Modeling and Performance Evaluation of dual polarized MIMO Land Mobile Satellite Channels | ||
| The International Conference on Electrical Engineering | ||
| Article 2, Volume 9, 9th International Conference on Electrical Engineering ICEENG 2014, May 2014, Pages 1-17 PDF (1.49 M) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/iceeng.2014.30355 | ||
| Authors | ||
| Gamal Mabrouk Abdelhamid1; Gamal Hamad1; Yasser Kamel Badran2 | ||
| 1Military Technical Collage. | ||
| 2Egyptian Armed Forces. | ||
| Abstract | ||
| The paper is concerned with generating of narrow-band dual polarized Multi Input Multi Output (MIMO) over land Mobile Satellite (LMS) fading channels. In the absence of accurate experimental results of MIMO-LMS channels, a statistical model for the characterization of MIMO-LMS is proposed based on available experimental results for Single Input Single output (SISO) LMS and MIMO wireless channels as well as on their extrapolation to the MIMO-LMS case of interest. In this paper a step-bystep methodology for transforming SISO model (Loo model) to MIMO model with detailed description and block diagrams for the simulation and time series signal generation for MIMO-LMS, with the desired power, probability distribution, covariance relations and spectrum. Moreover, based on the proposed channel model, the channel capacity statistics as well as the error performance of a SIMO-LMS diversity system, assuming both maximal ratio combining (MRC) and selection combining (SC), and MIMO-LMS using Space-Time Block Code are evaluated through simulations. Useful numerical results on the capacity are also provided taking into account several operational system parameters. The simulation model and results are useful for LMS-MIMO physical layer researches and system designer, who need an easy to implement and realizable model, representative of typical MIMO-LMS communication systems. | ||
| Keywords | ||
| Fading channels; Land Mobile Satellite (LMS); Multiple- Input Multiple-Output (MIMO); and Polarization Diversity Statistical Modeling | ||
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