NDLI: Optimal downlink space-time scheduling design with convex utility functions - multiple antenna systems with orthogonal transmit beamforming

Content Provider	IEEE Xplore Digital Library
Author	Lau, V.K.N.
Copyright Year	2004
Description	Author affiliation: Lucent Technol., Bell Labs., Whippany, NJ, USA (Lau, V.K.N.)
Abstract	We consider the optimal downlink MISO scheduling design framework for a general class of convex utility functions. The access point or base station is equipped with n/sub T/ transmit antennas. There are K mobiles in the system with single receive antenna. For practical reasons, we constraint the physical/link layer of the base station and mobile devices to linear processing complexity in signal transmission/reception respectively. We shall apply the design framework to two common utility functions, namely the maximum throughput and the proportional fair. The scheduling problem is a mixed nonlinear integer programming problem and therefore, the complexity of the optimal solution is enormous. Greedy algorithms is widely used in today's wireless data systems (3GIX, HDR, UMTS) and is optimal when n/sub T/ = 1. However, we found that there is a large performance penalty of greedy algorithms (relative to optimal performance) when n/sub T/ > 1 and this motivates the search for more efficient heuristics. In this paper, we address genetic-based heuristics and discuss their complexity-performance tradeoff.
Starting Page	3040
Ending Page	3045
File Size	330216
Page Count	6
File Format	PDF
ISBN	0780385330
DOI	10.1109/ICC.2004.1313090
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-06-20
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Downlink Transmitting antennas Array signal processing Femtocell networks Greedy algorithms Receiving antennas Signal processing Throughput Linear programming Data systems
Content Type	Text
Resource Type	Article

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