Robust Beamforming Design for Intelligent Reflecting Surface Aided MISO Communication Systems

Perfect channel state information (CSI) is challenging to obtain due to the limited signal processing capability at the intelligent reflection surface (IRS). This is the first work to study the worst-case robust beamforming design for an IRS-aided multiuser multiple-input single-output (MU-MISO) sys...

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Vydáno v:IEEE wireless communications letters Ročník 9; číslo 10; s. 1658 - 1662
Hlavní autoři: Zhou, Gui, Pan, Cunhua, Ren, Hong, Wang, Kezhi, Renzo, Marco Di, Nallanathan, Arumugam
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.10.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
IEEE comsoc
Témata:
Array signal processing
Beamforming
Channel state information
Communications systems
Engineering Sciences
imperfect channel state information (CSI)
Intelligent reflecting surface (IRS)
large intelligent surface (LIS)
MISO (control systems)
MISO communication
Optimization
Precoding
Quality of service
Reconfigurable intelligent surfaces
robust design
Robustness (mathematics)
semidefinite program (SDP)
Signal and Image processing
Signal processing
State (computer science)
Surface treatment
Uncertainty
imperfect channel state information (CSI)
robust design
semidefinite program (SDP)
Intelligent reflecting surface (IRS)
large intelligent surface (LIS)
ISSN:2162-2337, 2162-2345
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Shrnutí:Perfect channel state information (CSI) is challenging to obtain due to the limited signal processing capability at the intelligent reflection surface (IRS). This is the first work to study the worst-case robust beamforming design for an IRS-aided multiuser multiple-input single-output (MU-MISO) system under the assumption of imperfect CSI. We aim for minimizing the transmit power while ensuring that the achievable rate of each user meets the quality of service (QoS) requirement for all possible channel error realizations. With unit-modulus and rate constraints, this problem is non-convex. The imperfect CSI further increases the difficulty of solving this problem. By using approximation and transformation techniques, we convert the optimization problem into a squence of semidefinite program (SDP) subproblems that can be efficiently solved. Numerical results show that the proposed robust beamforming design can guarantee the required QoS targets for all the users.
Bibliografie:ObjectType-Article-1
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ISSN:2162-2337
2162-2345
DOI:10.1109/LWC.2020.3000490