4.7 Article

Double Intelligent Reflecting Surface for Secure Transmission With Inter-Surface Signal Reflection

Journal

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume 70, Issue 3, Pages 2912-2916

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2021.3062059

Keywords

Optimization; Manifolds; Wireless communication; MISO communication; Transmitters; Linear programming; Convergence; Alternating optimization; intelligent reflecting surface; inter-surface signal reflection; product Riemmanian manifold; secrecy rate

Funding

  1. National Natural Science Foundation of China [61941118, 61941105]
  2. Innovation Team Research Fund of Shaanxi Province [2019TD-013]

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This study uses double intelligent reflecting surfaces (IRS) to enhance the secrecy performance of wireless transmission, and proposes an algorithm to jointly optimize the beamformer at transmitter and phase shift coefficients at double IRS for channel optimization, showing significant advantages in secrecy rate optimization.
In this correspondence, we use double intelligent reflecting surface (IRS) assisted design to enhance the secrecy performance of wireless transmission. Different from the existing studies in the literature, the inter-surface signal reflection is considered in this work, which makes the formulated secrecy rate (SR) optimization problem difficult to tackle. In particular, to solve this problem, we propose a product Riemmanian manifold (PRM) based alternating optimization (AO) algorithm to jointly optimize the beamformer at transmitter as well as phase shift coefficients at double IRS, in which the PRM optimization algorithm is applied to optimize the phase shift coefficients at both IRSs simultaneously. Simulation results show that the proposed algorithm greatly enhance the SR compared with the existing benchmark schemes. And compared with conventional semi-definite relaxation based AO algorithm, the proposed PRM based AO algorithm can achieve much lower computational complexity as well as faster speed of convergence.

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