Reference : Robust Probabilistic-Constrained Optimization for IRS-Aided MISO Communication Systems
Scientific journals : Article
Engineering, computing & technology : Electrical & electronics engineering
Security, Reliability and Trust
http://hdl.handle.net/10993/44418
Robust Probabilistic-Constrained Optimization for IRS-Aided MISO Communication Systems
English
Le, Anh Tuan mailto [The Department of Design Engineering & Mathematics, Faculty of Science and Technology, Middlesex University, London, U. K.]
Trinh, van Chien mailto [University of Luxembourg > > >]
Di Renzo, Marco mailto [Université Paris-Saclay, CNRS, CentraleSupélec, Laboratoire des Signaux et Systèmes, 91192 Gif-sur-Yvette, France]
14-Aug-2020
IEEE Wireless Communications Letters
IEEE Communications Society
Yes (verified by ORBilu)
International
2162-2337
2162-2345
Piscataway
NJ
[en] 6G wireless ; intelligent reflecting surface
[en] Taking into account imperfect channel state information, this letter formulates and solves a joint active/passive beamforming optimization problem in multiple-input single-output systems with the support of an intelligent reflecting surface. In particular, we introduce an optimization problem to minimize the total transmit power subject to maintaining the users' signal-to-interference-plus-noise-ratio coverage probability above a predefined target. Due to the presence of probabilistic constraints, the proposed optimization problem is non-convex. To circumvent this issue, we first recast the proposed problem in a convex form by adopting the Bernstein-type inequality, and we then introduce a converging alternating optimization approach to iteratively find the active/passive beamforming vectors. In particular, the transformed robust optimization problem can be effectively solved by using standard interior-point methods. Numerical results demonstrate the effectiveness of jointly optimizing the active/passive beamforming vectors.
http://hdl.handle.net/10993/44418

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