[2018-12-03] Dr. Mate Boban, Huawei Munich Research Center, "Reinforcement Learning Scheduler for Vehicle-to-Vehicle Communications Outside Network Coverage"(English Speech)

Poster:Post date:2018-11-30
Title: Reinforcement Learning Scheduler for Vehicle-to-Vehicle Communications Outside Network Coverage
Date: 2018-12-03 4:30pm-6:00pm
Location: R210, CSIE
Speaker: Dr. Mate Boban, Huawei Munich Research Center
Hosted by: Prof. Hsin-Mu (Michael) Tsai


Radio resources in vehicle-to-vehicle (V2V) communication can be scheduled either by a centralized scheduler residing in the network (e.g., a base station in case of cellular systems) or a distributed scheduler, where the resources are autonomously selected by the vehicles. The former approach yields a considerably higher resource utilization in case the network coverage is uninterrupted. However, in case of intermittent or out-of-coverage, due to not having input from centralized scheduler, vehicles need to revert to distributed scheduling. Motivated by recent advances in reinforcement learning (RL), we investigate whether a centralized learning scheduler can be taught to efficiently pre-assign the resources to vehicles for out-of-coverage V2V communication. Specifically, we use the actor-critic RL algorithm to train the centralized scheduler to provide non-interfering resources to vehicles before they enter the out-of-coverage area. Our initial results show that a RL-based scheduler can achieve performance as good as or better than the state-of-art distributed scheduler, often outperforming it. Furthermore, the learning process completes within a reasonable time (ranging from a few hundred to a few thousand epochs), thus making the RL-based scheduler a promising solution for V2V communications with intermittent network coverage.
Mate Boban received his diploma in informatics from the University of Zagreb, Croatia, and his Ph.D. degree in electrical and computer engineering from Carnegie Mellon University, Pittsburgh, Pennsylvania, in 2004 and 2012, respectively. He is a principal research engineer at Huawei Munich Research Center, Germany. Before joining Huawei, he worked for NEC Labs Europe, Carnegie Mellon University, and Apple. He is an alumnus of the Fulbright Scholar Program. He has co-chaired several IEEE workshops and conferences and has been involved in European Union-funded projects on vehicle-to-everything (V2X) communication as a work package leader and deliverables editor. He actively participates in key industry and standardization bodies dealing with V2X: 3GPP, 5GAA, and ETSI. His current research is in the areas of channel modeling, resource allocation, and machine learning applied to V2X communication systems. For his work on V2X, he received the Best Paper Awards at the IEEE Vehicular Technology Conference and IEEE Vehicular Networking Conference.

Last modification time:2018-11-30 PM 2:36

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