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Hua Qian

8 accepted papers

2020

Global Traffic State Recovery VIA Local Observations with Generative Adversarial Networks

ICASSP 2020accepted

Traffic signal control for a large-scale traffic network is one challenging problem in intelligent transportation systems (ITS). High communication overheads are typically required to achieve the optimal control of the traffic signals in multiple road intersections. In this paper, in order to avoid…

Cited by 0SourceScholar
2020

Greedy Hybrid Rate Adaptation in Dynamic Wireless Communication Environment

ICASSP 2020accepted

High data throughput is desired in the wireless communication system design. Rate adaptation is an efficient way to update the data rate in the dynamic wireless environment. Conventional rate adaptation algorithms rely on the feedback of acknowledgment/negative acknowledgment (ACK/NACK) messages or…

Cited by 0SourceScholar
2020

Peer To Peer Offloading With Delayed Feedback: An Adversary Bandit Approach

ICASSP 2020accepted

Fog computing brings computation and services to the edge of networks enabling real time applications. In order to provide satisfactory quality of experience, the latency of fog networks needs to be minimized. In this paper, we consider a peer computation offloading problem for a fog network with un…

Cited by 0SourceScholar
2019

Online Learning for Computation Peer Offloading with Semi-bandit Feedback

ICASSP 2019accepted

Fog computing is emerging as a promising paradigm to perform distributed, low-latency computation. Efficient computation peer offloading is critical to fully utilize the computational resources in fog networks. In this paper, we consider computation peer offloading problem in a fog network with time…

Cited by 6SourceScholar
2018

Distributed Censoring with Energy Constraint in Wireless Sensor Networks

ICASSP 2018accepted

In wireless sensor networks (WSN s), energy is always precious for sensor nodes. To save energy, censoring is introduced to cut the total number of transmission by only transmitting informative data. This algorithm, however, ignores the energy consumption during the delivery of parameters, which can…

Cited by 0SourceScholar