SPCOM-P5: Machine Learning for Communication and Networking I
Poster
Wed, 6 May, 14:00 - 16:00
Location: Poster Area 35
Session Type: Poster
Track: Signal Processing for Sensing and Communications [SPCOM] [SC]
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SPCOM-P5.1: FLOW MATCHING-BASED ACTIVE LEARNING FOR RADIO MAP CONSTRUCTION WITH LOW-ALTITUDE UAVS
Hao Sun, Shicong Liu, Xianghao Yu, City University of Hong Kong, Hong Kong; Ying Sun, Pennsylvania State University, United States of America

SPCOM-P5.2: WIRAG: RETRIEVAL-AUGMENTED GENERATION WITH LARGE LANGUAGE MODELS (LLM) FRAMEWORK FOR WIFI-BASED HUMAN ACTIVITY RECOGNITION
Xinyi Shen, Tao Deng, Soochow University, China; Yi Zhao, Uppsala University, Sweden; Juncheng Jia, Soochow University, China; Mianxiong Dong, Muroran Institute of Technology, Japan; Zhicheng Dong, Xizang University, China; Di Yuan, Uppsala University, Sweden

SPCOM-P5.3: IADP-SNN: Integer Activation Dropping Spiking Neural Network for Underwater Acoustic Communication Signal Recognition
Yan Gong, Acousnet Technology Company, China; Yi Fang, Institute of Acoustics, Chinese Academy of Sciences, China; Minyan Huang, Acousnet Technology Company, China; Li Ma, Institute of Acoustics, Chinese Academy of Sciences, China; Yanhui Tu, Anhui University, China; Haihong Feng, Institute of Acoustics, Chinese Academy of Sciences, China

SPCOM-P5.4: Soft Graph Transformer for MIMO Detection
Jiadong Hong, Lei Liu, Zhejiang University, China; Xinyu Bian, Wenjie Wang, Huawei Technologies Co., Ltd., Hong Kong; Zhaoyang Zhang, Zhejiang University, China

SPCOM-P5.5: STRUCTURE-DRIVEN GRAPH NEURAL NETWORKS FOR SCALABLE MULTI-GROUP MULTICASTING
Reza SoleimaniMajd, Min Dong, Ontario Tech University, Canada

SPCOM-P5.6: PRECODER DESIGN IN MULTI-USER FDD SYSTEMS WITH VQ-VAE AND GNN
Srikar Allaparapu, Michael Baur, Benedikt Böck, Michael Joham, Wolfgang Utschick, Technical University of Munich, Germany

SPCOM-P5.7: Scalable LLM-Augmented DRL with Context-Aware Prompt Learning for O-RAN Slicing
Fatemeh Lotfi, Hossein Rajoli, Fatemeh Afghah, Clemson University, United States of America

SPCOM-P5.8: Ultra-Reliable Risk-Aggregated Sum Rate Maximization via Model-Aided Deep Learning
Hassaan Hashmi, Yale University, United States of America; Spyridon Pougkakiotis, King's College London, United Kingdom of Great Britain and Northern Ireland; Dionysis Kalogerias, Yale University, United States of America