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Volume 41 Issue 6
Jun.  2019
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Miao CUI, Xin YU, Xueyi LI, Guangchi ZHANG, Yijun LIU. Joint Downlink and Uplink Resource Allocation for Multi-user Multi-carrier Simultaneous Wireless Information and Power Transfer Systems[J]. Journal of Electronics & Information Technology, 2019, 41(6): 1359-1364. doi: 10.11999/JEIT180762
Citation: Miao CUI, Xin YU, Xueyi LI, Guangchi ZHANG, Yijun LIU. Joint Downlink and Uplink Resource Allocation for Multi-user Multi-carrier Simultaneous Wireless Information and Power Transfer Systems[J]. Journal of Electronics & Information Technology, 2019, 41(6): 1359-1364. doi: 10.11999/JEIT180762

Joint Downlink and Uplink Resource Allocation for Multi-user Multi-carrier Simultaneous Wireless Information and Power Transfer Systems

doi: 10.11999/JEIT180762
Funds:  The National Natural Science Foundation of China (61571138), The Science and Technology Project of Guangdong Province (2017B090909006, 2016B090904001, 2016B090918031, 2018A050506015), The Science and Technology Project of Guangzhou City (201803030028)
  • Received Date: 2018-08-03
  • Rev Recd Date: 2019-03-05
  • Available Online: 2019-03-28
  • Publish Date: 2019-06-01
  • Simultaneous Wireless Information and Power Transfer (SWIPT) is an effective technique to solve the energy limitation problem of wireless networks. A multi-carrier SWIPT communication system that includes one Base Station (BS) and multiple users is investigated. Both the uplink and downlink of the system apply the OFDM transmission. In the downlink, the BS transmits information and power over different subcarriers to the users simultaneously. In the uplink, the user transmits information to the BS by using the power harvested from the BS in the downlink. This paper aims to maximize the weighted sum of the downlink and uplink achievable rates by jointly optimizing subcarrier allocation and power allocation of the uplink and downlink. An optimal algorithm is proposed to solve this resulted optimization problem, which is based on the Lagrange duality method and the ellipsoid method. The performances of the proposed algorithm are verified by computer simulations.
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