activity
20172020
most citedDeep Learning for Ultra-Reliable and Low-Latency Communications in 6G Networks

8 citations · 17 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SP2020★ 8 cited

Deep Learning for Ultra-Reliable and Low-Latency Communications in 6G Networks

Changyang She, Rui Dong, Zhouyou Gu +6

In the future 6th generation networks, ultra-reliable and low-latency communications (URLLC) will lay the foundation for emerging mission-critical applications that have stringent…

eess.SP2019★ 1 cited

Prediction and Communication Co-design for Ultra-Reliable and Low-Latency Communications

Zhanwei Hou, Changyang She, Yonghui Li +2

Ultra-reliable and low-latency communications (URLLC) are considered as one of three new application scenarios in the fifth generation cellular networks. In this work, we aim to re…

eess.SP2019★ 1 cited

Towards Ultra-Reliable Low-Latency Communications: Typical Scenarios, Possible Solutions, and Open Issues

Daquan Feng, Changyang She, Kai Ying +5

Ultra-reliable low-latency communications (URLLC) has been considered as one of the three new application scenarios in the \emph{5th Generation} (5G) \emph {New Radio} (NR), where…

cs.IT2017★ 4 cited

Incentive Mechanism Design for Wireless Energy Harvesting-Based Internet of Things

Zhanwei Hou, He Chen, Yonghui Li +1

Radio frequency energy harvesting (RFEH) is a promising technology to charge unattended Internet of Things (IoT) low-power devices remotely. To enable this, in future IoT system, b…

cs.GT2017★ 3 cited

A Contract-based Incentive Mechanism for Energy Harvesting-based Internet of Things

Zhanwei Hou, He Chen, Yonghui Li +2

By enabling wireless devices to be charged wirelessly and remotely, radio frequency energy harvesting (RFEH) has become a promising technology to power the unattended Internet of T…