Low-Complexity Tensor-Based Monostatic Sensing for IRS-Assisted Communication Systems

This paper proposes a tensor-based parameter estimation algorithm for sensing in an intelligent reflecting surface-assisted system. We present a higher-order singular value decomposition-based solution that exploits the tensor structure of the received echo signal to jointly estimate the target'...

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Bibliographic Details
Main Authors: Benicio, Kenneth B. A., Sokal, Bruno, de Almeida, Andre L. F., Fazal-E-Asim, Makki, Behrooz, Fodor, Gabor
Format: Conference Proceeding
Language:English
Subjects:
complexity analysis
Delays
Estimation
higher-order singular value decomposition
Intelligent reflecting surfaces
monostatic sensing
Parameter estimation
Sensors
Simulation
tensor-based sensing
Tensors
Wireless communication
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Summary:This paper proposes a tensor-based parameter estimation algorithm for sensing in an intelligent reflecting surface-assisted system. We present a higher-order singular value decomposition-based solution that exploits the tensor structure of the received echo signal to jointly estimate the target's delay, Doppler, and angular information. Our tensor-based solution can estimate the parameters individually at low complexity, benefiting from parallel computation. Complexity analysis is carried out in comparison with a baseline scheme that does not exploit the intrinsic multilinear structure of the sensed signal. Simulation results show that our proposed tensor-based method can achieve the same performance as the reference method while drastically reducing the computational complexity.
ISSN:2154-0225
DOI:10.1109/ISWCS61526.2024.10639156