Distributed spectrum management and relay selection in interference-limited cooperative wireless networks

  • Authors:
  • Zhangyu Guan;Tommaso Melodia;Dongfeng Yuan;Dimitris A. Pados

  • Affiliations:
  • Shandong University, Jinan, China;State University of New York at Buffalo, Buffalo, NY, USA;Shandong University, Jinan, China;State University of New York at Buffalo, Buffalo, NY, USA

  • Venue:
  • MobiCom '11 Proceedings of the 17th annual international conference on Mobile computing and networking
  • Year:
  • 2011

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Abstract

It is well known that the data transport capacity of a wireless network can be increased by leveraging the spatial and frequency diversity of the wireless transmission medium. This has motivated the recent surge of research in cooperative and dynamic-spectrum-access networks. Still, as of today, a key open research challenge is to design distributed control strategies to dynamically jointly assign (i) portions of the spectrum and (ii) cooperative relays to different traffic sessions to maximize the resulting network-wide data rate. In this article, we make a significant contribution in this direction. First, we mathematically formulate the problem of joint spectrum management and relay selection for a set of sessions concurrently utilizing an interference-limited infrastructure-less wireless network. We then study distributed solutions to this (nonlinear and nonconvex) problem. The overall problem is separated into two subproblems, (i) spectrum management through power allocation with given relay selection strategy, and (ii) relay selection for a given spectral profile. Distributed solutions for each of the two subproblems are proposed, which are then analyzed based on notions from variational inequality (VI) theory. The distributed algorithms can be proven to converge, under certain conditions, to VI solutions, which are also Nash equilibrium (NE) solutions of the equivalent NE problems. A distributed algorithm based on iterative solution of the two subproblems is then designed. Performance and price of anarchy of the distributed algorithm are then studied by comparing it to the globally optimal solution obtained with a centralized algorithm. Simulation results show that the proposed distributed algorithm achieves performance that is within a few percentage points of the optimal solution.