Joint SINR-based link scheduling with max-min traffic delivery ratio in wireless multihop network systems

Ka Wai Gary WONG

Research output: Contribution to journalArticle


Link scheduling under the physical interference model has been an ongoing research problem in multihop wireless network systems. Yet, this issue has not been well addressed due to the difficulty of solving such problem. In this paper, our objective is to schedule each communication link where the minimal traffic delivery ratio at the destination in the multihop wireless network is maximised. The link scheduling optimisation problem is formulated as a power controlled rate adaptive scheduling problem (PRSP) using mixed integer non-linear programming (MINLP). We propose an iterative-based algorithm by enhancing the generalised Bender's decomposition (GBD) with node eliminations to reduce the complexity in the MINLP and solve it numerically. We prove that our enhanced GBD algorithm can generate a near-optimal solution for the MINLP. Based on the sub-optimal solution, we design a novel greedy power controlled scheduling algorithm for PRSP which can also generate a similar result in polynomial time complexity. Copyright © 2014 Inderscience Enterprises Ltd.
Original languageEnglish
Pages (from-to)191-211
JournalInternational Journal of Business and Systems Research
Issue number2
Early online dateApr 2014
Publication statusPublished - 2014


Wireless networks
Nonlinear programming
Scheduling algorithms
Telecommunication traffic
Telecommunication links
Benders decomposition
Optimal solution


Wong, G. K.-w. (2014). Joint SINR-based link scheduling with max-min traffic delivery ratio in wireless multihop network systems. International Journal of Business and Systems Research, 8(2), 191-211.


  • Cross-layer optimisation
  • Transmission link scheduling
  • Power control
  • Rate adaptation
  • Physical interference model
  • SINR
  • Signal-to-interference and noise ratio
  • Max-min traffic delivery ratio
  • Wireless networks
  • Multihop networks
  • Mixed integer nonlinear programming