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Dynamic Time Switching for MIMO Wireless Information and Power Transfer

Authors
Kang, SeowooLee, HoonJang, SeokjuKim, HanjinLee, Inkyu
Issue Date
Jun-2019
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Wireless information and power transfer; MIMO; time switching; rate-energy region
Citation
IEEE TRANSACTIONS ON COMMUNICATIONS, v.67, no.6, pp.3978 - 3990
Indexed
SCIE
SCOPUS
Journal Title
IEEE TRANSACTIONS ON COMMUNICATIONS
Volume
67
Number
6
Start Page
3978
End Page
3990
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/65260
DOI
10.1109/TCOMM.2019.2899605
ISSN
0090-6778
Abstract
This paper studies simultaneous wireless information and power transfer (SWIPT) techniques for point-to-point multiple-input multiple-output channels, where a multi-antenna transmitter conveys information and energy at the same time to a multi-antenna receiver equipped with time switching (TS) circuits for an energy harvesting (EH) mode and an information decoding (ID) mode. Unlike conventional uniform TS (UTS) structure where all the receive antennas at the receiver employ a single TS circuit, in this paper, we propose a general dynamic TS (DTS) receiver architecture which has an individual TS circuit for each antenna. In the proposed DTS, the operation modes of the antennas can be dynamically changed to improve SWIPT performance. We aim to identify the achievable rate-energy (R-E) tradeoff of the DTS protocol for both linear and non-linear EH models by maximizing the information rate subject to the EH constraint. This results in joint optimization of the transmit covariance matrices and the time durations for the EH and the ID modes of the receive antennas, which is jointly non-convex in general. To tackle the non-convexity of the original problem, the successive convex approximation technique is adopted by addressing a series of approximated convex problems. As a result, efficient optimization algorithms are proposed for determining the boundary points of the achievable R-E region. We also provide a low-complexity algorithm which achieves near-optimal performance with much reduced complexity. Numerical results demonstrate that the proposed DTS presents significant performance gains over conventional UTS approaches.
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