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most citedProbabilistic Position-Aided Beam Selection for mmWave MIMO Systems

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eess.SP2026

Low-Complexity Tensor Beamforming for RIS-Aided Multiuser Multistream MIMO Systems

Bruno Sokal, André L. F. de Almeida, Martin Haardt

We address joint active and passive beamforming for uplink RIS-assisted multi-user multi-stream MIMO systems with joint detection. The coupled design of the receive combiner, block…

eess.SP2025

Max-Min Beamforming for Large-Scale Cell-Free Massive MIMO: A Randomized ADMM Algorithm

Bin Wang, Jun Fang, Yue Xiao +1

We consider the problem of max-min beamforming (MMB) for cell-free massive multi-input multi-output (MIMO) systems, where the objective is to maximize the minimum achievable rate a…

eess.SP2025★ 1 cited

Probabilistic Position-Aided Beam Selection for mmWave MIMO Systems

Joseph K. Chege, Arie Yeredor, Martin Haardt

Millimeter-wave (mmWave) MIMO systems rely on highly directional beamforming to overcome severe path loss and ensure robust communication links. However, selecting the optimal beam…

eess.SP2024

Enhanced channel estimation for double RIS-aided MIMO systems using coupled tensor decomposition

Gerald C. Nwalozie, Andre L. F. de Almeida, Martin Haardt

In this paper, we consider a double-RIS (D-RIS)-aided flat-fading MIMO system and propose an interference-free channel training and estimation protocol, where the two single-reflec…

eess.SP2024

Direction of Arrival Estimation with Sparse Subarrays

W. Leite, R. C. de Lamare, Y. Zakharov +2

This paper proposes design techniques for partially-calibrated sparse linear subarrays and algorithms to perform direction-of-arrival (DOA) estimation. First, we introduce array ar…