Joint random access and power selection for maximal throughput in wireless networks

  • Authors:
  • Yan Gao;Zheng Zeng;P. R. Kumar

  • Affiliations:
  • Department of Computer Science, and CSL, University of Illinois at Urbana-Champaign;Department of Computer Science, and CSL, University of Illinois at Urbana-Champaign;Department of Electrical and Computer Engineering, and CSL, University of Illinois at Urbana-Champaign

  • Venue:
  • INFOCOM'10 Proceedings of the 29th conference on Information communications
  • Year:
  • 2010

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Abstract

In wireless networks, how to select transmit power that maximizes throughput is a challenging problem. On one hand, transmissions at a high power level could increase interference to others; on the other hand, transmissions at a low power level are prone to being interfered by others. Prior works consider this problem as a search for a fixed optimal power setting that maximizes communication spatial reuse. In this paper, we pursue a novel approach that combines power selection with a random medium access mechanism. For each transmission, a node randomly selects a transmit power from all available power levels to access the medium. In this way, all combinations of network power settings could be selected with some probability. Using a recently developed Markov chain model, we derive a distributed scheme that determines the access probabilities of each power setting, according to the arrival rate of traffic and the service rate achieved by the scheme. We show that this scheme always converges to the optimal solution. Moreover, we also show that the random scheme can attain the maximal throughput region that can be obtained by any time-sharing between power settings, and which is consequently larger than the region any fixed power setting can achieve.