Reduced-Complexity Multicell Decoding Systems with Multiple Antennas at the Base Station

Chatzinotas, S., Imran, M. A. and Hoshyar, R. (2009) Reduced-Complexity Multicell Decoding Systems with Multiple Antennas at the Base Station. In: 2009 International Wireless Communications and Mobile Computing Conference (IWCMC '09), Leipzig, Germany, 21-24 Jun 2009, pp. 849-853. ISBN 9781605585697 (doi: 10.1145/1582379.1582564)

Abstract

Multicell joint decoding has been proven to greatly enhance the capacity of cellular systems in a range of regimes. However, the complexity of such a joint receiver makes it impossible to implement in practice using current computational capabilities. In this direction, this paper investigates the capacity performance of reduced-complexity communication schemes in order to evaluate their performance with respect to the optimal multicell joint decoding scheme. More specifically, two sub-optimal schemes are considered: 1) intra-cell user orthogonalization combined with optimal multicell joint decoding and 2) intra-cell user orthogonalization combined with linear MMSE filtering and single-user decoding. The employed cellular multiple-access channel model incorporates flat fading, path loss, distributed users and multiple antennas at the Base Station, while both peak and average transmit power constraints are taken into account. In this context, it is shown that linear MMSE filtering combined with multiple BS antennas and intra-cell orthogonalization can still provide a considerable capacity enhancement. Furthermore, FDMA is shown to be more efficient than TDMA as an intra-cell orthogonalization technique.

• Item Type: Conference Proceedings
• Additional Information: This research has been funded by the following Industrial Companies who are Members of Mobile VCE - BBC, BT, Huawei, Nokia, Nokia Siemens Networks, Nortel, Vodafone.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Imran, Professor Muhammad
• Authors: Chatzinotas, S., Imran, M. A., and Hoshyar, R.
• College/School: College of Science and Engineering > School of Engineering
• ISBN: 9781605585697