Abstract
This paper introduces two innovative feedback algorithms—phase shift matrix (PSM)-based and single-bit feedback (SBF)-based—that improve the efficiency of phase adjustments in intelligent reflecting surfaces (IRS). In the PSM-based algorithm, the IRS phase shift vector is selected from a predefined PSM to maximize the output signal-to-noise ratio (SNR) at the receiver. The receiver then sends back only the index of the optimal phase shift vector to the transmitter. In contrast, the SBF algorithm adjusts the IRS elements using single-bit feedback. Here, the transmitter makes a minor random alteration in the phase of each IRS element at each iteration; simultaneously, the receiver transmits an SBF, indicating whether the SNR improved or deteriorated after the current iteration. The transmitter keeps the “good” phase adjustment and throws away the “bad” ones. Simulation results are produced to compare the performance of both algorithms in terms of average bit error rate, and results show that SBF-based phase adjustment of IRS elements is better than PSM-based phase adjustment.
Original language | English |
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Article number | e0322183 |
Pages (from-to) | 1-11 |
Number of pages | 11 |
Journal | PLoS ONE |
Volume | 20 |
Early online date | 8 May 2025 |
DOIs | |
Publication status | Published online - 8 May 2025 |
Bibliographical note
© 2025 Sohaib et al. This is an openaccess article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the
original author and source are credited.
Data Access Statement
All data generated and analyzed in this study are included within the paper.Keywords
- Algorithms
- Computer Simulation
- Feedback
- Signal-To-Noise Ratio