This article is part of the series Fairness in Radio Resource Management for Wireless Networks.

Open Access Research Article

Throughput versus Fairness: Channel-Aware Scheduling in Multiple Antenna Downlink

EduardA Jorswieck1*, Aydin Sezgin2 and Xi Zhang3

Author Affiliations

1 Communications Laboratory, Faculty of Electrical Engineering and Information Technology, Dresden University of Technology, D-01062 Dresden, Germany

2 Department of Electrical Engineering & Computer Science, Henry Samueli School of Engineering, University of California, Irvine, CA 92697, USA

3 ACCESS Linnaeus Center, Royal Institute of Technology, SE-100 44 Stockholm, Sweden

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EURASIP Journal on Wireless Communications and Networking 2009, 2009:271540  doi:10.1155/2009/271540


The electronic version of this article is the complete one and can be found online at: http://jwcn.eurasipjournals.com/content/2009/1/271540


Received:1 July 2008
Accepted:23 December 2008
Published:2 February 2009

© 2009 The Author(s).

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Channel aware and opportunistic scheduling algorithms exploit the channel knowledge and fading to increase the average throughput. Alternatively, each user could be served equally in order to maximize fairness. Obviously, there is a tradeoff between average throughput and fairness in the system. In this paper, we study four representative schedulers, namely the maximum throughput scheduler (MTS), the proportional fair scheduler (PFS), the (relative) opportunistic round robin scheduler (ORS), and the round robin scheduler (RRS) for a space-time coded multiple antenna downlink system. The system applies TDMA based scheduling and exploits the multiple antennas in terms of spatial diversity. We show that the average sum rate performance and the average worst-case delay depend strongly on the user distribution within the cell. MTS gains from asymmetrical distributed users whereas the other three schedulers suffer. On the other hand, the average fairness of MTS and PFS decreases with asymmetrical user distribution. The key contribution of this paper is to put these tradeoffs and observations on a solid theoretical basis. Both the PFS and the ORS provide a reasonable performance in terms of throughput and fairness. However, PFS outperforms ORS for symmetrical user distributions, whereas ORS outperforms PFS for asymmetrical user distribution.

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