An Out-of-Sample Extension for Wireless Multipoint Channel Charting

Tushara Ponnada, Hanan Al-Tous*, Olav Tirkkonen, Christoph Studer

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

3 Citations (Scopus)

Abstract

Channel-charting (CC) is a machine learning technique for learning a multi-cell radio map, which can be used for cognitive radio-resource-management (RRM) problems. Each base-station (BS) extracts features from the channel-state-information samples (CSI) from transmissions of user-equipment (UE) at different unknown locations. The multi-path channel components are estimated and used to construct a dissimilarity matrix between CSI samples at each BS. A fusion center combines the dissimilarity matrices of all base-stations, performs dimensional reduction based on manifold learning, constructing a Multipoint-CC (MPCC). The MPCC is a two dimension map, where the spatial difference between any pair of UEs closely approximates the distance between the clustered features. MPCC provides a mapping for any given trained UE location. To use MPCC for cognitive RRM tasks, CSI measurements for new UEs would be acquired, and these UEs would be placed on the radio map. Repeating the MPCC procedure for out-of-sample CSI measurements is computationally expensive. For this, extensions of MPCC to out-of-sample UE CSIs are investigated in this paper, when Laplacian-Eigenmaps (LE) is used for dimensional reduction. Simulation results are used to show the merits of the proposed approach.

Original languageEnglish
Title of host publicationCognitive Radio-Oriented Wireless Networks - 14th EAI International Conference, CrownCom 2019, Proceedings
EditorsFaouzi Bader, Pawel Kryszkiewicz, Nikos Dimitriou, Adrian Kliks, Michal Sybis, Dionysia Triantafyllopoulou, Carlos E. Caicedo, Aydin Sezgin
Pages208-217
Number of pages10
DOIs
Publication statusPublished - 1 Jan 2019
MoE publication typeA4 Article in a conference publication
EventInternational Conference on Cognitive Radio-Oriented Wireless Networks - Poznan, Poland
Duration: 11 Jun 201912 Jun 2019
Conference number: 14

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume291
ISSN (Print)1867-8211

Conference

ConferenceInternational Conference on Cognitive Radio-Oriented Wireless Networks
Abbreviated titleCROWNCOM
Country/TerritoryPoland
CityPoznan
Period11/06/201912/06/2019

Keywords

  • Channel charting
  • Laplacian eigenmaps
  • Massive MIMO
  • Out-of-sample mapping

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