Energy Efficient SWIPT Systems in Multi-Cell MISO Networks

Seokju Jang, Hoon Lee, Seowoo Kang, Taeseok Oh, Inkyu Lee

Research output: Contribution to journalArticlepeer-review

34 Citations (Scopus)


This paper studies beamforming design problems for multi-cell multi-user downlink networks with simultaneous wireless information and power transfer (SWIPT). In this system, multi-antenna base stations (BSs) concurrently transfer information and energy to multiple single-antenna information decoding (ID) and energy-harvesting (EH) users. We aim to maximize EH efficiency (EHE) that is defined as the ratio of the harvested energy at the EH users to the amount of energy consumption at the BSs while guaranteeing the quality-of-service constraint for each ID user. The EHE metric quantifies the efficiency of the power transfer capability of the SWIPT network. For the EH operation, both an ideal linear model and a practical non-linear model are individually investigated. We optimally solve this non-convex problem in two different scenarios according to the cooperation level among the BSs. First, for the centralized case, where global channel state information (CSI) is available at all BSs, we propose a centralized beamforming method based on the semi-definite relaxation and the successive convex approximation techniques. Next, in order to reduce the backhaul signaling overhead, decentralized algorithms are presented where each BS computes its beamforming vector by only using local CSI. The simulation results show that the proposed SWIPT beamforming algorithms offer a significant EHE performance gain over conventional schemes.

Original languageEnglish
Article number8493519
Pages (from-to)8180-8194
Number of pages15
JournalIEEE Transactions on Wireless Communications
Issue number12
Publication statusPublished - 2018 Dec

Bibliographical note

Publisher Copyright:
© 2018 IEEE.


  • Energy efficiency
  • multi-cell coordination
  • simultaneous wireless information and power transfer (SWIPT)

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics


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