IEEE International Conference on Machine Learning for Communication and Networking
5–8 May 2024 // Stockholm, Sweden

Oral Sessions

Monday, May 6

OS 1: Machine Learning for Signal Detection
Chair: TBD
Time: 10:00-11:00
Location: Room F2

A Universal Deep Neural Network for Signal Detection in Wireless Communication Systems:
Khalid F Albagami (Imperial College London, United Kingdom (Great Britain)); Nguyen Van Huynh (Edinburgh Napier University, United Kingdom (Great Britain)); Geoffrey Ye Li (Imperial College London, United Kingdom (Great Britain))

Vector Similarity Search Based Offline Learning for Deep-Unfolded MIMO Signal Detector:
Lantian Wei and Tadashi Wadayama (Nagoya Institute of Technology, Japan); Kazunori Hayashi (Kyoto University, Japan)

A Machine Learning Approach for Simultaneous Demapping of QAM and APSK Constellations:
Arwin Gansekoele (Centrum Wiskunde & Informatica & Vrije Universiteit Amsterdam, The Netherlands); Alexios Balatsoukas-Stimming (Eindhoven University of Technology, The Netherlands); Tom Brusse (Ministry of Defence, The Netherlands); Mark Hoogendoorn (Vrije Universiteit Amsterdam, The Netherlands); Sandjai Bhulai (VU University Amsterdam, The Netherlands); Rob van der Mei (Centrum voor Wiskunde en Informatica, The Netherlands)

OS 2: Machine Learning for Resource Allocation
Chair: TBD
Time: 11:30-12:30
Location: Room F2

A Custom Loss Function for Machine Learning-Based Resource Allocation Policies:
Nidhi Simmons (Queens University Belfast, United Kingdom (Great Britain)); David E Simmons (Co-founder Dhali Holdings Ltd., United Kingdom (Great Britain)); Rashika Raina (Queens University Belfast, United Kingdom (Great Britain)); Michel Daoud Yacoub (State University of Campinas, Brazil)

MemorAI: Energy-Efficient Last-Level Cache Memory Optimization for Virtualized RANs:
Ethan Sánchez Hidalgo (Fundació i2CAT, Spain); Josep Xavier Salvat (NEC Labs Europe, Germany); Jose A. Ayala-Romero (NEC Laboratories Europe GmbH, Germany); Andres Garcia-Saavedra (NEC Labs Europe, Germany); Xi Li (NEC, Germany); Xavier Costa-Perez (ICREA and i2cat & NEC Laboratories Europe, Spain)

Energy-Efficient Power Allocation in Cell-Free Massive MIMO via Graph Neural Networks:
Ramprasad Raghunath and Bile Peng (TU Braunschweig, Germany); Eduard A Jorswieck (Technische Universität Braunschweig, Germany)

OS 3: Federated Learning
Chair: TBD
Time: 16:00-17:00
Location: Room F2

Balancing Energy Efficiency and Distributional Robustness in Over-The-Air Federated Learning:
Mohamed H Badi and Chaouki Ben Issaid (University of Oulu, Finland); Anis Elgabli (King Fahd University of Petroleum and Minerals, Saudi Arabia); Mehdi Bennis (Centre of Wireless Communications, University of Oulu, Finland)

Federated Learning via Active RIS Assisted Over-The-Air Computation:
Deyou Zhang (KTH Royal Institute of Technology, Sweden); Ming Xiao (Royal Institute of Technology, Sweden); Mikael Skoglund (KTH Royal Institute of Technology, Sweden); H. Vincent Poor (Princeton University, USA)

A Joint Communication and Learning Design for Secure Federated Learning with Differential Privacy:
Licheng Lin (University of Miami, USA); Zhaohui Yang (Zhejiang University, China); Mingzhe Chen (University of Miami, USA)

Tuesday, May 7

SS 1: Network Intelligence in Integrated Terrestrial and Non-Terrestrial Networks I
Chair: TBD
Time: 10:00-11:00
Location: Room F2

Q-Learning for Distributed Routing in LEO Satellite Constellations:
Beatriz Soret (Universidad de Malaga, Spain); Israel Leyva-Mayorga (Aalborg University, Denmark); Federico Lozano-Cuadra (University of Malaga, Spain); Mathias Thorsager (Aalborg University, Denmark)

Flexible Payload Configuration for Satellites Using Machine Learning:
Marcele O K Mendonça (University of Luxembourg & SNT, Luxembourg); Flor Ortiz, Jorge Querol, Eva Lagunas, Juan A. Vásquez Peralvo, Victor Monzon Baeza, Symeon Chatzinotas and Björn Ottersten (University of Luxembourg, Luxembourg)

Air Traffic and Usage Predictions in Avionic Communications Using Attention Based VAEGAN Model:
Hind Mukhtar (University of Ottawa & Satcom Direct, Canada); Raymond Schaub III (Satcom Direct, USA); Melike Erol-Kantarci (University of Ottawa & Ericsson, Canada)

SS 2: On Knowledge-based Future Networks I
Chair: TBD
Time: 11:30-12:30
Location: Room F2

