Tensor-based modeling/estimation of static channels in IRS-assisted MIMO systems

Kenneth Brenner Benício, André de Almeida, Bruno Sokal, Fazal-E- Asim, Behrooz Makki, Gabor Fodor

DOI: 10.14209/sbrt.2023.1570923345

Evento: XLI Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2023)

Keywords: channel estimation intelligent reflecting surfaces tensor-based algorithm complexity analysis

Abstract

This paper proposes a tensor-based parametric modeling and estimation framework in MIMO systems assisted by intelligent reflecting surfaces (IRSs). We present two algorithms that exploit the tensor structure of the received pilot signal to estimate the concatenated channel. The first one is an iterative solution based on the alternating least squares algorithm. In contrast, the second method provides closed-form estimates of the involved parameters using the high order single value decomposition. Our numerical results show that our proposed tensor-based methods provide improved performance compared to competing state-of-the-art channel estimation schemes, thanks to the exploitation of the algebraic tensor structure of the combined channel without additional computational complexity.

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