From the 1 of 5 linked papers with an AI index.
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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…
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…
Context-Aware CSI Prediction for Access Point Selection Utilizing Conditional VAEs
Franz WeiÃer, 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…
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…
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…