PhD proposition M/F : Integrated Sensing and Communication for mmWave MIMO Channel Estimation

16 Mar 2024
Job Information

Organisation/Company

CNRS

Department

Equipes Traitement de l'Information et Systèmes

Research Field

Physics

Researcher Profile

First Stage Researcher (R1)

Country

France

Application Deadline

5 Apr 2024 - 23:59 (UTC)

Type of Contract

Temporary

Job Status

Full-time

Hours Per Week

35

Offer Starting Date

1 Oct 2024

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

This position is a 3-year PhD contract in the context of PEPR 5G réseaux du futur, PC4 YACARI investigating the integrated sensing and communication for mmWave MIMO channel estimation. This thesis is thus part of a larger scientific project including internal and external collaborations from which the candidate will be able to benefit. The PhD project will be carried out in the ICI (Information, Communication, Imagerie) team of ETIS (UMR8051), under Prof. Inbar Fijalkow's supervision and Dr. Luan Chen's co-supervision. The successful candidate will be enrolled at CY's EM2PSI (Economics, Management, Mathematics, Physics, Computer Science) doctoral school.
ETIS is a joint lab between CY Cergy Paris Université, ENSEA and CNRS, and a prominent research unit in computer science and information technologies in France. ICI is one of ETIS's four multi-PI groups and is specialized in signal processing, information theory and wireless communications. The group's research areas include optimization of resource allocation for wireless communication systems, massive MIMO, NOMA systems, physical layer security, etc. ICI has built a world-class reputation and has become a major actor in these research areas in France with multiple national and international collaborations.

Context :
Millimeter-Wave (mmWave) communication is considered to be a key component of the next generation of mobile communication technologies (e.g., beyond 5G and 6G cellular systems). One of the major challenges is that RF signals propagating in the mmWave frequency band experience significant path loss, penetration and reflection loss. Despite these disadvantages, by adopting advanced MIMO technology, mmWave system can compensate the high propagation loss through beamforming techniques. However, the gains stemming from these multiple antenna techniques hinge on the ability to accurately estimate the channel state information (CSI).

Objectives :
In this context, we aim to address the problem of channel estimation for mmWave MIMO system by leveraging the emerging solution of integrated sensing and communication (ISAC), which allows communication and radar systems to share the scarce spectrum and expensive hardware resources, saving a large amount of cost. Specifically, sensing information obtained from a co-located radar at the base station, primarily including the location information represented by the time of flight (ToF) and angle of arrival (AoA), can be used to reduce the pilot overhead.

Research program :
During the PhD study, potential efficient channel estimation solutions will be thoroughly explored. Low pilot overhead is a prerequisite for effective time-varying channel estimation so that high-mobility users (e.g. vehicular networks) in ISAC scenarios can be reliably served. Given the major challenge that MIMO-aided ISAC systems introduce significant computational burden on the signal processing for both communications and radar sensing, compressed sensing (CS), which can recover signals from reduced measurements by leveraging the intrinsic sparsity, is a promising solution for ISAC channel estimation. A greedy orthogonal matching pursuit (OMP) based channel estimation algorithm can be designed and implemented by simulations in the framework of compressive sensing theory. Advanced machine learning techniques can also be investigated to serve the mmWave beam prediction. In addition, the realistic sensing/communication implementations could further be evaluated by deploying 60GHz/77GHz mmWave radar sensors which are available from the Next Generation Smart Wireless Communication platform (NextGenComm) in the lab.

[1] Garcia, Nil et al. ”Location-aided mm-wave Channel Estimation for Vehicular Communication.” in IEEE SPAWC, 2016.

[2] R. Mundlamuri, R. Gangula, C. K. Thomas, F. Kaltenberger and W. Saad, "Sensing Aided Channel Estimation in Wideband Millimeter-Wave MIMO Systems," in IEEE ICC Workshops, 2023.

[3] Luan Chen et al. ”AoA-aware Probabilistic Indoor Location Fingerprinting using Channel State Information”, in IEEE Internet of Things Journal, 2020.

[4] Gao, Zhen, et al. "Integrated sensing and communication with mmWave massive MIMO: A compressed sampling perspective." IEEE Transactions on Wireless Communications, 2022.

Requirements

Research Field

Physics

Education Level

PhD or equivalent

Languages

FRENCH

Level

Basic

Research Field

Physics

Years of Research Experience

None

Additional Information

Website for additional job details

https://emploi.cnrs.fr/Offres/Doctorant/UMR8051-VIRLAI-005/Default.aspx

Work Location(s)

Number of offers available

1

Company/Institute

Equipes Traitement de l'Information et Systèmes

Country

France

City

CERGY

Geofield

Where to apply

Website

https://emploi.cnrs.fr/Candidat/Offre/UMR8051-VIRLAI-005/Candidater.aspx

Contact

City

CERGY

Website

https://www.etis-lab.fr

STATUS: EXPIRED