Wireless Networking and Systems (WINGS) Lab

SpecSense - Large-Scale Distributed Spectrum Sensing
Wings In SpecSense we envision a large-scale RF spectrum monitoring system that will feed into multitudes of spectrum-aware applications forming an entire ecosystem of spectrum data, analytics, and apps. Our goal is to investigate what it takes to develop an end-to-end enabling platform to support this vision. The SpecSense system (i) crowdsources spectrum monitoring using low-cost, low-power custom-designed hardware, and (ii) provides necessary API support for spectrum-aware apps via a central spectrum server/database platform. The project addresses various algorithmic and systems-level challenges for SpecSense.
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Publications: IEEE INFOCOM'20, PAM'19, IEEE DySPAN'18, IEEE INFOCOM'18, IEEE INFOCOM'17, ACM HotWireless'16, ACM CoNEXT'14, ACM MobiCom'13
Dynamic Spectrum Access / Mobile Spectrum Sensing
Wings This project deals with augmenting spectrum databases that are based on propagation models with real spectrum sensor measurements. It is envisioned that such measurements will be crowdsourced using mobile devices. We look into spatial and temporal opportunities across such resource-constrained devices to collect measurement data.

Publications: IEEE INFOCOM'17, ACM HotWireless'16, DCOSS'16, IEEE DySPAN'15, ACM CoNEXT'14, ACM Mobicom'13
Quality of Experience
Wings This work aims to guarantee good video QoE in resource constrained and highly congested wireless networks. With a multitude of radios available in newer generation smartphones (WiFi, 3G, 4G, LTE), we identify which network is enough for a good QoE and while saving phone's battery, data cost and so on. Further, we understand other critical factors along with network, such as resource availability (CPU, Memory, GPU and DSP) that influence QoE in low end devices.

Publications: USENIX NSDI'17, ACM CoNEXT'16, ACM MMSys'16, ACM IMC'14, ACM Cellnet'13
Backscatter-based Tag-to-Tag Networking
Wings This project develops a prototype RF tag platform called RIBBN (Research Infrastructure for Backscatter-Based Networks) that uses the principle of backscatterd communication (similar to RFID), but there is no requirement of RFID readers or equivalent devices. The tags have the ability to communicate among themselves using completely passive backscatter modulation. The vision is developing a modular/extensible, programmable and powerful platform that will drive the future Internet of Things.

Publications: ACM MSWiM'15
NFV for Cellular Core Networks
Wings This project studies network functions virtualization (NFV), specifically targeting virtualization & customization of cellular core networks functions of tomorrow. This not only involves study of LTE's EPC core but also its compatibility with the emerging M2M and IOTs with the LTE Architecture. Also, involved in developing the new policy framework for the next generation LTE infrastructure.

Publications: IFIP'17, ACM AllThingsCellular'16
FSO-based Networking
Wings This project develops very high bit rate (Gbps and up) dynamic topology networks using free space optical (FSO) links. Steerable FSO links power the network and are developed using commodity optical components. Two applications are studied: data center networks and backhaul for future picocellular networks.

Publications: ACM Mobicom'17, IEEE ICC'16, ACM Sigcomm'14, ACM Hotnets'13
Wings In this project we are interested in exploring machine learning approaches for localization using radio signals normally used for communications (such as WiFi and cellular signals). We are interested in exploring complex problem spaces in this general area.

Publications: ACM CoNEXT'11, IEEE INFOCOM'15, ACM/IEEE IPSN'20
Analytics on Cellular Data Networks
Wings This project seeks to undertake a significant modeling exercise on wireless/mobile network data with two goals: 1) understanding the traffic dynamics and discovering any possible structure or relationships; 2) using this knowledge for doing some form of resource management decisions. We specifically target cellular data networks.

Publications: IEEE INFOCOM'13
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