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20242026
most citedLow-Complexity Tensor-Based Monostatic Sensing for IRS-Assisted Communication Systems

2 citations · 3 across the 12 of their papers we have counts for

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eess.SP2026

PARAFAC-Based Low-Latency Angular Tracking for RIS-Assisted Sensing

Kenneth Benício, André L. F. de Almeida, Bruno Sokal +3

This paper proposes adaptive tensor tracking for angular trajectories (ATTRACT), a structure-aware alternating least squares algorithm for low-latency target tracking in reconfigur…

eess.SP2026

Deconstructing the Composite Channel for Beyond Diagonal RIS: Channel Estimation and Beamforming Design

Fazal-E Asim, André L. F. de Almeida, Bruno Sokal +2

As beyond-diagonal reconfigurable intelligent surfaces (BD-RISs) gain increasing attention in high-frequency wireless communications, accurate and scalable channel-estimation metho…

eess.SP2026

Decoupled Delay-Doppler and Angle Estimation in BD-RIS Sensing via Nested Tucker Decomposition

Kenneth Benício, André L. F. de Almeida, Fazal-E-Asim +4

We study single-target localization in a group-connected beyond-diagonal reconfigurable intelligent surface (BD-RIS)-assisted monostatic network with K element groups. We propose a…

eess.SP2026★ 2 cited

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

Kenneth B. A. Benício, Bruno Sokal, André L. F. de Almeida +3

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 decompo…

eess.SP2026

Multi-Target Estimation via Tensor Decomposition for Beyond Diagonal RIS-Aided Bistatic Sensing

Kenneth Benício, André L. F. de Almeida, Fazal-E Asim +4

We investigate the performance of beyond-diagonal reconfigurable intelligent surfaces (BD-RIS) for bistatic MIMO multi-target sensing using a two-stage tensor Doppler-delay-angle e…

eess.SP2026

Living Off the Grid: Continuous Range-Angle Super-Resolution for Near-Field XL-MIMO

Sajad Daei, Gabor Fodor, Mikael Skoglund

Near-field extremely large multiple input multiple output (XL-MIMO) breaks the assumptions that make classical super-resolution effective: the receiver acquires only a limited set…