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• [P155] Fairness Constrained Optimization of Channel Allocation for Open Spectrum Networks
  Author(s): Tao Zhang, Bin Wang, Zhiqiang Wu
  
  

  Abstract
  Channel allocation is an important area of research in open spectrum networks which asserts a significant impact on the spectrum utilization and the fairness among users. This paper studies the optimization of channel allocation, considering multiple objectives. For each objective, a binary programming model is described. Then a new optimization objective called fairness constrained maximum throughput is proposed. To achieve this optimization objective, a unified binary linear programming (UBLP) model is constructed which is then solved by the simplex method and branch-and-bound search. The solution to this model satisfies a bandwidth requirement for each user, e.g., the bandwidth for each user is equal to or larger than a per-user bandwidth minimum, and the solution also maximizes the network throughput. We prove that given different per-user bandwidth minimum, the optimal solution to the UBLP model achieves specific optimization objectives, such as the maximum network throughput and the max-min fairness. For the proportional fairness objective, the solution to the UBLP model proves to be within a bound of the optimal solution.

  
   

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