Rollout-Based Shapley Values for Explainable Cooperative Multi-Agent Reinforcement Learning:
Franco Ruggeri (KTH Royal Institute of Technology & Ericsson Research, Sweden); William Emanuelsson (KTH Royal Institute of Technology, Sweden); Ahmad Terra (Ericsson AB & KTH Royal Institute of Technology, Sweden); Rafia Inam (Ericsson AB, Sweden); Karl H. Johansson (KTH, Sweden)

Utilizing Causal Learning for Cognitive Management of 6G Networks:
Mehmet Karaca (Ericsson Research, Turkey); Jishnu Sadasivan (Ericsson Research India, India); Ahmet Cihat Baktir (Ericsson, Turkey); Alexandros Palaios (Ericsson Research, Germany); András Zahemszky (Ericsson Research, Sweden)

Entity Recognition in Telecommunications Using Domain-Adapted Language Models:
Doumitrou Daniil Nimara and Fitsum Gaim (Ericsson, Sweden); Vincent Huang (Ericsson AB, Sweden)

OS 4: Semantic Communication
Chair: TBD
Time: 16:00-17:00
Location: Room F2

Over-The-Air Neural Group Testing:
Chandra Shekhara Kaushik Valmeekam, Krishna Narayanan and Alex Sprintson (Texas A&M University, USA)

Model-Free Reinforcement Learning of Semantic Communication by Stochastic Policy Gradient:
Edgar Beck, Carsten Bockelmann and Armin Dekorsy (University of Bremen, Germany)

Deep Joint Source-Channel Coding Over the Relay Channel:
Chenghong Bian (Imperial College London, United Kingdom (Great Britain)); Yulin Shao (Imperial College, United Kingdom (Great Britain)); Haotian Wu and Deniz Gündüz (Imperial College London, United Kingdom (Great Britain))

Wednesday, May 8

SS 3: Network Intelligence in Integrated Terrestrial and Non-Terrestrial Networks II
Chair: TBD
Time: 10:00-11:00
Location: Room F2

Nash Soft Actor-Critic LEO Satellite Handover Management Algorithm for Flying Vehicles:
Jinxuan Chen (Southeast University & Royal Institute of Technology, Sweden); Mustafa Ozger and Cicek Cavdar (KTH Royal Institute of Technology, Sweden)

Harnessing Supervised Learning for Adaptive Beamforming in Multibeam Satellite Systems:
Flor Ortiz, Juan A. Vásquez Peralvo, Jorge Querol, Eva Lagunas, Jorge L González-Rios, Luis Manuel Garcés-Socarrás, Victor Monzon Baeza and Symeon Chatzinotas (University of Luxembourg, Luxembourg)

Machine-Learning-Based Path Loss Prediction for In-Cabin Wireless Networks:
Nektarios Moraitis (National Technical University of Athens & Institute of Communications and Computers Systems, Greece); Lefteris Tsipi and Demosthenes Vouyioukas (University of the Aegean, Greece)

SS 4: On Knowledge-based Future Networks II
Chair: TBD
Time: 11:30-12:30
Location: Room F2

On the Accuracy and Efficiency of Received Signal Strength Modelling for a Forest Environment:
Vasileios P. Rekkas and Sotirios Sotiroudis (Aristotle University of Thessaloniki, Greece); Georgios P. Koudouridis (Ericsson & Dept. of Physics, Aristotle Univerity ot Thessaloniki (AUTH), Sweden); Panagiotis Sarigiannidis (University of Western Macedonia, Greece); Zaharias D. Zaharis, George K. Karagiannidis and Sotirios Goudos (Aristotle University of Thessaloniki, Greece)

Model Based Residual Policy Learning With Applications to Antenna Control:
Viktor Eriksson Möllerstedt and Alessio Russo (KTH, Sweden); Maxime Bouton (Ericsson, Sweden)

Explainable Asymmetric Auto-Encoder for End-To-End Learning of IoBNT Communications:
Roya Khanzadeh (Johannes Kepler University Linz, Austria); Stefan Angerbauer (Johannes Kepler University, Austria); Jorge Torresgomez (TU Berlin, Germany); Pit Hofmann (Technische Universität Dresden, Germany); Falko Dressler (TU Berlin, Germany); Frank H.P. Fitzek (Technische Universität Dresden & ComNets - Communication Networks Group, Germany); Andreas Springer and Werner Haselmayr (Johannes Kepler University Linz, Austria)

OS 5: Machine Learning for MAC Design
Chair: TBD
Time: 14:30-15:30
Location: Room F2

ML Framework for Wireless MAC Protocol Design:
Navid Keshtiarast (RWTH Aachen University, Germany); Marina Petrova (RWTH Aachen University, Germany & KTH Royal Institute of Technolgy, Sweden)

Flexible Reinforcement Learning Scheduler for 5G Networks:
Aurora Paz-Pérez, Anxo Tato and J. Joaquín Escudero-Garzás (Gradiant - Galician Research and Development Center for Advanced Telecommunications, Spain); Felipe Gómez-Cuba (University of Vigo, Spain)

Reliability-Optimized User Admission Control for URLLC Traffic: A Neural Contextual Bandit Approach:
Omid Semiari (Intel Labs, USA); Hosein Nikopour (Intel Corporation, USA); Shilpa Talwar (Intel, USA)