A characterization of max---min SIR-balanced power allocation with applications

  • Authors:

  • Sławomir Stańczak;Michał Kaliszan;Nicholas Bambos

  • Affiliations:

  • Fraunhofer German-Sino Lab for Mobile Communications, Berlin, Germany 10587;Fraunhofer German-Sino Lab for Mobile Communications, Berlin, Germany 10587;Department of Electrical Engineering, Stanford University, Stanford, USA 94305

  • Venue:
  • Wireless Networks
  • Year:
  • 2010

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Abstract

We consider a power-controlled wireless network with an established network topology in which the communication links (transmitter---receiver pairs) are corrupted by the co-channel interference and background noise. We have fairly general power constraints since the vector of transmit powers is confined to belong to an arbitrary convex polytope. The interference is completely determined by a so-called gain matrix. Assuming irreducibility of this gain matrix, we provide an elegant characterization of the max---min SIR-balanced power allocation under such general power constraints. This characterization gives rise to two types of algorithms for computing the max---min SIR-balanced power allocation. One of the algorithms is a utility-based power control algorithm to maximize a weighted sum of the utilities of the link SIRs. Our results show how to choose the weight vector and utility function so that the utility-based solution is equal to the solution of the max---min SIR-balancing problem. The algorithm is not amenable to distributed implementation as the weights are global variables. In order to mitigate the problem of computing the weight vector in distributed wireless networks, we point out a saddle point characterization of the Perron root of some extended gain matrices and discuss how this characterization can be used in the design of algorithms in which each link iteratively updates its weight vector in parallel to the power control recursion. Finally, the paper provides a basis for the development of distributed power control and beamforming algorithms to find a global solution of the max---min SIR-balancing problem.