most citedCache-Aided NOMA Mobile Edge Computing: A Reinforcement Learning Approach

10 citations · 23 across the 6 of their papers we have counts for

collaborators

6 papers

eess.SP2021

Integrated 3C in NOMA-enabled Remote-E-Health Systems

Xiao Liu, Yuanwei Liu, Zhong Yang +3

A novel framework is proposed to integrate communication, control and computing (3C) into the fifth-generation and beyond (5GB) wireless networks for satisfying the ultra-reliable…

eess.SP20213 cited

Artificial Intelligence Driven UAV-NOMA-MEC in Next Generation Wireless Networks

Zhong Yang, Mingzhe Chen, Xiao Liu +4

Driven by the unprecedented high throughput and low latency requirements in next-generation wireless networks, this paper introduces an artificial intelligence (AI) enabled framewo…

cs.IT20217 cited

Machine Learning for User Partitioning and Phase Shifters Design in RIS-Aided NOMA Networks

Zhong Yang, Yuanwei Liu, Yue Chen +1

A novel reconfigurable intelligent surface (RIS) aided non-orthogonal multiple access (NOMA) downlink transmission framework is proposed. We formulate a long-term stochastic optimi…

eess.SP2021

Deep Learning for Latent Events Forecasting in Twitter Aided Caching Networks

Zhong Yang, Yuanwei Liu, Yue Chen +1

A novel Twitter context aided content caching (TAC) framework is proposed for enhancing the caching efficiency by taking advantage of the legibility and massive volume of Twitter d…

eess.SP201910 cited

Cache-Aided NOMA Mobile Edge Computing: A Reinforcement Learning Approach

Zhong Yang, Yuanwei Liu, Yue Chen +1

A novel non-orthogonal multiple access (NOMA) based cache-aided mobile edge computing (MEC) framework is proposed. For the purpose of efficiently allocating communication and compu…

eess.SP20193 cited

Learning Automata Based Q-learning for Content Placement in Cooperative Caching

Zhong Yang, Yuanwei Liu, Yue Chen +1

An optimization problem of content placement in cooperative caching is formulated, with the aim of maximizing sum mean opinion score (MOS) of mobile users. Firstly, a supervised fe…