Power allocation and admission control in multiuser relay networks via convex programming: centralized and distributed schemes

Authors:
Khoa T. Phan;Long Bao Le;Sergiy A. Vorobyov;Tho Le-Ngoc
Affiliations:
Department of Electrical Engineering, California Institute of Technology, Pasadena, CA;Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA;Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada;Department of Electrical and Computer Engineering, McGill University, Montreal, QC, Canada
Venue:
EURASIP Journal on Wireless Communications and Networking - Special issue on optimization techniques in wireless communications
Year:
2009

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Abstract

The power allocation problem for multiuser wireless networks is considered under the assumption of amplify-and-forward cooperative diversity. Specifically, optimal centralized and distributed power allocation strategies with and without minimum rate requirements are proposed. We make the following contributions. First, power allocation strategies are developed to maximize either (i) the minimum rate among all users or (ii) the weighted-sum of rates. These two strategies achieve different throughput and fairness tradeoffs which can be chosen by network operators depending on their offering services. Second, the distributed implementation of the weighted-sum of rates maximization-based power allocation is proposed. Third, we consider the case when the requesting users have minimum rate requirements, which may not be all satisfied due to the limited-power relays. Consequently, admission control is needed to select the number of users for further optimal power allocation. As such a joint optimal admission control and power allocation problem is combinatorially hard, a heuristic-based suboptimal algorithm with significantly reduced complexity and remarkably good performance is developed. Numerical results demonstrate the effectiveness of the proposed approaches and reveal interesting throughput-fairness tradeoff in resource allocation.