Dynamic Time Switching for MIMO Wireless Information and Power Transfer
- Authors
- Kang, Seowoo; Lee, Hoon; Jang, Seokju; Kim, Hanjin; Lee, Inkyu
- Issue Date
- 6월-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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