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20242026
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eess.SP2026

Lightweight Beam Index Map Using Coupled Gaussian Mixture Models

Amar Kasibovic, Franz Weißer, Wolfgang Utschick

This paper addresses the beam alignment problem in MIMO systems from a decentralized, mobile terminal (MT)-centric perspective. We propose a lightweight machine learning approach t…

eess.SP2026

Efficient Channel Prediction based on Gram-Square-Root Factorization using GMMs

Kathrin Klein, Amar Kasibovic, Michael Joham +2

The paper proposes a Gaussian mixture model framework that uses Gram‑square‑root factorization to efficiently predict MIMO‑OFDM channel state information from partial feedback, red…

eess.SP2026

Context-Aware CSI Prediction for Access Point Selection Utilizing Conditional VAEs

Franz Weißer, Amar Kasibovic, Wolfgang Utschick

Indoor wireless communication environments are strongly influenced by dynamic conditions, which affect channel state information (CSI) and, consequently, the precoding strategy and…

eess.SP2025

Wireless Channel Modeling for Machine Learning -- A Critical View on Standardized Channel Models

Benedikt Böck, Amar Kasibovic, Wolfgang Utschick

Standardized (link-level) channel models such as the 3GPP TDL and CDL models are frequently used to evaluate machine learning (ML)-based physical-layer methods. However, in this wo…

eess.SP2024

Addressing Pilot Contamination in Channel Estimation with Variational Autoencoders

Amar Kasibovic, Benedikt Fesl, Michael Baur +1

Pilot contamination (PC) is a well-known problem that affects massive multiple-input multiple-output (MIMO) systems. When frequency and pilots are reused between different cells, P…