output (MIMO) systems. For small number of antenna element pairs, correlation-based models have lower computational complexity while the geometry-based stochastic models (GBSMs) can provide more accurate modeling of real radio propagation. This paper investigates several potential simplifications of the GBSM to reduce the complexity with minimal impact on accuracy. In addition, we develop a set of broadband metrics which enable a thorough investigation of the differences between the GBSMs and the simplified models. The impact of various random variables which are employed by the original GBSM on the system level simulation are also studied. Both simulation results and a measurement campaign show that complexity can be reduced significantly with a negligible loss of accuracy in the proposed metrics. As an example, in the presented scenarios, the computational time can be reduced by up to 57% while keeping the relative deviation of 5% outage capacity within 5%.

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