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Conference Papers Year : 2018

Heuristic approach for forecast scheduling

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Hind Zaaraoui
  • Function : Author
  • PersonId : 974187
Zwi Altman
  • Function : Author
  • PersonId : 872996
Eitan Altman
  • Function : Author
  • PersonId : 830042
Tania Jimenez

Abstract

Forecast Scheduling (FS) is a scheduling concept that utilizes rate prediction along the users' trajectories in order to optimize the scheduler allocation. The rate prediction is based on Signal to Interference plus Noise Ratio (SINR) or rate maps provided by a Radio Environment Map (REM). The FS has been formulated as a convex optimization problem namely the maximization of an α−fair utility function of the cumulated rates of the users along their trajectories [1]. This paper proposes a fast heuristic for the FS problem based on two FS users' scheduling. Furthermore, it is shown that in the case of two users, the FS problem can be solved analytically, making the heuristic computationally very efficient. Numerical results illustrate the throughput gain brought about by the scheduling solution.
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Dates and versions

hal-01705829 , version 1 (09-02-2018)

Identifiers

  • HAL Id : hal-01705829 , version 1

Cite

Hind Zaaraoui, Zwi Altman, Sana Ben Jemaa, Eitan Altman, Tania Jimenez. Heuristic approach for forecast scheduling. IWSON 2018 - 7th International Workshop on Self-Organizing Networks, Apr 2018, Barcelona, Spain. pp.1-6. ⟨hal-01705829⟩
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