Computer Science > Information Theory
[Submitted on 14 Apr 2010 (v1), last revised 4 Feb 2014 (this version, v3)]
Title:Duality, Polite Water-filling, and Optimization for MIMO B-MAC Interference Networks and iTree Networks
View PDFAbstract:This paper gives the long sought network version of water-filling named as polite water-filling. Unlike in single-user MIMO channels, where no one uses general purpose optimization algorithms in place of the simple and optimal water-filling for transmitter optimization, the traditional water-filling is generally far from optimal in networks as simple as MIMO multiaccess channels (MAC) and broadcast channels (BC), where steepest ascent algorithms have been used except for the sum-rate optimization. This is changed by the polite water-filling that is optimal for all boundary points of the capacity regions of MAC and BC and for all boundary points of a set of achievable regions of a more general class of MIMO B-MAC interference networks, which is a combination of multiple interfering broadcast channels, from the transmitter point of view, and multiaccess channels, from the receiver point of view, including MAC, BC, interference channels, X networks, and most practical wireless networks as special case. It is polite because it strikes an optimal balance between reducing interference to others and maximizing a link's own rate. Employing it, the related optimizations can be vastly simplified by taking advantage of the structure of the problems. Deeply connected to the polite water-filling, the rate duality is extended to the forward and reverse links of the B-MAC networks. As a demonstration, weighted sum-rate maximization algorithms based on polite water-filling and duality with superior performance and low complexity are designed for B-MAC networks and are analyzed for Interference Tree (iTree) Networks, a sub-class of the B-MAC networks that possesses promising properties for further information theoretic study.
Submission history
From: An Liu Dr [view email][v1] Wed, 14 Apr 2010 19:48:30 UTC (156 KB)
[v2] Sat, 1 May 2010 21:32:20 UTC (159 KB)
[v3] Tue, 4 Feb 2014 13:50:55 UTC (151 KB)
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