Integrated power controlled rate adaptation and medium access control in wireless mesh networks

  • Authors:
  • Kian Hedayati;Izhak Rubin;Arash Behzad

  • Affiliations:
  • Electrical Engineering Department, University of California, Los Angeles, CA;Electrical Engineering Department, University of California, Los Angeles, CA;Electrical Engineering Department, University of California, Los Angeles, CA

  • Venue:
  • IEEE Transactions on Wireless Communications
  • Year:
  • 2010

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Abstract

In this paper, a new mathematical programming model and assignment algorithms are developed for minimizing the schedule length in adaptive power and adaptive rate link scheduling in spatial-TDMA wireless networks. The underlying problem entails the optimal joint scheduling of transmissions across multi-access communication links combined with the simultaneous allocation of transmit power levels and data rates across active links, while meeting required Signal-to-Interferenceplus-Noise Ratio (SINR) levels at intended receivers. We prove that the problem can be modeled as a Mixed Integer-Linear Programming (MILP) and show that the latter yields a solution that consists of transmit power levels that are strongly Pareto Optimal. We note this problem to be NP-complete. For comparison purposes, we employ the MILP formulation for computing the optimal schedule for networks with small number of designated links and limited number of data rate levels. We proceed to develop and investigate a heuristic algorithm of polynomial complexity for solving the problem in a computationally effective manner. The algorithm is based on the construction of a Power Controlled Rate adaptation Interference Graph. The desired schedule is then derived by using a greedy algorithm to construct an independence set from this graph. Based on system analyses, we show, for smaller illustrative networks, the performance behavior realized by the heuristic algorithms to generally be in the 75 percentile of those attained by the optimal schedule. We also show that performance of our heuristic algorithm is on average 20% better than that attained under prior algorithms that were developed for use under fixed transmit power and fixed rate link scheduling.