A generic geometrical-based MIMO mobile-to-mobile channel model

Xiang Cheng, Cheng Xiang Wang, David I. Laurenson, Hsiao H. Ghent, Athanasios V. Vasilakos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)

Abstract

In this paper, a generic and adaptive geometrical-based stochastic reference model is proposed for multiple-input multiple-output (MIMO) mobile-to-mobile (M2M) Ricean fading channels. The proposed model employs a combined two-ring model and elliptical-ring model, where the received signal is constructed as a sum of the line-of-sight (LoS), single-, and double-bounced rays with different energies. This makes the model sufficiently generic and therefore includes many existing channel models as special cases. Importantly, the model can easily be adapted to a variety of M2M propagation environments, e.g., outdoor macro-, micro, and pico-cells taking into account different vehicle traffic densities, by adjusting model parameters. From the proposed model, the space-time (ST) correlation function (CF) and the corresponding space-Doppler (SD) power spectral density (PSD) of any two sub-channels are derived for a two-dimensional (2D) non-isotropic scattering environment. Finally, some numerical results are presented and compared with measured results. The close agreement between the theoretical and empirical curves verifies the utility of the proposed model. © 2008 IEEE.

Original languageEnglish
Title of host publicationIWCMC 2008 - International Wireless Communications and Mobile Computing Conference
Pages1000-1005
Number of pages6
DOIs
Publication statusPublished - 2008
EventInternational Wireless Communications and Mobile Computing Conference, IWCMC 2008 - Crete, Greece
Duration: 6 Aug 20088 Aug 2008

Conference

ConferenceInternational Wireless Communications and Mobile Computing Conference, IWCMC 2008
CountryGreece
CityCrete
Period6/08/088/08/08

Fingerprint Dive into the research topics of 'A generic geometrical-based MIMO mobile-to-mobile channel model'. Together they form a unique fingerprint.

Cite this