An adaptive geometry-based stochastic model for non-isotropic MIMO mobile-to-mobile channels

Authors:
Xiang Cheng;Cheng-Xiang Wang;David I. Laurenson;Sana Salous;Athanasios V. Vasilakos
Affiliations:
Joint Research Institute for Signal and Image Processing, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, UK;Joint Research Institute for Signal and Image Processing, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, UK;Joint Research Institute for Signal and Image Processing, School of Engineering and Electronics, The University of Edinburgh, Edinburgh, UK;Center for Communication Systems, School of Engineering, University of Durham, Durham, UK;Department of Computer and Telecommunications Engineering, University of Western Macedonia, Kozani, Greece
Venue:
IEEE Transactions on Wireless Communications
Year:
2009

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Abstract

In this paper, a generic and adaptive geometry-based stochastic model (GBSM) is proposed for non-isotropic multiple-inputmultiple-output (MIMO) mobile-to-mobile (M2M) Ricean fading channels. The proposed model employs a combined two-ring model and ellipse model, where the received signal is constructed as a sum of the line-of-sight, single-, and double-bounced rays with different energies. This makes the model sufficiently generic and adaptable to a variety of M2M scenarios (macro-, micro-, and pico-cells). More importantly, our model is the first GBSM that has the ability to study the impact of the vehicular traffic density on channel characteristics. From the proposed model, the space-time-frequency correlation function and the corresponding space-Doppler-frequency power spectral density (PSD) of any two sub-channels are derived for a non-isotropic scattering environment. Based on the detailed investigation of correlations and PSDs, some interesting observations and useful conclusions are obtained. These observations and conclusions can be considered as a guidance for setting important parameters of our model appropriately and building up more purposeful measurement campaigns in the future. Finally, close agreement is achieved between the theoretical results and measured data, demonstrating the utility of the proposed model.