Intelligent Reflecting Surface Aided MIMO Broadcasting for Simultaneous Wireless Information and Power Transfer

An intelligent reflecting surface (IRS) is invoked for enhancing the energy harvesting performance of a simultaneous wireless information and power transfer (SWIPT) aided system. Specifically, an IRS-assisted SWIPT system is considered, where a multi-antenna aided base station (BS) communicates with...

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Veröffentlicht in:IEEE journal on selected areas in communications Jg. 38; H. 8; S. 1719 - 1734
Hauptverfasser: Pan, Cunhua, Ren, Hong, Wang, Kezhi, Elkashlan, Maged, Nallanathan, Arumugam, Wang, Jiangzhou, Hanzo, Lajos
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.08.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Antennas
Array signal processing
Computer simulation
Convergence
Decoupling
Energy harvesting
Erbium
Feasibility studies
Intelligent reflecting surface (IRS)
Iterative algorithms
Iterative methods
large intelligent surface (LIS)
MIMO
MIMO (control systems)
MIMO communication
Optimization
Phase shift
Power transfer
Receivers
Receivers & amplifiers
Reconfigurable intelligent surfaces
SWIPT
Wireless communication
ISSN:0733-8716, 1558-0008
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Zusammenfassung:An intelligent reflecting surface (IRS) is invoked for enhancing the energy harvesting performance of a simultaneous wireless information and power transfer (SWIPT) aided system. Specifically, an IRS-assisted SWIPT system is considered, where a multi-antenna aided base station (BS) communicates with several multi-antenna assisted information receivers (IRs), while guaranteeing the energy harvesting requirement of the energy receivers (ERs). To maximize the weighted sum rate (WSR) of IRs, the transmit precoding (TPC) matrices of the BS and passive phase shift matrix of the IRS should be jointly optimized. To tackle this challenging optimization problem, we first adopt the classic block coordinate descent (BCD) algorithm for decoupling the original optimization problem into several subproblems and alternately optimize the TPC matrices and the phase shift matrix. For each subproblem, we provide a low-complexity iterative algorithm, which is guaranteed to converge to the Karush-Kuhn-Tucker (KKT) point of each subproblem. The BCD algorithm is rigorously proved to converge to the KKT point of the original problem. We also conceive a feasibility checking method to study its feasibility. Our extensive simulation results confirm that employing IRSs in SWIPT beneficially enhances the system performance and the proposed BCD algorithm converges rapidly, which is appealing for practical applications.
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ISSN:0733-8716
1558-0008
DOI:10.1109/JSAC.2020.3000802