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Stephan, M.Sc., Phillip

Phillip Stephan, M.Sc.

Research Assistant
Institute of Telecommunications

Contact

+49 711 685 67944
+49 711 685 67929
Email
Business card (VCF)

Pfaffenwaldring 47
70569 Stuttgart
Deutschland
Room: 2.340

Subject

My research interests are:

Wireless telecommunication systems and massive MIMO
Signal processing and machine learning for wireless systems
Channel charting and radio-based localization
Raytracing for channel modeling

Currently, I’m focusing on channel charting (CC), which aims to create a virtual map of the radio environment from high-dimensional channel state information (CSI) that is acquired by a multi-antenna wireless system. In contrast to supervised fingerprinting methods for user equipment (UE) localization, a channel chart can be learned in a self-supervised manner since the CSI mainly depends on the spatial position of the UE. However, CC is a fairly new field of study, so the ongoing research mainly focuses on improving the existing approaches, which include CSI feature engineering and dimensionality reduction. In addition, various applications for CC are explored.

Our channel charting tutorial provides a comprehensible step-by-step guide to perform triplet-based CC on channel measurements captured by our DICHASUS channel sounder.

If you are interested in wireless telecommunication systems, machine learning and programming, please feel free to contact me for a bachelor, research, or master thesis.

Publications

2023
1. P. Stephan, F. Euchner, and S. ten Brink, “Angle-Delay Profile-Based and Timestamp-Aided Dissimilarity Metrics for Channel Charting.” 2023.
  - BibTeX
  BibTeX
  @misc{stephan2023angledelay, archiveprefix = {arXiv}, author = {Stephan, Phillip and Euchner, Florian and ten Brink, Stephan}, eprint = {2308.09539}, primaryclass = {cs.IT}, title = {Angle-Delay Profile-Based and Timestamp-Aided Dissimilarity Metrics for Channel Charting}, year = 2023 }
2. F. Euchner, P. Stephan, and S. ten Brink, “Augmenting Channel Charting with Classical Wireless Source Localization Techniques.” 2023.
  - BibTeX
  BibTeX
  @misc{euchner2023augmenting, archiveprefix = {arXiv}, author = {Euchner, Florian and Stephan, Phillip and ten Brink, Stephan}, eprint = {2312.01968}, primaryclass = {cs.IT}, title = {Augmenting Channel Charting with Classical Wireless Source Localization Techniques}, year = 2023 }
2022
1. F. Euchner, P. Stephan, M. Gauger, S. Dörner, and S. Ten Brink, “Improving Triplet-Based Channel Charting on Distributed Massive MIMO Measurements,” in 2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC), 2022, pp. 1–5.
  - Abstract
  - BibTeX
  Abstract
  The objective of channel charting is to learn a virtual map of the radio environment from high-dimensional channel state information (CSI) that is acquired by a multi-antenna wireless system. Since, in static environments, CSI is a function of the transmitter location, a mapping from CSI to channel chart coordinates can be learned in a self-supervised manner using dimensionality reduction techniques. The state-of-the-art triplet-based approach is evaluated on multiple datasets measured by a distributed massive multiple-input multiple-output (MIMO) channel sounder, with both co-located and distributed antenna setups. The importance of suitable triplet selection is investigated by comparing results to channel charts learned from a genie-aided triplet generator and learned from triplets on simulated trajectories through measured data. Finally, the transferability of learned forward charting functions to similar, but different radio environments is explored.
  BibTeX
  @inproceedings{EuchnerCC2022, abstract = {The objective of channel charting is to learn a virtual map of the radio environment from high-dimensional channel state information (CSI) that is acquired by a multi-antenna wireless system. Since, in static environments, CSI is a function of the transmitter location, a mapping from CSI to channel chart coordinates can be learned in a self-supervised manner using dimensionality reduction techniques. The state-of-the-art triplet-based approach is evaluated on multiple datasets measured by a distributed massive multiple-input multiple-output (MIMO) channel sounder, with both co-located and distributed antenna setups. The importance of suitable triplet selection is investigated by comparing results to channel charts learned from a genie-aided triplet generator and learned from triplets on simulated trajectories through measured data. Finally, the transferability of learned forward charting functions to similar, but different radio environments is explored.}, author = {Euchner, Florian and Stephan, Phillip and Gauger, Marc and Dörner, Sebastian and Ten Brink, Stephan}, booktitle = {2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC)}, doi = {10.1109/SPAWC51304.2022.9833925}, issn = {1948-3252}, month = {07}, pages = {1-5}, title = {Improving Triplet-Based Channel Charting on Distributed Massive MIMO Measurements}, year = 2022 }
