From the 1 of 18 linked papers with an AI index.
18 papers
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…
Joint Access Point Selection and Precoder Design under Statistical CSI
Tim N. Faisst, Franz Weißer, Wolfgang Utschick
This work addresses joint access point (AP) selection and precoding for sum-rate maximization under statistical channel state information (CSI) in multi-AP multi-user systems. To 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…
Autoregressive-Gaussian Mixture Models: Efficient Generative Modeling of WSS Signals
Kathrin Klein, Benedikt Böck, Nurettin Turan +1
This work addresses the challenge of making generative models suitable for resource-constrained environments like mobile wireless communication systems. We propose a generative mod…
Is Lattice Reduction Necessary for Vector Perturbation Precoding?
Dominik Semmler, Wolfgang Utschick, Michael Joham
Vector perturbation (VP) precoding is an effective nonlinear precoding technique in the downlink (DL) with modulo channels, providing an approximation of dirty paper coding (DPC) w…
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…