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Lou Salaun

Paris-Saclay, France
Research Engineer

Research Interests

Biography

Lou Salaün is a research engineer at Nokia Bell Labs, France. His research focuses on machine learning, discrete and continuous optimization methods, and distributed computing applied to resource allocation in future wireless networks. Another of his research interests is the application of online graph algorithms and multi-agent learning to autonomous multi-robot systems. Prior to joining Bell Labs as a permanent researcher, Lou Salaün obtained his Ph.D. in 2020 on resource allocation and optimization for the non-orthogonal multiple access from Institut Polytechnique de Paris, jointly working with Telecom Paris and Nokia Bell Labs.

Selected articles and publications

  • "Deep learning based power control for cell-free massive MIMO with MRT", IEEE Globecom, 2021
  • "Downlink connection density maximization for NB-IoT networks using NOMA with perfect and partial CSI", IEEE Internet of Things Journal, 2021
  • "Design of coded slotted ALOHA with interference cancellation errors", IEEE Transactions on Vehicular Technology, 2021
  • "Joint subcarrier and power allocation in NOMA: Optimal and approximate algorithms", IEEE Transactions on Signal Processing, 2020
  • "Zero-forcing oriented power minimization for multi-cell MISO-NOMA systems: A joint user grouping, beamforming, and power control perspective", IEEE JSAC, 2020
  • "Improved Deterministic Strategy for the Canadian Traveller Problem Exploiting Small Max-(s, t)-Cuts", International Workshop on Approximation and Online Algorithms, 2019
  • "Weighted sum-rate maximization in multi-carrier NOMA with cellular power constraint", IEEE Infocom, 2019
  • "Subcarrier and power allocation for the downlink of multicarrier NOMA systems", IEEE Transactions on Vehicular Technology, 2018
  • "Optimal joint subcarrier and power allocation in NOMA is strongly NP-hard", IEEE ICC, 2018

Honors & Awards

  • IDIA Best Thesis Award, 2021, from the Department of Computer Science, Data and Artificial Intelligence at Institut Polytechnique de Paris

  • PGMO Best Thesis Award, 2021, from the Mathematical Foundation Jacques Hadamard

  • Best Paper of the 9th IFIP/IEEE International Conference on Performance Evaluation and Modeling in Wired and Wireless Networks (PEMWN 2020): "Multi-Power Irregular Repetition Slotted ALOHA in Heterogeneous IoT networks"