activity
20162020
most citedDeep Reinforcement Learning for Fresh Data Collection in UAV-assisted IoT Networks

14 citations · 16 across the 2 of their papers we have counts for

collaborators

5 papers

cs.IT202014 cited

Deep Reinforcement Learning for Fresh Data Collection in UAV-assisted IoT Networks

Mengjie Yi, Xijun Wang, Juan Liu +2

Due to the flexibility and low operational cost, dispatching unmanned aerial vehicles (UAVs) to collect information from distributed sensors is expected to be a promising solution…

cs.IT2018

Joint Queue-Aware and Channel-Aware Delay Optimal Scheduling of Arbitrarily Bursty Traffic over Multi-State Time-Varying Channels

Meng Wang, Juan Liu, Wei Chen +1

This paper is motivated by the observation that the average queueing delay can be decreased by sacrificing power efficiency in wireless communications. In this sense, we naturally…

cs.IT2018

Age-Optimal Trajectory Planning for UAV-Assisted Data Collection

Juan Liu, Xijun Wang, Bo Bai +1

Unmanned aerial vehicle (UAV)-aided data collection is a new and promising application in many practical scenarios. In this work, we study the age-optimal trajectory planning probl…

eess.SP20172 cited

Cache Placement in Fog-RANs: From Centralized to Distributed Algorithms

Juan Liu, Bo Bai, Jun Zhang +1

To deal with the rapid growth of high-speed and/or ultra-low latency data traffic for massive mobile users, fog radio access networks (Fog-RANs) have emerged as a promising archite…

cs.IT2016

Delay Optimal Scheduling of Arbitrarily Bursty Traffic over Multi-State Time-Varying Channels

Meng Wang, Juan Liu, Wei Chen

In this paper, we study joint queue-aware and channel-aware scheduling of arbitrarily bursty traffic over multi-state time-varying channels, where the bursty packet arrival in the…