Current Projects

Spectrum Access for Connected Vehicles

Sponsor: Georgia Department of Transportation (GDOT)  [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 V2X Communications

Sponsor: National Science Foundation (NSF)  [Project Info]

Connected and autonomous vehicles are no longer a futuristic dream from science fiction, but they are already emerging as a reality in our everyday life. Throughout the short yet rich history of evolution of connected and autonomous vehicles, a salient paradigm is to accomplish the efficient data exchange among vehicles, which has made vehicle-to-everything (V2X) communications a household name. Despite the rapid evolution of V2X communications, successful exchange of safety messages still remains an ambitious task mainly due to the high mobility and dynamicity of vehicular systems. The bigger problem is that as more vehicles become connected and autonomously driven, the number of exchanged messages will explode, which will likely deteriorate the chance of successful message delivery. This project aims to (i) define the driving risk of a vehicle; (ii) prioritize the spectrum access in accordance with the driving risk measured at each vehicle; and (iii) solve the prioritization problem (which is NP-complete) by using the reinforcement learning (RL).

Cybersecurity in Wireless Communications and Networks

It is crucial for the Close Access Team (CAT) to grasp radio frequency (RF) characteristics for identifying transmitters, even in non-military applications. In response to that need, this project extends its scope to include signals beyond the military realm, such as cellular and Wi-Fi, which demands a high level of capability of identifying key RF characteristics such as modulation, bandwidth, pulse width, etc. Accommodating this breadth can be expensive when designing a prototype. To address this, we propose a two-pronged solution: (i) utilizing a neural network (NN) for handling signal diversity and (ii) employing software-defined radio (SDR) for cost efficiency.

Blockchain Applied to Connected Vehicles

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.