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Found 10 papers, 1 papers with code
Representation-Constrained Autoencoders and an Application to Wireless Positioning
In a number of practical applications that rely on dimensionality reduction, the dataset or measurement process provides valuable side information that can be incorporated when learning low-dimensional embeddings.
Model-based Deep Learning for Beam Prediction based on a Channel Chart
In non-standalone or cell-free systems, chart locations computed at a given base station can be transmitted to several other base stations (possibly operating at different frequency bands) for them to predict which beams to use.
Wireless Channel Charting: Theory, Practice, and Applications
Channel charting is a recently proposed framework that applies dimensionality reduction to channel state information (CSI) in wireless systems with the goal of associating a pseudo-position to each mobile user in a low-dimensional space: the channel chart.
Channel Charting Aided Pilot Reuse for Massive MIMO Systems with Spatially Correlated Channels
Massive multiple-input multiple-output (mMIMO) technology is a way to increase the spectral efficiency of machine-type communications (MTC).
Exploiting Spatial Correlation for Pilot Reuse in Single-Cell mMTC
This work addresses the design of channel features from correlated fading channels to assist the pilot assignment in multi-sector mMTC systems under pilot reuse of orthogonal sequences.
Binary Subspace Chirps
We describe in details the interplay between binary symplectic geometry and quantum computation, with the ultimate goal of constructing highly structured codebooks.
Information Theory Information Theory
A Big Data Enabled Channel Model for 5G Wireless Communication Systems
This paper investigates various applications of big data analytics, especially machine learning algorithms in wireless communications and channel modeling.
Siamese Neural Networks for Wireless Positioning and Channel Charting
In this paper, we propose a unified architecture based on Siamese networks that can be used for supervised UE positioning and unsupervised channel charting.
Improving Channel Charting with Representation-Constrained Autoencoders
Channel charting (CC) has been proposed recently to enable logical positioning of user equipments (UEs) in the neighborhood of a multi-antenna base-station solely from channel-state information (CSI).
Channel Charting: Locating Users within the Radio Environment using Channel State Information
We propose channel charting (CC), a novel framework in which a multi-antenna network element learns a chart of the radio geometry in its surrounding area.