2. F. Euchner, P. Stephan, M. Gauger, and S. ten Brink, “Channel Sounder with Over-the-Air Antenna Synchronization: Absolute Phase and Timing Calibration Using Known Transmitter Locations,” European Conference on Networks and Communications, 2022.
  - BibTeX
  BibTeX
  @article{euchner2022channel, author = {Euchner, Florian and Stephan, Phillip and Gauger, Marc and Brink, Stephan ten}, journal = {European Conference on Networks and Communications}, title = {Channel Sounder with Over-the-Air Antenna Synchronization: Absolute Phase and Timing Calibration Using Known Transmitter Locations}, year = 2022 }
3. F. Euchner, P. Stephan, M. Gauger, and S. ten Brink, “Geometry-Based Phase and Time Synchronization for Multi-Antenna Channel Measurements,” 2022.
  - Abstract
  - BibTeX
  Abstract
  Synchronization of transceiver chains is a major challenge in the practical realization of massive MIMO and especially distributed massive MIMO. While frequency synchronization is comparatively easy to achieve, estimating the carrier phase and sampling time offsets of individual transceivers is challenging. However, under the assumption of phase and time offsets that are constant over some duration and knowing the positions of several transmit and receive antennas, it is possible to estimate and compensate for these offsets even in scattering environments with multipath propagation components. The resulting phase and time calibration is a prerequisite for applying classical antenna array processing methods to massive MIMO arrays and for transferring machine learning models either between simulation and deployment or from one radio environment to another. Algorithms for phase and time offset estimation are presented and several investigations on large datasets generated by an over-the-air-synchronized channel sounder are carried out.
  BibTeX
  @conference{euchner2022geometrybased, abstract = {Synchronization of transceiver chains is a major challenge in the practical realization of massive MIMO and especially distributed massive MIMO. While frequency synchronization is comparatively easy to achieve, estimating the carrier phase and sampling time offsets of individual transceivers is challenging. However, under the assumption of phase and time offsets that are constant over some duration and knowing the positions of several transmit and receive antennas, it is possible to estimate and compensate for these offsets even in scattering environments with multipath propagation components. The resulting phase and time calibration is a prerequisite for applying classical antenna array processing methods to massive MIMO arrays and for transferring machine learning models either between simulation and deployment or from one radio environment to another. Algorithms for phase and time offset estimation are presented and several investigations on large datasets generated by an over-the-air-synchronized channel sounder are carried out. }, author = {Euchner, Florian and Stephan, Phillip and Gauger, Marc and ten Brink, Stephan}, eventdate = {2022}, eventtitle = {IEEE Global Communications Conference}, title = {Geometry-Based Phase and Time Synchronization for Multi-Antenna Channel Measurements}, year = 2022 }

Teaching

summer term 2024	Master Lab Course "Multimedia Communications"
winter term 2023/2024	Master Lab Course "Multimedia Communications" Fachpraktikum (Bachelor) "Digitale Nachrichtenübertragung"
summer term 2023	Master Lab Course "Multimedia Communications"
winter term 2022/2023	Master Lab Course "Multimedia Communications" Fachpraktikum (Bachelor) "Digitale Nachrichtenübertragung" füSQ: Effektive Organisations- und Arbeitstechniken
summer term 2022	Master Lab Course "Multimedia Communications"

Phillip Stephan, M.Sc.

Contact

Subject

Publications

2023

BibTeX

BibTeX

2022

Abstract

BibTeX

BibTeX

Abstract

BibTeX

Teaching

Audience

Formalities

Services

Organization

Phillip Stephan, M.Sc.

Contact

Subject

Publications

2023

BibTeX

BibTeX

2022

Abstract

BibTeX

BibTeX

Abstract

BibTeX

Teaching

Here you can reach us

Audience

Formalities

Services

Organization