An iterative water-filling algorithm for maximum weighted sum-rate of Gaussian MIMO-BC

We consider the maximization of weighted rate sum in Gaussian multiple-input-multiple-output broadcast channels. This problem is motivated by optimal adaptive resource allocation policies in wireless systems with multiple antenna at the base station. In fact, under random packet arrival and transmis...

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Bibliographic Details
Published inIEEE journal on selected areas in communications Vol. 24; no. 8; pp. 1640 - 1646
Main Authors Kobayashi, M., Caire, G.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.08.2006
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Adaptive arrays
Algorithms
Antennas
Base stations
Broadcasting
Convergence
Convex optimization
Downlink
Gaussian
Iterative algorithms
Maximization
MIMO
Queues
Resource allocation
Resource management
Stability
Stations
Transmitters
Transmitting antennas
uplink-downlink duality
weighted rate sum
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Summary:We consider the maximization of weighted rate sum in Gaussian multiple-input-multiple-output broadcast channels. This problem is motivated by optimal adaptive resource allocation policies in wireless systems with multiple antenna at the base station. In fact, under random packet arrival and transmission queues, the system stability region is achieved by maximizing a weighted rate sum with suitable weights that depend on the queue buffer sizes. Our algorithm is a generalization of the well-known Iterative Multiuser Water-Filling that maximizes the rate sum under a total transmit power constraint and inherits from the latter its simplicity. We propose also a variation on the basic algorithm that makes convergence speed very fast and essentially independent of the number of users
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ISSN:0733-8716
1558-0008
DOI:10.1109/JSAC.2006.879410