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Mobile Networks and Applications

, Volume 15, Issue 5, pp 710–728 | Cite as

Opportunistic Fair Scheduling in Wireless Networks: An Approximate Dynamic Programming Approach

  • Zhi Zhang
  • Sudhir Moola
  • Edwin K. P. ChongEmail author
Article

Abstract

We consider the problem of temporal fair scheduling of queued data transmissions in wireless heterogeneous networks. We deal with both the throughput maximization problem and the delay minimization problem. Taking fairness constraints and the data arrival queues into consideration, we formulate the transmission scheduling problem as a Markov decision process (MDP) with fairness constraints. We study two categories of fairness constraints, namely temporal fairness and utilitarian fairness. We consider two criteria: infinite horizon expected total discounted reward and expected average reward. Applying the dynamic programming approach, we derive and prove explicit optimality equations for the above constrained MDPs, and give corresponding optimal fair scheduling policies based on those equations. A practical stochastic-approximation-type algorithm is applied to calculate the control parameters online in the policies. Furthermore, we develop a novel approximation method—temporal fair rollout—to achieve a tractable computation. Numerical results show that the proposed scheme achieves significant performance improvement for both throughput maximization and delay minimization problems compared with other existing schemes.

Keywords

approximate dynamic programming fairness Markov decision process resource allocation scheduling stochastic approximation wireless networks 

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringColorado State UniversityFt. CollinsUSA

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