Post-Doctoral Research Visit F - M Post-Doctoral Research Visit F - M Modern Grant-Free Access Techniques For Cellular Networks Ai And Experimentation H/F INRIA

Post-Doctoral Research Visit F/M Post-Doctoral Research Visit F/M Modern Grant-Free Access Techniques for Cellular Networks (AI and Experimentation)
Le descriptif de l'offre ci-dessous est en Anglais
Type de contrat : CDD

Niveau de diplôme exigé : Thèse ou équivalent

Fonction : Post-Doctorant

A propos du centre ou de la direction fonctionnelle

Created in 2008, the Inria Saclay Center is located at the heart of the Paris-Saclay scientific and technological excellence cluster, which alone accounts for 15% of French research. Serving the development of the Université Paris-Saclay and the Institut Polytechnique de Paris, the Inria Saclay center employs 80 people in research support services and 500 scientists of 54 nationalities.

Benefiting from continuous growth, the center now has a total of 42 project-teams and two in the process of being created, including 21 jointly with the Institut Polytechnique de Paris, 16 with the Université Paris-Saclay, as well as 7 Inria EPs, including one in collaboration with Onera and one with the Pôle Universitaire Centre Val de Loire. These research teams are spread over more than ten sites.

Contexte et atouts du poste

This post-doctoral position is part of the , and its project. PERSEUS focuses on the technologies, processing and optimization of next-generation cellular cell-free networks. This includes the development of robust physical and MAC layers and the proofs of concept for the practical assessment of the performance of selected algorithms.

The position will be based at Inria Saclay, with expected collaboration with other sites and partners. The start and end dates are flexible, subject to administrative constraints, and the contract is for 12 months.

Mission confiée

The proposed position will focus on the development of grant-free access techniques for IoT applications.

One common communication scenario in IoT applications is massive machine-type communications (mMTC), where a large number of devices transmit sporadic, small packets. In traditional cellular systems, each device is allocated orthogonal resources prior to uplink transmission via a grant mechanism. However, this allocation requires signaling on control channels, which can exceed the data payload size and lead to inefficient resource use. Consequently, grant-free methods [1] that eliminate or reduce control traffic are well suited for these scenarios. Removing coordination introduces non-orthogonality, resulting in the superposition of signals from some or all devices.

A recent family of random access protocols-sometimes called "modern random access"-aims to address and even exploit this phenomenon. The IRSA protocols (Irregular Repetition Slotted ALOHA) [2,3,4] use Successive Interference Cancellation (SIC) and represent one form of grant-free technique, but they can also operate with any packet transmission scheme. They are related to "Unsourced Random Access" [7]. Adapting these methods for grant-free mMTC in cellular networks is therefore of prime interest and the main objective of this position.

Principales activités

The initial research direction in this post-doctoral position is to study variants of modern random access, incorporating realistic physical-layer features and methods (e.g., [5,6]), including cell-free systems.

Our main objectives are to enhance performance and practicality in cellular networks. IRSA-based protocols can operate with any modulation scheme, including existing transmission techniques, and do not necessarily require NOMA features such as advanced multi-user detection. However, they can benefit from NOMA methods that improve SIC, as well as ML methods to perform SIC itself (e.g. [9]).

We are particularly interested in improving the selection of transmission opportunities (e.g., using precomputed sequences), possibly constructed with machine learning techniques (as in [8]). We could also consider lightweight node synchronization to reduce signal superposition.
An important aspect is that we plan to do actual experiments on the platform in INSA/Inria Lyon using available software. We envision the use of.

References

[1] Muhammad Basit Shahab, Rana Abbas, Mahyar Shirvanimoghaddam, and Sarah J. Johnson. "Grant-free non-orthogonal multiple access for iot: A survey.IEEE Communications Surveys & Tutorials", 2020.
[2] Gianluigi Liva. "Graph-Based Analysis and Optimization of Contention Resolution Diversity Slotted ALOHA." IEEE Transactions on Communications, 59(2):477-487, 2011.
[3] Clazzer, Federico, Andrea Munari, Gianluigi Liva, Francisco Lazaro, Cedomir Stefanovic, and Petar Popovski. "From 5G to 6G: Has the time for modern random access come?." arXiv preprint arXiv:1903.03063 (2019).
[4] "Modern Random Access for Grant-Free Cellular Networks," C. Adjih, Tutorial,
[5] Saeed Alsabbagh, Cédric Adjih, Amine Adouane, and Nadjib Aitsaadi. "Optimization of Irregular Repetition Slotted ALOHA with Imperfect SIC in 5G CIoT". IEEE International Conference on Communications (ICC) 2025.
[6] Saeed Alsabbagh, Cédric Adjih, Amine Adouane, and Nadjib Aitsaadi "IRSA Under Capture Effect and Imperfect SIC: a de Analysis for Future Cellular IoT", PIMRC 2025, Sep. 2025
[7] G. Liva and Y. Polyanskiy, Unsourced Multiple Access: A Coding Paradigm for Massive Random Access, Proceedings of the IEEE, vol. 112, no. 9, pp. 1214-1229, Sep. 2024
[8] Iman Hmedoush, Pengwenlong Gu, Cedric Adjih, Paul Muhlethaler, Ahmed Serhrouchni, "DS-IRSA: A Deep Reinforcement Learning and Sensing Based IRSA" in IEEE Global Communications Conference - GLOBECOM 2023, Kuala Lumpour, Malaysia, December 04-08, 2023.
[9] N. Shlezinger, R. Fu, Y. C. Eldar, "DeepSIC: Deep Soft Interference Cancellation for Multiuser MIMO Detection,"" IEEE Transactions on Wireless Communications, vol. 20, no. 2, pp. 1349-1362, Feb. 2021.

Compétences

- Ph. D. in Computer Science, Telecommunications, Electrical Engineering, or a related field.
- Excellent programming skills, specifically in Python and good knowledge of machine learning frameworks.
- Strong background in telecommunication, including communication theory, random access, (machine learning, or artificial intelligence applied to telecommunications).
- Experience in programming SDR (Software Defined Radio) is a plus.
- Some experience in is a plus.

Avantages

- Subsidized meals
- Partial reimbursement of public transport costs
- Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
- Possibility of teleworking and flexible organization of working hours
- Professional equipment available (videoconferencing, loan of computer equipment, etc.)
- Social, cultural and sports events and activities
- Access to vocational training
- Social security coverage

Rémunération

2788€ gross per month