中国邮电高校学报(英文) ›› 2015, Vol. 22 ›› Issue (2): 24-30.doi: 10.1016/S1005-8885(15)60635-5

• Wireless • 上一篇    下一篇

End-to-end energy-efficient resource allocation in device-to-device communication underlaying cellular networks

徐全盛1,纪红2,李曦1,熊丹妮1   

  1. 1. 北京邮电大学
    2. 北邮199信箱
  • 收稿日期:2014-07-11 修回日期:2014-09-26 出版日期:2015-04-30 发布日期:2015-04-22
  • 通讯作者: 李曦 E-mail:lixi@bupt.edu.cn

End-to-end energy-efficient resource allocation in device-to-device communication underlaying cellular networks

  • Received:2014-07-11 Revised:2014-09-26 Online:2015-04-30 Published:2015-04-22
  • Contact: Xi LI E-mail:lixi@bupt.edu.cn

摘要: A proposed resource allocation (RA) scheme is given to device-to-device (D2D) communication underlaying cellular networks from an end-to-end energy-efficient perspective, in which, the end-to-end energy consumptions were taken into account. Furthermore, to match the practical situations and maximize the energy-efficiency (EE), the resource units (RUs) were used in a complete-shared pattern. Then the energy-efficient RA problem was formulated as a mixed integer and non-convex optimization problem, extremely difficult to be solved. To obtain a desirable solution with a reasonable computation cost, this problem was dealt with two steps. Step 1, the RU allocation policy was obtained via a greedy search method. Step 2, after obtaining the RU allocation, the power allocation strategy was developed through quantum-behaved particle swarm optimization (QPSO). Finally, simulation was presented to validate the effectiveness of the proposed RA scheme.

关键词: energy-efficiency, resource allocation, D2D communication, mixed integer and non-convex optimization problem

Abstract: A proposed resource allocation (RA) scheme is given to device-to-device (D2D) communication underlaying cellular networks from an end-to-end energy-efficient perspective, in which, the end-to-end energy consumptions were taken into account. Furthermore, to match the practical situations and maximize the energy-efficiency (EE), the resource units (RUs) were used in a complete-shared pattern. Then the energy-efficient RA problem was formulated as a mixed integer and non-convex optimization problem, extremely difficult to be solved. To obtain a desirable solution with a reasonable computation cost, this problem was dealt with two steps. Step 1, the RU allocation policy was obtained via a greedy search method. Step 2, after obtaining the RU allocation, the power allocation strategy was developed through quantum-behaved particle swarm optimization (QPSO). Finally, simulation was presented to validate the effectiveness of the proposed RA scheme.

Key words: energy-efficiency, resource allocation, D2D communication, mixed integer and non-convex optimization problem

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