Wireless Networking and Systems (WINGS) Lab
The Wireless Networking and Systems (WINGS) Lab was established in year 2001 and has been engaged in research in several areas of wireless networking and mobile computing systems, specifically focusing on using various mathematical modeling and machine learning techniques to improve network performance. The students and faculty in the lab have contributed in various directions including low-latency and fault-tolerant networks, wireless sensor networks and cellular networks. Currently the lab focuses on shared spectrum access technologies, mobile experience, RFID backscatter networks, and video streaming. Starting in 2020, we also explore quantum networks. Currently studying the network stack in quantum networks.
Lab Location
Rooms 330, 348 New Computer Science Building, Rooms 255,256 CEWIT Building.Selected Recent Papers
ACM Transactions on Quantum Computing 2024
Optimizing Initial State of Detector Sensors in Quantum Sensor Networks
ACM IMWUT 2023
RoVaR: Robust Multi-agent Tracking through Dual-layer Diversity in Visual and RF Sensor Fusion
IEEE TQE 2022
Efficient Quantum Network Communication using Optimized Entanglement-Swapping Trees
ACM CoNEXT 2021
dcSR: Practical Video Quality Enhancement using Data-CentricSuper-Resolution
ACM/IEEE IPSN 2020
Efficient Localization of Multiple Intruders for Shared Spectrum System
TheWebConf 2020
An intent-based automation framework for securing dynamic consumer IoT Infrastructures
Active Funded Projects
- [Quantum Information] Cisco Quantum Information
- [Quantum Computing / Networking] Robust Quantum Networks via Efficient Entanglement Distribution
- [Spectrum Sensing] Secured Spectrum Allocation and Patrolling in Shared Spectrum Systems
- [RFID, Tag-to-Tag Networks] RF-Based Analytics with Intelligent Backscattering in Passive Tag-to-Tag Networks
- [RFID, Backscattering] Passive Network of Tags for Smart Spaces
- [Picocells, FSO, 5G+] A Wireless Backhaul for Multi-Gigabit Picocells Using Steerable Free Space Optics
- [Spectrum Sensing] SpecSense: Bringing Spectrum Sensing to the Masses
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