Energy-efficient uplink resource allocation for IEEE 802.16j transparent-relay networks

  • Authors:
  • Jia-Ming Liang;You-Chiun Wang;Jen-Jee Chen;Jui-Hsiang Liu;Yu-Chee Tseng

  • Affiliations:
  • Department of Computer Science, National Chiao-Tung University, Hsin-Chu 30010, Taiwan;Department of Computer Science and Engineering, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan;Department of Electrical Engineering, National University of Tainan, Tainan 70005, Taiwan;Department of Computer Science, National Chiao-Tung University, Hsin-Chu 30010, Taiwan;Department of Computer Science, National Chiao-Tung University, Hsin-Chu 30010, Taiwan

  • Venue:
  • Computer Networks: The International Journal of Computer and Telecommunications Networking
  • Year:
  • 2011

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Abstract

The IEEE 802.16j standard is defined to enhance WiMAX networks with relay capacity. Under the transparent mode, existing studies only target improving network throughput by increasing the transmission rates of mobile stations (MSs) and maximizing concurrent transmissions. However, using a higher transmission rate or allowing more concurrent transmissions could harm MSs in terms of their energy consumption, especially when they are battery-powered. In this paper, we consider the energy-conserved resource allocation problem in the uplink direction of an IEEE 802.16j network under the transparent mode. This problem asks how to arrange the frame usage with satisfying MSs' demands as the constraint and minimizing their total energy consumption as the objective. We prove this problem to be NP-complete and develop two energy-efficient heuristics, called demand-first allocation (DFA) and energy-first allocation (EFA) schemes. These heuristics employ a gradient-like search method to approximate the optimal solution. Specifically, DFA tries to satisfy MSs' demands first by using as less frame space as possible. Then, with the remaining frame space, DFA tries to save MSs' energy by lowering their transmission rates or adjusting their transmission paths. Viewed from a different perspective, EFA first allocates the frame space to MSs to consume the least energy. Since the total allocation may exceed the frame space, EFA then exploits spatial reuse and rate adjustment to pack all demands into one frame. Simulation results show that our heuristics can approximate the ideal performance bounds and save up to 90% of MSs' energy as compared to existing results.