Research Opportunities for Undergraduate Students at UConn
Prof. Song Han’s research group is looking for multiple undergraduate research students to work on the following two research projects in Summer 2025. If you are interested, please send your resume to Prof. Song Han (song.han@uconn.edu).
Project 1. Real-Time 5G RAN Resource Management Framework Design and Experimentation for Industrial IoT Systems.
This project aims to conduct experimental research on 5G New Radio (NR) using the NSF-supported Powder platform (https://powderwireless.net/). Powder is a remotely accessible “living laboratory” and provides open-source 5G testbeds, combining software-defined radio (SDR) units equipped with custom-designed RF frontends and implementation of the open-source OAI (OpenAirInterface) 5G software stack. Powder provides a detailed manual and some ready-to-use experiment configurations called ‘profiles.’ We plan to proceed with the project following two steps.
- Using some of the handy profiles provided by Powder to evaluate the 5G PHY layer techniques, e.g., mixed-numerology, by measuring the network throughput and latency.
- Implementing some well-designed scheduling algorithms into the platform, creating our own profile, and performing performance evaluation.
Preferred skills and experience:
- Proficient programming skills.
- Familiar with 5G networks.
- Experience with the OAI platform is highly preferred.
Some references for Real-Time 5G:
[RTSS’23] Tianyu Zhang, Jiachen Wang, Xiaobo Sharon Hu, Song Han, “Real-Time Flow Scheduling in Industrial 5G New Radio”, accepted in the 44th Real-Time System Symposium (RTSS), 2023.
[DAC’23] Tianyu Zhang, Sharon Xiaobo Hu, Song Han, “Contention-Free Configured Grant Scheduling for 5G URLLC Traffic”, accepted in Design Automation Conference (DAC), 2023.
Project 2. Architecture and Algorithm Designs for Resilient Time-Sensitive Networking (TSN).
Time-Sensitive Networking (TSN) is a collection of standards, standard amendments, and projects published or under development by the TSN Task Group (TG) within the IEEE 802.1 Working Group (WG). There are four main pillars on which TSN is built: (1) time synchronization, (2) guaranteed end-to-end (e2e) latency, (3) reliability, and (4) resource management. These characteristics make TSN a strong candidate for meeting special requirements in industrial automation, such as deterministic communication, ultra-low communication latency, and extremely high reliability.
One notable advantage of TSN lies in its capability to support mixed-critical applications within the same network infrastructure. This means that TSN can accommodate a diverse range of data traffic with varying levels of importance or urgency, from critical flight control systems to less time-sensitive passenger entertainment systems, all within a single network framework.
Due to specific environmental conditions, a range of faults may occur in TSN networks which may lead to the breakdown of one or several network equipment. While it is common in traditional networks to use a different path in case of link failure, TSN offers the opportunity of a more flexible approach, i.e., the run-time reconfiguration of the faulty network on both temporal and spatial dimensions while ensuring real-time guarantees for all affected flows.
This project aims to explore this potential and provide architecture and algorithm designs to handle safe and prompt TSN run-time reconfiguration for real-time and embedded networks.
Preferred skills and experience:
- Proficient programming skills.
- Familiar with Ethernet protocol stack.
- Experience with TSN is highly preferred.
Some references for TSN:
[CSUR] Tianyu Zhang, Gang Wang, Chuanyu Xue, Jiachen Wang, Mark Nixon, Song Han, “Time-Sensitive Networking (TSN) for Industrial Automation: Current Advances and Future Directions”, accepted in ACM Computing Surveys (CSUR), 2024.
[DAC’24] Chuanyu Xue, Tianyu Zhang, Song Han, “Towards Cost-Effective Real-Time High-Throughput End Station Design for Time-Sensitive Networking (TSN)”, accepted in Design Automation Conference (DAC), 2024.
Industrial Challenge from ECRTS 2025: https://www.ecrts.org/industrial-challenge-current-challenge-thales/