Speaker: Yulia Sunyoto
Affiliation: Ph.D. Candidate - UCLA
*Available by Zoom only: https://ucla.zoom.us/j/3519847806
Abstract: Autonomous driving based systems will improve safety and enhance vehicular traffic efficiency. A fully-autonomous highway system must make effective use of a reliable, robust and low-latency communication system which enables data networking for the dissemination of critical and non-critical messages to and from highway vehicles. We develop methods for the design of data networking mechanisms that provide for low-latency dissemination of critical messages, as well as enabling high system data throughput capacity levels that are used to accommodate the transport of other message flows and sensor data streams. The data networking mechanisms that are studied and presented in the dissertation encompass vehicle-to-vehicle (V2V) and/or infrastructure-aided data communication. The latter employ vehicle-to-infrastructure and infrastructure-to-vehicle (V2I) communications. We develop novel networking protocols by considering mobile systems that employ sub-6 GHz spectral resources as well as emerging systems that make use of millimeter wave (mmWave) frequency bands. Data transmissions across sub-6 GHz bands experience lower channel propagation degradations. In turn, mmWave communications channels make use of more directional antenna array systems and provide for vastly wider spectral resources, and thus operating at much higher data rates and lower message latencies, while characterized by higher signal propagation losses and blocking conditions.
For transportation regions that are not supported by a dense communications infrastructure, we show that an effective use of V2V networking systems can be well realized, through the proper implementation of cross-layer operations. In turn, we show that when a proper infrastructure system, which consists of interconnected road side units (RSUs), is available, a highly upgraded networking operations can be realized. For this purpose, we derive the proper setting of the RSU-aided cross-layer network system. In setting the system schemes and parameters to induce desired delay-throughput performance behavior, we examine a multitude of scheduling schemes, and properly set the underlying modulation/coding schemes and parameters, as well as the underlying transmit power levels. We also involve the following system parameters and settings: antenna gains, vehicular formations, density of the RSU backbone. The schemes and techniques presented in the dissertation provide system designers with guidelines, protocols and performance evaluation methods that they will use to synthesize a network system for the autonomous highway that will guarantee enhanced data networking performance.
Biography: Yulia Sunyoto received her B.S. and M.S. degrees in Electrical Engineering from the University of California Los Angeles (UCLA) in 2013 and 2015, respectively. Her research interests include communications systems / networks and intelligent transportation systems.
Date(s) - Apr 01, 2020
10:00 am - 12:00 pm