• DocumentCode
    1789484
  • Title

    Multiple resource allocation in OFDMA downlink networks: End-to-end energy-efficient approach

  • Author

    Quansheng Xu ; Xi Li ; Hong Ji

  • Author_Institution
    Key Lab. of Universal Wireless Commun., Beijing Univ. of Posts & Telecommun., Beijing, China
  • fYear
    2014
  • fDate
    10-14 June 2014
  • Firstpage
    3957
  • Lastpage
    3962
  • Abstract
    For energy-efficient (EE) resource allocation, only limited work has considered end-to-end energy consumption. In this paper, a novel EE resource allocation algorithm is proposed for orthogonal frequency division multiple access (OFDMA) downlink networks, where both transmitter energy consumption (base station (BS) transmission and BS circuit energy consumption) and receiver energy consumption (user equipment (UE) circuit energy consumption) are taken into account. The time slot, subchannel (frequency) and power allocation policies are joint considered to optimize system energy efficiency. In addition, different quality of service (QoS) requirements including minimum-rate guarantee service and best effort service are supported in our considering system. With all these considerations, the EE resource allocation problem is formulated as a mixed combinatorial and non-convex optimization problem, which is extremely difficult to solve. To obtain a desirable solution with a reasonable computation cost, an algorithm based on quantum-behaved particle swarm optimization (QPSO) is proposed. Finally, extensive simulation results are presented to validate the effectiveness of the proposed algorithm.
  • Keywords
    OFDM modulation; energy conservation; frequency division multiple access; particle swarm optimisation; power consumption; quality of service; radio receivers; radio transmitters; resource allocation; telecommunication power management; OFDMA downlink networks; QPSO; QoS; base station circuit; base station transmission; end-to-end energy consumption; end-to-end energy-efficient approach; energy-efficient resource allocation; minimum-rate guarantee service; mixed combinatorial problem; multiple resource allocation; nonconvex optimization problem; orthogonal frequency division multiple access; power allocation policy; quality of service; quantum-behaved particle swarm optimization; receiver energy consumption; subchannel frequency; time slot; transmitter energy consumption; user equipment; Algorithm design and analysis; Convergence; Energy consumption; OFDM; Optimization; Resource management; Signal processing algorithms; Energy efficiency; OFDMA; quantum-behaved particle swarm optimization; resource allocation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications (ICC), 2014 IEEE International Conference on
  • Conference_Location
    Sydney, NSW
  • Type

    conf

  • DOI
    10.1109/ICC.2014.6883939
  • Filename
    6883939