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Main Authors: Liesegang, Sergi, Pascual-Iserte, Antonio, Muñoz, Olga, Zappone, Alessio
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2601.19523
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author Liesegang, Sergi
Pascual-Iserte, Antonio
Muñoz, Olga
Zappone, Alessio
author_facet Liesegang, Sergi
Pascual-Iserte, Antonio
Muñoz, Olga
Zappone, Alessio
contents Within the context of massive machine-type communications+, reconfigurable intelligent surfaces (RISs) represent a promising technology to boost system performance in scenarios with poor channel conditions. Considering single-antenna sensors transmitting short data packets to a multiple-antenna collector node, we introduce and design an RIS to maximize the weighted sum rate (WSR) of the system working in the finite blocklength regime. Due to the large number of reflecting elements and their passive nature, channel estimation errors may occur. In this letter, we then propose a robust RIS optimization to combat such a detrimental issue. Based on concave bounds and approximations, the nonconvex WSR problem for the RIS response is addressed via successive convex optimization (SCO). Numerical experiments validate the performance and complexity of the SCO solutions.
format Preprint
id arxiv_https___arxiv_org_abs_2601_19523
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Design of RIS-aided mMTC+ Networks for Rate Maximization under the Finite Blocklength Regime with Imperfect Channel Knowledge
Liesegang, Sergi
Pascual-Iserte, Antonio
Muñoz, Olga
Zappone, Alessio
Signal Processing
Information Theory
Within the context of massive machine-type communications+, reconfigurable intelligent surfaces (RISs) represent a promising technology to boost system performance in scenarios with poor channel conditions. Considering single-antenna sensors transmitting short data packets to a multiple-antenna collector node, we introduce and design an RIS to maximize the weighted sum rate (WSR) of the system working in the finite blocklength regime. Due to the large number of reflecting elements and their passive nature, channel estimation errors may occur. In this letter, we then propose a robust RIS optimization to combat such a detrimental issue. Based on concave bounds and approximations, the nonconvex WSR problem for the RIS response is addressed via successive convex optimization (SCO). Numerical experiments validate the performance and complexity of the SCO solutions.
title Design of RIS-aided mMTC+ Networks for Rate Maximization under the Finite Blocklength Regime with Imperfect Channel Knowledge
topic Signal Processing
Information Theory
url https://arxiv.org/abs/2601.19523