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 |