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Enabling Secure Wireless Communications via Intelligent Reflecting Surfaces

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arxiv 1904.09573 v4 pith:XLYWNTOE submitted 2019-04-21 cs.IT math.IT

classification cs.ITmath.IT
keywords irsstransmitterwirelessalgorithmscommunicationsefficientenhancingintelligent
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In this paper, we propose to utilize intelligent reflecting surfaces (IRSs) for enhancing the physical layer security of wireless communications systems. In particular, an IRS-assisted secure wireless system is considered, where a multi-antenna transmitter communicates with a single-antenna receiver in the presence of an eavesdropper. To maximize the secrecy rate, both the beamformer at the transmitter and the IRS phase shifts are jointly optimized. Based on the block coordinate descent (BCD) and minorization maximization (MM) techniques, two efficient algorithms are developed to solve the resulting non-convex optimization problem for small- and large-scale IRSs, respectively. Simulation results show that IRSs can significantly improve physical layer security if the proposed algorithms are employed. Furthermore, we reveal that deploying large-scale IRSs is more efficient than enlarging the antenna array size of the transmitter for both boosting the secrecy rate and enhancing the energy efficiency.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

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

    eess.SP 2019-08 conditional novelty 5.0 of 10

    Joint optimization of BS precoding and IRS phase shifts for weighted sum rate maximization in SWIPT MIMO systems is solved by a convergent BCD algorithm, with simulations showing IRS expands the energy-harvesting range.

  2. Secure Transmission Strategy for Intelligent Reflecting Surface Enhanced Wireless System

    cs.IT 2019-09 conditional novelty 4.0 of 10

    For rank-one base station to reflecting surface channels, the optimal secrecy beamforming is the channel-matched vector, and phase design reduces to a hard quadratic problem solved by SDP or gradient methods.

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