activity
20102020
most citedEnabling AI in Future Wireless Networks: A Data Life Cycle Perspective

155 citations · 285 across the 8 of their papers we have counts for

collaborators

8 papers

cs.IT2020★ 24 cited

Task Offloading for Large-Scale Asynchronous Mobile Edge Computing: An Index Policy Approach

Yizhen Xu, Peng Cheng, Zhuo Chen +3

Mobile-edge computing (MEC) offloads computational tasks from wireless devices to network edge, and enables real-time information transmission and computing. Most existing work con…

cs.IT2020★ 1 cited

Deep Multi-Task Learning for Cooperative NOMA: System Design and Principles

Yuxin Lu, Peng Cheng, Zhuo Chen +3

Envisioned as a promising component of the future wireless Internet-of-Things (IoT) networks, the non-orthogonal multiple access (NOMA) technique can support massive connectivity w…

cs.NI2020★ 155 cited

Enabling AI in Future Wireless Networks: A Data Life Cycle Perspective

Dinh C. Nguyen, Peng Cheng, Ming Ding +6

Recent years have seen rapid deployment of mobile computing and Internet of Things (IoT) networks, which can be mostly attributed to the increasing communication and sensing capabi…

cs.IT2020★ 2 cited

Spectrum Intelligent Radio: Technology, Development, and Future Trends

Peng Cheng, Zhuo Chen, Ming Ding +3

The advent of Industry 4.0 with massive connectivity places significant strains on the current spectrum resources, and challenges the industry and regulators to respond promptly wi…

eess.SP2019★ 11 cited

A Learning-Based Two-Stage Spectrum Sharing Strategy with Multiple Primary Transmit Power Levels

Rui Zhang, Peng Cheng, Zhuo Chen +2

Multi-parameter cognition in a cognitive radio network (CRN) provides a more thorough understanding of the radio environments, and could potentially lead to far more intelligent an…

cs.IT2018★ 71 cited

Mobile Collaborative Spectrum Sensing for Heterogeneous Networks: A Bayesian Machine Learning Approach

Yizhen Xu, Peng Cheng, Zhuo Chen +2

Spectrum sensing in a large-scale heterogeneous network is very challenging as it usually requires a large number of static secondary users (SUs) to obtain the global spectrum stat…