The key idea is to represent the potentially large IRS phase-shift vector using a low-rank tensor model. This is achieved by factorizing a tensorized version of the IRS phase-shift vector, where each component is modeled as the Kronecker product of a predefined number of factors of smaller sizes, which can be obtained via tensor decomposition algorithms. We show that the proposed low-rank models drastically reduce the required feedback requirements associated with the BS-IRS control links. Our simulation results indicate that the proposed method is especially attractive in scenarios with a strong line of sight component, in which case nearly the same spectral efficiency is reached as in the cases with near-optimal phase-shifts, but with a drastically reduced communication overhead.
Full abstract in IEEEXplore DOI: 10.1109/TWC.2023.3244487
Authors
Bruno Sokal, Paulo R. B. Gomes, André L. F. De Almeida – Federal University of Ceará, Brazil
Behrooz Makki, Gabor Fodor – Ericsson Research
Published in IEEE Transactions on Wireless Communications ( Volume: 22, Issue: 10)
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