most citedProbabilistic Position-Aided Beam Selection for mmWave MIMO Systems

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Direction Finding with Sparse Arrays Based on Variable Window Size Spatial Smoothing

Wesley S. Leite, Rodrigo C. de Lamare, Yuriy Zakharov +2

In this work, we introduce a variable window size (VWS) spatial smoothing framework that enhances coarray-based direction of arrival (DOA) estimation for sparse linear arrays. By c…

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.SP20251 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…

cs.LG2025

A Unified MDL-based Binning and Tensor Factorization Framework for PDF Estimation

Mustafa Musab, Joseph K. Chege, Arie Yeredor +1

Reliable density estimation is fundamental for numerous applications in statistics and machine learning. In many practical scenarios, data are best modeled as mixtures of component…

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…