We consider a multiple-input single-output wireless powered communication network (WPCN), where the single-Antenna users harvest energy from a multi-Antenna access point (AP) and then transmit information back to the AP. With multiple antennas, the AP can perform energy beamforming in the downlink and exploit multiplexing-or (receive) beamforming-gain in the uplink. We consider maximizing the sum of the users' energy efficiencies (EEs) by jointly optimizing the energy beamforming of the AP, transmit powers of the users, and time allocation. We formulate EE maximization problems for both TDMA-based WPCN (T-WPCN) and SDMA-based WPCN (S-WPCN), which are non-convex because they have the sum-of-ratios objective functions. We optimally solve the former by reformulating it into an equivalent parametric problem, whose solution can be obtained by iteratively solving convex problems, while the latter is optimally solved by convexifying it using the so-called feasible set reduction scheme. We show that the T-WPCN outperforms S-WPCN when there is no minimum throughput requirement, while we can observe that the S-WPCN outperforms T-WPCN when minimum throughput requirement is high. The simulation results verify our theoretical findings and demonstrate the effectiveness of our proposed schemes.
Bibliographical noteFunding Information:
Manuscript received September 7, 2017; revised January 21, 2018, May 2, 2018, July 31, 2018 and October 16, 2018; accepted November 27, 2018. Date of publication December 18, 2018; date of current version February 11, 2019. This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education under Grant 2016R1D1A1A09916968. The associate editor coordinating the review of this paper and approving it for publication was L. Dai. (Corresponding author: Taewon Hwang.) The authors are with the School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, South Korea (e-mail: huleem7@yonsei. ac.kr; firstname.lastname@example.org).
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All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Electrical and Electronic Engineering
- Applied Mathematics