Term of Award

Summer 2019

Degree Name

Master of Science, Electrical Engineering

Document Type and Release Option

Thesis (restricted to Georgia Southern)

Copyright Statement / License for Reuse

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


Department of Electrical and Computer Engineering

Committee Chair

Omid Semiari

Committee Member 1

Seungmo Kim

Committee Member 2

Rami Haddad


Ultra reliable, low latency vehicle-to-infrastructure (V2I) communication is a key requirement for seamless operation of autonomous vehicles (AVs) in future smart cities. To this end, cellular small base stations (SBSs) with edge computing capabilities can reduce the end-to-end (E2E) service delay by processing requested tasks from AVs locally, without forwarding the tasks to a remote cloud server. Nonetheless, due to the limited computational capabilities of the SBSs, coupled with the scarcity of the wireless bandwidth resources, minimizing the E2E latency for AVs and achieving a reliable V2I network are challenging. In this thesis, resource allocation in a V2I communication network is taken care of with a goal of establishing Ultra-Reliable Low-Latency (URLLC) in a vehicular network. Matching theory is used to solve an NP-hard problem into polynomial time. Downlink and computational resource allocation have been taken as two matching game, and tools from \emph{labor matching markets} have been used. The proposed framework can effectively perform distributed association of AVs to SBSs while accounting for the latency needs of AVs as well as the limited computational and bandwidth resources of SBSs. Moreover, the convergence of the proposed algorithm to a core allocation between AVs and SBSs is proved and its ability to capture interdependent computational and transmission latencies for AVs in a V2I network are characterized. Simulation results show that by optimizing the E2E latency, the proposed algorithm substantially outperforms the baseline cell association scheme, in terms of service reliability and latency.

Research Data and Supplementary Material


Available for download on Wednesday, June 26, 2024