Publication

Sie verwenden einen Browser, in dem JavaScript deaktiviert ist. Dadurch wird verhindert, dass Sie die volle Funktionalität dieser Webseite nutzen können. Zur Navigation müssen Sie daher die Sitemap nutzen.

You are currently using a browser with deactivated JavaScript. There you can't use all the features of this website. In order to navigate the site, please use the Sitemap .

Modeling and Performance Evaluation for Mobile Ricean MIMO Channels

Authors:
Ispas, A. ,  Hoelscher, J. ,  Gong, X. ,  Schneider, C. ,  Ascheid, G. ,  Thomä, R.
Book Title:
Proc. IEEE Int. Conf. Commun. (ICC)
Organization:
IEEE
Address:
Ottawa, Canada
Date:
Jun. 2012
DOI:
10.1109/ICC.2012.6363749
Language:
English

Abstract

We propose a general channel model for mobile Ricean multiple-input multiple-output (MIMO) channels, which is characterized by parameters that are readily obtainable from measurements. To this end, a moment-based channel decomposition is derived. For the case of statistical channel state information (CSI) at the transmitter (TX) and instantaneous CSI at the receiver, we derive an approximation of the achievable rate, i.e., the mutual information (MI), which is only a function of the channel parameters of the proposed channel model and thus gives insight into the parameters that influence the MI. Finally, we evaluate the MI for a 4x4 MIMO system based on channel measurements at 2.53 GHz for two low-complexity TX strategies, i.e., a beamforming (BF) and a spatial multiplexing (SM) strategy. We find that the proposed channel model and the approximate evaluation of the MI are both accurate for realistic signal-to-noise ratio (SNR) values. The approximate evaluation is able to reproduce crossing points between the MI of the considered TX strategies; it thus reflects the SNR at which one should switch from the BF to the SM strategy.

Download

BibTeX

Copyright © by IEEE
Ispas_2012_ICC.pdf
© 2021 IEEE.Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.