activity
20092026
most citedDynamic Computation Offloading for Mobile-Edge Computing with Energy Harvesting Devices

1.7k citations · 6.5k across the 204 of their papers we have counts for

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Showing 2018Show all

8 papers · 1 filter

eess.SP2018★ 6 cited

LORM: Learning to Optimize for Resource Management in Wireless Networks with Few Training Samples

Yifei Shen, Yuanming Shi, Jun Zhang +1

Effective resource management plays a pivotal role in wireless networks, which, unfortunately, results in challenging mixed-integer nonlinear programming (MINLP) problems in most c…

eess.SP2018★ 4 cited

Transfer Learning for Mixed-Integer Resource Allocation Problems in Wireless Networks

Yifei Shen, Yuanming Shi, Jun Zhang +1

Effective resource allocation plays a pivotal role for performance optimization in wireless networks. Unfortunately, typical resource allocation problems are mixed-integer nonlinea…

cs.IT2018★ 3 cited

Joint Activity Detection and Channel Estimation for IoT Networks: Phase Transition and Computation-Estimation Tradeoff

Tao Jiang, Yuanming Shi, Jun Zhang +1

Massive device connectivity is a crucial communication challenge for Internet of Things (IoT) networks, which consist of a large number of devices with sporadic traffic. In each co…

cs.IT2018

A Unified Framework for the Tractable Analysis of Multi-Antenna Wireless Networks

Xianghao Yu, Chang Li, Jun Zhang +2

Densifying networks and deploying more antennas at each access point are two principal ways to boost the capacity of wireless networks. However, the complicated distributions of th…

eess.SP2018

Scalable network adaptation for Cloud-RANs: An imitation learning approach

Yifei Shen, Yuanming Shi, Jun Zhang +1

Network adaptation is essential for the efficient operation of Cloud-RANs. Unfortunately, it leads to highly intractable mixed-integer nonlinear programming problems. Existing solu…

eess.SP2018

Minor probability events detection in big data: An integrated approach with Bayesian testing and MIM

Shuo Wan, Jiaxun Lu, Pingyi Fan +1

The minor probability events detection is a crucial problem in Big data. Such events tend to include rarely occurring phenomenons which should be detected and monitored carefully.…