IEEE Global Communications Conference
9-13 December 2018 // Abu Dhabi, UAE
Gateway to a Connected World


2018 IEEE Global Communications Conference: Workshops: Machine Learning for Communications Program

Thursday, December 13 8:30 - 10:00

MLCOMM-1: Transceiver design, detection, and decoding

Autoencoder-Based Optical Wireless Communications Systems
Morteza Soltani, Wael Fatnassi, Ahmed Aboutaleb and Zouheir Rezki (University of Idaho, USA); Arupjyoti Bhuyan (INL, USA); Paul Titus (Idaho National Laboratory, USA)
Channel Agnostic End-to-End Learning based Communication Systems with Conditional GAN (invited paper)
Hao Ye (Georgia Tech, USA); Geoffrey Ye Li and Fred Juang (Georgia Institute of Technology, USA); Kathiravetpillai Sivanesan (Intel Corporation, USA)
Deep Learning-Based Decoding for Constrained Sequence Codes
Congzhe Cao, Duanshun Li and Ivan Fair (University of Alberta, Canada)
On the Sphere Decoding for MU-MIMO Systems with One-bit ADCs: Hierarchical Clustering Forest
Seonho Kim and SongNam Hong (Ajou University, Korea)
Deep Learning Based Joint Detection and Decoding of Non-Orthogonal Multiple Access Systems
Fuqiang Sun, Kai Niu and Chao Dong (Beijing University of Posts and Telecommunications, P.R. China)

Thursday, December 13 10:30 - 12:00

MLCOMM-2: Signal Processing

MmWave Vehicular Beam Training with Situational Awareness by Machine Learning (invited paper)
Yuyang Wang (University of Texas at Austin, USA); Aldebaro Klautau (Universidade Federal do Para, Brazil); Monica Ribero (University of Texas at Austin, USA); Murali Narasimha (Huawei Technologies, USA); Robert Heath (The University of Texas at Austin, USA)
Improved Localization Accuracy using Machine Learning: Predicting and Refining RSS Measurements
Cam Ly Nguyen (Corporate Research & Development Center, Toshiba, Japan); Orestis Georgiou (Toshiba Telecommunications Research Laboratory, United Kingdom (Great Britain)); Vorapong Suppakitpaisarn (The University of Tokyo & JST, ERATO, Kawarabayashi Large Graph Project, Japan)
Machine Learning for early HARQ Feedback Prediction in 5G
Nils Strodthoff and Barış Göktepe (Fraunhofer Heinrich Hertz Institute, Germany); Thomas Schierl (Fraunhofer HHI, Germany); Wojciech Samek (Fraunhofer Heinrich Hertz Institute, Germany); Cornelius Hellge (Fraunhofer HHI, Germany)
Machine Learning Based Hybrid Precoding for MmWave MIMO-OFDM with Dynamic Subarray
Yiwei Sun, Zhen Gao and Hua Wang (Beijing Institute of Technology, P.R. China); Di Wu (China Academy of Information and Communications Technology, P.R. China)
Geometric Tracking of Vehicular mmWave Channels to Enable Machine Learning of Onboard Sensors
Erich Zöchmann (TU Wien, Austria); Vutha Va (University of Texas at Austin, USA); Markus Rupp (TU Wien, Austria); Robert Heath (The University of Texas at Austin, USA)

Thursday, December 13 1:30 - 3:00

MLCOMM-3: Resource Allocation

Deep Reinforcement Learning (DRL)-based Transcoder Selection for Blockchain-Enabled Video Streaming
Mengting Liu (Beijing University of Posts and Telecommunications, P.R. China); F. Richard Yu (Carleton University, Canada); Yinglei Teng (Beijing University of Posts and Telecommunications, P.R. China); Victor C.M. Leung (University of British Columbia, Canada); Mei Song (Beijing University of Posts and Telecommunications, P.R. China)
Deep Deterministic Policy Gradient based Dynamic Power Control for Self-Powered Ultra-Dense Networks
Han Li (Beijing University of Post and Telecommunication, P.R. China); Tiejun Lv and Xuewei Zhang (Beijing University of Posts and Telecommunications, P.R. China)
Actor-Critic-Based Resource Allocation for Multi-modal Optical Networks
Boyuan Yan, Yongli Zhao, Yajie Li, Xiaosong Yu and Jie Zhang (Beijing University of Posts and Telecommunications, P.R. China); Ying Wang and Longchuan Yan (State Grid Information & Telecommunication Company, P.R. China); Sabidur Rahman (University of California, Davis, USA)
Artificial Intelligence Driven Optimization of Channel and Location in Wireless Networks
Samurdhi Karunaratne (University of Peradeniya, Sri Lanka & Nokia Bell Labs, Belgium); Ramy Atawia (Queen's University, Canada); Erma Perenda (Nokia, Belgium); Haris Gacanin (Nokia Bell Labs, Belgium)
Joint Machine Learning based Resource Allocation and Hybrid Beamforming Design for Massive MIMO
Irfan Ahmed (Higher Colleges of Technology, United Arab Emirates); Hedi Khammari (Taif University, Saudi Arabia)

Thursday, December 13 3:30 - 5:00

MLCOMM-4: Mobile Networks

Deep Neural Network based Computational Resource Allocation for Mobile Edge Computing
Ji Li and Tiejun Lv (Beijing University of Posts and Telecommunications, P.R. China)
An Association Rules Based Conflict-graph Construction Approach for Ultra-Dense Networks
Jiaqi Cao, Tao Peng, Weiguo Dong, Xin Liu and Wenbo Wang (Beijing University of Posts and Telecommunications, P.R. China)
Artificial Intelligence Based Handoff Management for Dense WLANs: A Deep Learning Approach
Zijun Han and Xiangming Wen (Beijing University of Posts and Telecommunications, P.R. China); Wei Zheng and Zhaoming Lu (BUPT, P.R. China); Tao Lei (Beijing University of Posts and Telecommunications & Beijing Key Laboratory of Network System Architecture and Convergence, P.R. China)
Mask R-CNN Based Object Detection for Intelligent Wireless Power Transfer
Aozhou Wu, Qingqing Zhang, Wen Fang, Hao Deng, Sai Jiang, Qingwen Liu and Pengfei Xia (Tongji University, P.R. China)
Human Activity Recognition Using Deep Learning Networks with Enhanced Channel State information
Zhenguo Shi and J. Andrew Zhang (University of Technology Sydney, Australia); Richard Yi Da Xu (University of Technology, Sydney, Australia); Gengfa Fang (University of Technology Sydney, Australia)




Star Diamond Patrons