WNCG Student Wins IEEE WCNC 2020 Best Paper Selection

Monday, June 22, 2020

WNCG student Yun Chen won Best Paper in the Wireless Networks track at the 2020 IEEE Wireless Communications and Networking Conference. Chen received the award for her paper “Efficient Drone Mobility Support Using Reinforcement Learning.”

The paper was co-authored by WNCG alumni Xingqin Lin and Talha Khan. Dr. Lin and Dr. Khan—both currently research engineers for Ericsson—worked on the research with Chen during her internship at Ericsson in 2019. Their project developed a reinforcement learning-based handover decision scheme for drones using both Q-learning algorithms and Deep Q Networks.

“It was very interesting to model a wireless communication problem into a reinforcement learning problem,” Chen stated. “We proposed a handover scheme for UAVs (Unmanned Aerial Vehicles, or ‘drones’) to maintain strong connectivity while reducing the number of handovers.” Compared to the baseline scheme in which the drone always connects to the strongest cell, the proposed method reduced handovers by about 80%.

The chance to work with WNCG alumni on the project was especially meaningful to Chen. Lin (graduated 2014) was advised by Prof. Jeff Andrews and Khan (graduated 2017) was advised by Prof. Robert Heath. Chen had a “wonderful time” collaborating and expressed interest in doing so again.

“It’s such a great honor that we can win the best paper award,” Chen stated. “The honor belongs to all of us on the team. In the future, if there are more opportunities we can work together, hopefully we will create even more impressive work."

At WNCG, Chen is a Graduate Research Assistant in Prof. Robert Heath’s Wireless Systems Innovation Laboratory. Her research interests include UAV navigation using deep reinforcement learning—specifically, interaction and coordination among drones and the interplay between drones and the environment.