IEEE Global Communications Conference
4–8 December 2022 // Rio de Janeiro, Brazil // Hybrid: In-Person and Virtual Conference
Accelerating the Digital Transformation through Smart Communications

WS17: Next-Generation Radio Access Networks: Architectures, Interfaces, and Implementations (NxtGenRAN) - VIRTUAL

VIRTUAL PROGRAM

*All times are BRT (GMT-3)

SUNDAY, DECEMBER 4 09:00-10:30

O-RAN

Time: 09:00-10:30 BRT
 
On the Implementation of a Reinforcement Learning-based Capacity Sharing Algorithm in O-RAN
Irene Vilà (Universitat Politècnica de Catalunya (UPC), Spain); Oriol Sallent (Universitat Politècnica de Catalunya, Spain); Jordi Pérez-Romero (Universitat Politècnica de Catalunya (UPC), Spain)
 
Intelligent O-RAN for Beyond 5G and 6G Wireless Networks
Solmaz Niknam (Virginia Tech, USA); Abhishek Roy (MediaTek Inc USA, USA); Harpreet S Dhillon (Virginia Tech, USA); Sukhdeep Singh (Samsung R&D India - Bangalore, India); Rahul Banerji (Microsoft, India); Jeffrey Reed (Virginia Tech, USA); Navrati Saxena (San Jose State University, USA); Seungil Yoon (Samsung Electronics, Korea (South))
 
Low-cost Beam-combining Architecture for O-RUs in mmWave Massive MIMO based 5G O-RAN System
Abhay Kumar Sah and Santosh Kumar Singh (IIT Roorkee, India); Satya Kumar Vankayala (Samsung R&D Institute Bangalore, India); Sudharsan Parthasarathy (National Institute of Technology Tiruchirappalli, India); UmaKishore Godavarti (Indian Institute of Technologyy, Madras & Samsung R&D Institute Bangalore, India); Seungil Yoon (Samsung Electronics, Korea (South))
 
Evolutionary Deep Reinforcement Learning for Dynamic Slice Management in O-RAN
Fatemeh Lotfi and Omid Semiari (University of Colorado Colorado Springs, USA); Fatemeh Afghah (Clemson University, USA)

SUNDAY, DECEMBER 4 11:00-12:30

Physical Layer

Time: 11:00-12:30 BRT
 
gMLPNet: Multilayer Perceptron for CSI Feedback in FDD Massive MIMO System
Chongwan Ren and Qimei Cui (Beijing University of Posts and Telecommunications, China); Xiangjun Li (Beijing University of Post and Telecommunication, China); Xueqing Huang (New York Institute of Technology, USA); Xiaofeng Tao (Beijing University of Posts and Telecommunications, China)
 
Adaptive Generalized Proportional Fair Scheduling with Deep Reinforcement Learning
Juhwan Song and Yujin Nam (Samsung Research, Korea (South)); Hyungtae Kwon, Ilsong Sim and Seung Joo Maeng (Samsung Electronics, Korea (South)); Seowoo Jang (Samsung Electronics, Korea (South), Korea (South))
 
On the Power Consumption of Massive-MIMO, 5G New Radio with Software-Based PHY Processing
George Ntavazlis Katsaros, Rahim Tafazolli and Konstantinos Nikitopoulos (University of Surrey, United Kingdom (Great Britain))
 
Optimal Beam Set Design During Network Operation without explicit Traffic Localization
Aliye Ozge Kaya and Harish Viswanathan (Nokia Bell Labs, USA)

SUNDAY, DECEMBER 4 13:30-15:00

Higher Layers

Time: 13:30-15:00 BRT
 
A General Downlink Frequency-domain ICIC Framework for Next-generation RAN
Zening Liu (Purple Mountain Laboratories, China); Jie Wu (China Mobile Research Institute, China); Wanli Lu and Dongjie Liu (Purple Mountain Laboratories, China); Cheng Zhang and Yongming Huang (Southeast University, China); Jinri Huang (China Mobile Research Institution, China)
 
ML Approach for Power Consumption Prediction in Virtualized Base Stations
Merim Dzaferagic (Trinity College Dublin, Ireland); Jose A. Ayala-Romero (NEC Laboratories Europe GmbH, Germany); Marco Ruffini (CONNECT, Trinity College Dublin, Ireland)
 
Scenario Compaction and Ensemble with RAN Digital Twin for Efficient and Robust Learning
Minsuk Choi (Samsung Research, Seoul R&D Campus, Korea (South)); Yujin Nam, Juhwan Song, Haksung Kim, Jongwoo Choi and Seungyeon Lee (Samsung Research, Korea (South)); Seungku Han and Gihyun Kim (Samsung Electronics, Korea (South)); Seowoo Jang (Samsung Electronics, Korea (South), Korea (South))
 
Efficient Timer Optimization Method for RLC in Mobile Communication
Srihari Das Sunkada Gopinath (Samsung R&D Institute, India-Bangalore, India); Aneesh Deshmukh and Nayan Ostwal (Samsung R&D Institute India - Bangalore, India)

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