A Low-Complexity Solution for Optimizing Binary Intelligent Reflecting Surfaces towards Wireless Communication

Santosh A. Janawade, Prabu Krishnan (), Krishnamoorthy Kandasamy, Shashank S. Holla, Karthik Rao and Aditya Chandrasekar
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Santosh A. Janawade: Department of Electronics and Communication Engineering, National Institute of Technology Karnataka, Mangalore 575025, India
Prabu Krishnan: Department of Electronics and Communication Engineering, National Institute of Technology Karnataka, Mangalore 575025, India
Krishnamoorthy Kandasamy: Department of Electronics and Communication Engineering, National Institute of Technology Karnataka, Mangalore 575025, India
Shashank S. Holla: Department of Electronics and Communication Engineering, National Institute of Technology Karnataka, Mangalore 575025, India
Karthik Rao: Department of Electronics and Communication Engineering, National Institute of Technology Karnataka, Mangalore 575025, India
Aditya Chandrasekar: Department of Electrical and Electronics Engineering, National Institute of Technology Karnataka, Mangalore 575025, India

Future Internet, 2024, vol. 16, issue 8, 1-15

Abstract: Intelligent Reflecting Surfaces (IRSs) enable us to have a reconfigurable reflecting surface that can efficiently deflect the transmitted signal toward the receiver. The initial step in the IRS usually involves estimating the channel between a fixed transmitter and a stationary receiver. After estimating the channel, the problem of finding the most optimal IRS configuration is non-convex, and involves a huge search in the solution space. In this work, we propose a novel and customized technique which efficiently estimates the channel and configures the IRS with fixed transmit power, restricting the IRS coefficients to { 1 , − 1 } . The results from our approach are numerically compared with existing optimization techniques.The key features of the linear system model under consideration include a Reconfigurable Intelligent Surface (RIS) setup consisting of 4096 RIS elements arranged in a 64 × 64 element array; the distance from RIS to the access point measures 107 m. NLOS users are located around 40 m away from the RIS element and 100 m from the access point. The estimated variance of noise N C is 3.1614 × 10 − 20 . The proposed algorithm provides an overall data rate of 126.89 (MBits/s) for Line of Sight and 66.093 (MBits/s) for Non Line of Sight (NLOS) wireless communication.

Keywords: 5G/6G; wireless networks; smart systems; non line of sight (NLOS); programmable meta-surface; line of sight (LOS); intelligent reflecting surface (IRS); beamforming; orthogonal frequency division multiplexing (OFDM) (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2024
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