192 citations · 760 across the 38 of their papers we have counts for
5 papers · 1 filter
Dealing with Limited Backhaul Capacity in Millimeter Wave Systems: A Deep Reinforcement Learning Approach
Mingjie Feng, Shiwen Mao
Millimeter Wave (MmWave) communication is one of the key technology of the fifth generation (5G) wireless systems to achieve the expected 1000x data rate. With large bandwidth at m…
Deep Reinforcement Learning Based Mode Selection and Resource Management for Green Fog Radio Access Networks
Yaohua Sun, Mugen Peng, Shiwen Mao
Fog radio access networks (F-RANs) are seen as potential architectures to support services of internet of things by leveraging edge caching and edge computing. However, current wor…
Application of Machine Learning in Wireless Networks: Key Techniques and Open Issues
Yaohua Sun, Mugen Peng, Yangcheng Zhou +2
As a key technique for enabling artificial intelligence, machine learning (ML) is capable of solving complex problems without explicit programming. Motivated by its successful appl…
Optimized Computation Offloading Performance in Virtual Edge Computing Systems via Deep Reinforcement Learning
Xianfu Chen, Honggang Zhang, Celimuge Wu +3
To improve the quality of computation experience for mobile devices, mobile-edge computing (MEC) is a promising paradigm by providing computing capabilities in close proximity with…
Performance Optimization in Mobile-Edge Computing via Deep Reinforcement Learning
Xianfu Chen, Honggang Zhang, Celimuge Wu +3
To improve the quality of computation experience for mobile devices, mobile-edge computing (MEC) is emerging as a promising paradigm by providing computing capabilities within radi…