activity
20142023
most citedDeep Reinforcement Learning for Collaborative Edge Computing in Vehicular Networks

254 citations · 917 across the 42 of their papers we have counts for

collaborators
Showing 2017Show all

5 papers · 1 filter

cs.NI2017★ 2 cited

Dynamic Mobile Edge Caching with Location Differentiation

Peng Yang, Ning Zhang, Shan Zhang +3

Mobile edge caching enables content delivery directly within the radio access network, which effectively alleviates the backhaul burden and reduces round-trip latency. To fully exp…

cs.CR2017★ 2 cited

Multi-message Authentication over Noisy Channel with Secure Channel Codes

Dajiang Chen, Ning Zhang, Nan Cheng +4

In this paper, we investigate multi-message authentication to combat adversaries with infinite computational capacity. An authentication framework over a wiretap channel $(W_1,W_2)…

cs.NI2017★ 71 cited

Self-Sustaining Caching Stations: Towards Cost-Effective 5G-Enabled Vehicular Networks

Shan Zhang, Ning Zhang, Xiaojie Fang +3

In this article, we investigate the cost-effective 5G-enabled vehicular networks to support emerging vehicular applications, such as autonomous driving, in-car infotainment and loc…

cs.NI2017

Energy-Sustainable Traffic Steering for 5G Mobile Networks

Shan Zhang, Ning Zhang, Sheng Zhou +4

Renewable energy harvesting (EH) technology is expected to be pervasively utilized in the next generation (5G) mobile networks to support sustainable network developments and opera…

cs.NI2017★ 1 cited

Software Defined Space-Air-Ground Integrated Vehicular Networks: Challenges and Solutions

Ning Zhang, Shan Zhang, Peng Yang +3

This article proposes a software defined space-air-ground integrated network architecture for supporting diverse vehicular services in a seamless, efficient, and cost-effective man…