V2X Communications for Connected Vehicles
Sponsor: Georgia Department of Transportation (GDOT) [View project info]
Vehicle-to-everything (V2X) communications are expected to take a critical role in a variety of transportation safety applications in connected and autonomous vehicle environment. However, Dedicated Short-Range Communications (DSRC), one of the representative technologies implementing V2X communications, is encountering challenges due to the re-allocation of the 5.9 GHz spectrum by the Federal Communications Commission (FCC). The state of Georgia is leading the nation in the deployment of connected vehicle infrastructure with more than 1,700 roadside units (RSUs) operating in DSRC. This project aims at measuring the impact of the spectrum re-allocation on the performance of the Georgia's connected vehicle infrastructure. The project's particular technical focuses are to (i) model the performance of a DSRC system and (ii) design a protocol to improve the DSRC performance, under the FCC's reform of the 5.9 GHz band.
Reinforcement Learning for Performance Optimization of a V2X Network
The key challenges for stable performance of a V2X network arises from the dynamicity of environment mainly due to its mobility. It makes a compelling case of enabling each vehicle to learn the ever changing environment autonomously. However, the learning itself is extremely complicated due to the dynamicity as well, which necessitates that the learning framework itself must be resilient and flexible according to the environment. Projects stemming from this research target to establish reinforcement learning (RL) frameworks for a V2X network. One particular example is to design a RL mechanism for optimizing the "endorsement" process in a blockchain system applied to V2X. It shows that the learning mechanism can be formulated as a multi-armed bandit (MAB) problem, which enables a vehicle, without any assistance from external infrastructure, to autonomously learn the environment and maximize the probability of block being successfully committed to the chain.
Blockchain for V2X Networks
This research investigates the feasibility of blockchain in V2X networks. First, it characterizes how 'mobility' affects the performance of a blockchain system operating in a vehicle-to-everything (V2X) network. The mobility of nodes incurs a unique challenge to a blockchain system due to continuous change and dynamicity in connectivity of the nodes. Specifically, the mobility makes a proof-of-work (PoW) process difficult since, while moving, the nodes can only have a limited length of time for a "rendezvous" to exchange a new block for verification. For this reason, an accurate modeling for the block exchange behavior in a V2X network is also challenging, which nevertheless has not been discussed in previous studies.
Second, this project applies the reinforcement learning to optimize the performance of a blockchain-empowered V2X network. It targets to address the <Scalability trilemma> of blockchain, where scalability, decentralized, and security cannot be achieved in a single blockchain type. For instance, a flexible blockchain system such as Hyperledger Fabric gains interest thanks to its scalability; but the "execute-order" mechanism adopted by the Hyperledger Fabric leaves the system less secure. This research targets to address this issue in various V2X network settings.
Human EMF Exposure in Wearable Communications Systems
The concern on human health is often overseen while wearable technologies attract exploding interests. Mainly due to the extreme proximity or direct physical contact to the human skin, wearable communications devices are prone to cause higher levels of specific absorption rate (SAR) at the skin surface. Unfortunately, so far, no prior work has provided a comprehensive study encompassing all the aspects that the general public needs to understand about wearable technologies--i.e., the analytical and experimental backgrounds, and report of SAR levels generated from commercial wearable devices. In this context, this research provides an extensive review of SAR from various commercial wearable devices that are currently sold in the market, as well as the analytical framework and the current measurement methodologies for standard compliance tests. Moreover, considering the present interest in millimeter wave (mmW), this research sheds light on the SAR evaluated at 60 GHz and compares to that measured at 2.4 GHz. We expect that this project will be valuable in informing the general public about the safety in using the currently sold wearable devices, and in igniting further study of the exact biological consequences from electromagnetic field (EMF) exposure due to wearable devices.
Georgia Department of Transportation (GDOT), Adequacy of DSRC in 5.9 GHz band for GDOT's connected vehicle infrastructure, ($87,142, May 2020 - May 2021, PI)
Millennium Corporation, Real-time data analysis to achieve risk reduction and enhanced security monitoring, ($84,557, Jul. 2019 - Jun. 2020, PI)
Georgia Southern University Faculty Development Committee Award, Wireless communications in nanonetwork for healthcare applications, ($9,986, Jul. 2019 - Jun. 2020, PI)
Georgia Southern University College of Engineering and Computing Faculty Research Seed Grant, Low-cost improvement of wireless sensor network for surface water management, ($7,000, Jan. - May 2019, PI)
Georgia Southern University College of Engineering and Computing Faculty Research Seed Grant, Promotion of traffic safety and communication efficacy in connected vehicles, ($8,000, Jan. - May 2019, Co-PI)
Georgia Southern University College of Engineering and Computing Undergraduate Research Award, Security in underwater communications, ($1,684, Jan. - May 2019, Faculty Advisor for Mr. Treston Montoya)
Georgia Southern University Faculty Development Summer Award, Creation of hands-on projects on disaster emergency communications ($3,000, Jun. - Jul. 2018, PI)
Georgia Southern University College of Engineering and Computing Faculty Research Seed Grant, Operation of future cellular communications in shared bands ($8,000, Jan. - May 2018, PI)