SCMA (Sparse Code Multiple Access) Professors and Supervisors

Laurent Clavierمشاهده پروفایل

استاد

Mines-Telecom InstituteFrance

Laurent Clavier is a Professor at IMT Lille Douai (now IMT Nord Europe), affiliated with the Institut Mines-Télécom and conducting research within the CNRS laboratories IEMN (UMR 8520) and IRCICA (USR 3380). His work centers on digital communications and the physical layer of wireless networks for IoT applications, especially in energy-autonomous and ultra-dense environments. His research focuses on interference modeling in wireless networks, particularly under non-Gaussian and heavy-tailed conditions such as those found in IoT scenarios. He investigates the impact of interference in LoRa-like and SCMA-based networks, with a strong emphasis on statistical modeling, channel access mechanisms, and capacity analysis under α-stable noise. The recent publications highlight a consistent trend in analyzing and modeling real-world interference in low-power, large-scale wireless systems. Key themes include LoRa network optimization, unsupervised signal detection, multiuser access, and theoretical limits in non-Gaussian channels—indicating a deep integration of information theory, signal processing, and practical IoT deployment challenges. Scientific Awards: No scientific awards mentioned in the provided text. Laurent Clavier is actively involved in research projects such as ALPAGA and CASTREAU, contributing to advancements in resilient communication systems and drone-based technologies. While no formal list of advisees is provided, his HDR degree and professorial status suggest supervision of doctoral candidates. He has contributed to book chapters and high-impact journals, reflecting sustained research productivity. He is associated with research teams focusing on multi-robot systems and disaster-resilient communication frameworks, as evidenced by his participation in the Robot-IA events and comments on resilient systems. His work bridges theoretical communication models with practical IoT implementations.

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Cédric Le Ruyetمشاهده پروفایل

پژوهشگر

Ruhr University BochumGermany

Cédric Le Ruyet is a prominent researcher at the Conservatoire National des Arts et Métiers (CNAM) , affiliated with the CEDRIC Laboratory. His work spans Wireless Communications , Signal Processing , and 5G/6G Network Design , with a focus on Filter Bank Multicarrier (FBMC) systems, MIMO , and Cognitive Radio . He collaborates extensively with institutions like CEA-LETI and CNAM . His research interests include Channel Modeling , Resource Allocation , Beamforming , and Machine Learning in wireless contexts. He has contributed to Reconfigurable Intelligent Surfaces (RIS) for beam optimization and SCMA/OFDM codebook design. Recent publications highlight his work on QAM-FBMC systems, Rayleigh Fading Models , and 5G Network Coexistence . His articles often explore Distributed MIMO , Low-Complexity Equalizers , and Indoor Positioning via Channel State Information (CSI) . He has authored numerous IEEE Transactions and conference papers, with technical reports for projects like ANR POSEIDON and NF-PERSEUS . His methodologies integrate Genetic Algorithms , Lattice-Reduction , and Deep Learning for next-gen wireless systems.

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Hassan Kaisمشاهده پروفایل

پژوهشگر

Le Mans UniversitéFrance

Hassan Kais is a Teacher-researcher affiliated with the Institute of Acoustics at Le Mans University. His work bridges acoustics and telecommunications, focusing on advanced signal processing techniques. Key research areas: Acoustics, Machine Learning, Wireless Communications Institution: Le Mans University, France Hassan's research explores the intersection of acoustic signal analysis and next-generation communication systems. Notably, he has contributed to: Innovative microphone array designs for sound capture SCMA (Sparse Code Multiple Access) systems in telecommunications Machine learning applications in acoustic and wireless signal processing mmWave hybrid MIMO systems for 5G networks Thermo-acoustic and electroacoustic sensor development His publications demonstrate interdisciplinary expertise in: Acoustic wave propagation in complex media Deep learning for communication protocols Signal processing algorithms Metamaterials and transducer design Audio sensor networks Non-linear acoustics applications

