Technical Program

DLW-L.2: Deep-Learning-Based Signal Processing for Wireless Communications

Symposium: Design, Implementation and Optimization of Deep Learning for Wireless Communications
Session Type: Lecture
Time: Thursday, November 29, 14:00 - 15:30
Location: Monorail
Session Chair: Zhongfeng Wang, Nanjing University
 
14:00 - 14:18
DLW-L.2.1: REINFORCEMENT LEARNING WITH BUDGET-CONSTRAINED NONPARAMETRIC FUNCTION APPROXIMATION FOR OPPORTUNISTIC SPECTRUM ACCESS
         Theodoros Tsiligkaridis; MIT Lincoln Laboratory
         David Romero; MIT Lincoln Laboratory
 
14:18 - 14:36
DLW-L.2.2: A MODEL-DRIVEN DEEP LEARNING NETWORK FOR MIMO DETECTION
         Hengtao He; Southeast University
         Chao-Kai Wen; National Sun Yat-sen University
         Shi Jin; Southeast University
         Geoffrey Ye Li; Georgia Institute of Technology
 
14:36 - 14:54
DLW-L.2.3: SET-THEORETIC LEARNING FOR DETECTION IN CELL-LESS C-RAN SYSTEMS
         Daniyal Amir Awan; Technical University of Berlin
         Renato L.G. Cavalcante; Fraunhofer Heinrich Hertz Institute
         Zoran Utkovski; Fraunhofer Heinrich Hertz Institute
         Slawomir Stanczak; Fraunhofer Heinrich Hertz Institute
 
14:54 - 15:12
DLW-L.2.4: CNN BASED RICIAN K FACTOR ESTIMATION FOR NON-STATIONARY INDUSTRIAL FADING CHANNEL
         Guobao Lu; University of Chinese Academy of Sciences
         Qilong Zhang; University of Chinese Academy of Sciences
         Xin Zhang; National University of Defense Technology
         Fei Shen; Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences
         Fei Qin; University of Chinese Academy of Sciences
 
15:12 - 15:30
DLW-L.2.5: ACTOR-CRITIC DEEP REINFORCEMENT LEARNING FOR DYNAMIC MULTICHANNEL ACCESS
         Chen Zhong; Syracuse University
         Ziyang Lu; Syracuse University
         M. Cenk Gursoy; Syracuse University
         Senem Velipasalar; Syracuse University