Reduced complexity channel models for IMT-advanced evaluation

  • Authors:

  • Yu Zhang;Jianhua Zhang;Peter J. Smith;Mansoor Shafi;Ping Zhang

  • Affiliations:

  • Wireless Technology Innovation Institute, Beijing University of Posts and Telecommunications, Beijing, China;Wireless Technology Innovation Institute, Beijing University of Posts and Telecommunications, Beijing, China;Department of Electrical and Computer Engineering, University of Canterbury, Christchurch, New Zealand;Telecom New Zealand, Wellington, New Zealand;Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, China

  • Venue:
  • EURASIP Journal on Wireless Communications and Networking - Special issue on advances in propagation modelling for wireless systems
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

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%.