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Pei Xiaoمشاهده پروفایل

استاد

University of SurreyUnited Kingdom

Professor Pei Xiao is a leading academic in wireless communications at the University of Surrey’s Institute for Communication Systems (5GIC), part of the School of Computer Science and Electronic Engineering. He holds a BEng from Huazhong University of Science & Technology, MSc from Tampere University of Technology, and PhD from Chalmers University of Technology. As technical manager of 5GIC, he oversees major 5G/6G research projects, coordinating activities across academia and industry. His research focuses on cutting-edge areas including 5G/6G network design, satellite communications, reconfigurable intelligent surfaces (RIS), integrated sensing and communication (ISAC), and machine learning-driven optimization. Key projects include EPSRC-funded initiatives on massive machine communications and industrial IoT systems. Professor Xiao’s recent publications emphasize innovations in beamforming, non-orthogonal multiple access (NOMA), and hybrid AI-hardware solutions for next-generation networks. He actively contributes to standards development through collaborations with Nokia Networks and global telecom partners. His work bridges theoretical advancements with practical implementations, addressing challenges in latency, energy efficiency, and network scalability.

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Ian D. Marslandمشاهده پروفایل

دانشیار

Carleton UniversityCanada

Dr. Ian D. Marsland is an Associate Professor in the Department of Systems and Computer Engineering at Carleton University, Faculty of Engineering and Design. He holds a Ph.D. in Electrical Engineering from the University of British Columbia and has been a faculty member since 1999. His research is centered on wireless digital communications, with a focus on error control coding, noncoherent detection, iterative decoding, and indoor localization. B.Sc.Eng. (Honours) in Mathematics and Engineering, Queen's University, 1987 M.Sc. in Electrical Engineering, University of British Columbia, 1994 Ph.D. in Electrical Engineering, University of British Columbia, 1999 His research interests span wireless digital communications , including indoor localization using wireless networks , error control coding (LDPC, turbo, polar codes) , noncoherent receiver design , and applications of iterative decoding . His work bridges theoretical communication systems with practical implementation in modern wireless networks. The analysis of his recent publications (2020–2024) reveals a strong trend toward advanced modulation and coding schemes such as SCMA , faster-than-Nyquist signaling , and polar codes , often integrated with machine learning (e.g., neural network-aided detection) and high-resolution localization techniques. His work frequently appears in high-impact IEEE journals like IEEE Transactions on Communications and top conferences including ICC and GlobeCom . Dr. Marsland has not been explicitly mentioned as receiving scientific awards in the provided texts. He actively advises graduate students and has collaborated extensively with researchers including H. Yanikomeroglu , R.H. Gohary , and T. Shehata . His research has been supported through academic grants and industrial partnerships, though specific grant details are not listed. He supervises work in areas such as MIMO systems, SCMA, polar coding, and indoor positioning. Dr. Marsland leads a research group focused on wireless communications and signal processing, with active projects in next-generation multiple access, low-latency detection, and robust communication in fading and interference-prone environments. His lab contributes to both theoretical advancements and practical implementations in modern wireless systems.

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Ian Marslandمشاهده پروفایل

دانشیار

Carleton UniversityCanada

Dr. Ian D. Marsland is an Associate Professor in the Department of Systems and Computer Engineering at Carleton University (Faculty of Engineering and Design). He holds a Ph.D. from the University of British Columbia and has been affiliated with Carleton since 1999. His research focuses on wireless digital communications, noncoherent receiver design, error control coding, and indoor localization using wireless networks. He has contributed to advancements in SCMA, FTN signaling, and polar codes, with a strong emphasis on iterative decoding applications. Education: B.Sc.Eng. (Honours) in Mathematics and Engineering, Queen's University (1987) M.Sc. in Electrical Engineering, University of British Columbia (1994) Ph.D. in Electrical Engineering, University of British Columbia (1999) Research Interests: Wireless communication systems (stationary/mobile) Error control coding (LDPC, turbo, polar codes) Noncoherent receiver design Faster-than-Nyquist (FTN) signaling and neural network-aided detection Multidimensional constellations for SCMA systems Indoor localization via wireless networks Recent Research Trends: Dr. Marsland’s recent work emphasizes low-complexity detection algorithms for FTN signaling, SCMA constellation design, and polar code optimization. His publications highlight advancements in throughput-based coding, sphere decoding for SCMA, and high-resolution positioning techniques using MUSIC-based methods. Grants & Advising: While specific grants or student advisees are not detailed in the provided texts, his research portfolio indicates sustained involvement in collaborative projects with industry and academic partners. His lab focuses on next-generation wireless systems and signal processing innovations. Labs & Teams: His research is conducted within Carleton’s Department of Systems and Computer Engineering, emphasizing interdisciplinary work in communications and signal processing. Collaborators include researchers from institutions like the University of Toronto and industry partners.

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