Demo videos from selected projects below.

xSHIFT: Battery-less RF Tags Deployable with Commodity Devices (2020)

This demo introduces xSHIFT, which is a novel, completely passive (battery-less) RF tag that works with commodity WiFi devices. One of the biggest bottlenecks in deploying battery-free wireless tags/sensors for on-body/object applications today is the need for dedicated, expensive readers to access and read these tags. xSHIFT aims to change this by bringing the benefits of passive RFID tags to consumer and personal health applications at “low cost” by designing novel RF tags that can operate with our smartphones, WiFi access points, and other smart devices (e.g. smart speakers), i.e. without the need for a dedicated RFID-like reader infrastructure. This can open the door to a myriad of physical analytics applications in consumer spaces.

TrackIO: Infrastructure-free Tracking of First Responders Inside Buildings using UAVs Outside (2019)

This demo shows how TrackIO is able to accurately localize and track first responders in hostile indoor environments, without relying on any indoor wireless infrastructure. It shows how ultra-wideband (UWB) and small form factor UAV(s), along with algorithmic innovations, are leveraged to enable accurate (1-2m) tracking of responders even when they are mobile and deep inside buildings. This information is made available to a situation coordinator on the ground as well as to responders inside to better coordinate and execute the mission both safely and efficiently.

SkyLiTE: A Network in the Sky for On-demand, Wide-area, Real-time Communication and Sensing (2018)

This demo captures some of the applications that can be enabled by SkyLiTE — a “high capacity, un-tethered network of UAVs” that can provide on-demand connectivity and sensing services — which are particularly useful in first responder scenarios. Specifically, the demo shows that both supplementary (to existing cellular networks) and stand-alone (private) LTE networks can be created on-demand, with a high-capacity backhaul network between UAVs. This allows for applications such as high-resolution, real-time video surveillance and analytics, video broadcasts for target events, HD video chat between responders, etc.

Context-empowered Mobile Edge Computing (2017)

This demo captures how we leverage user proximity information (enabled through peer-peer discovery mechanisms like WiFi-direct or LTE-direct) to enable an augmented-reality based smart retail application that requires tight latencies for real-time operation. Specifically, the user context information is used to re-direct the processing of the real-time AR application flow from the LTE core network to the edge of the mobile network, while also allowing to optimize the AR application itself. Update: The system was since further optimized to reduce the end-end latency for the AR application to sub-second.

ATOM: Intelligent Traffic Mangement over Heterogeneous Wireless Interfaces (LTE, WiFi) (2015)

In this demo, we setup an LTE basestation and a WiFi AP with 6 users such that 5 users are within the coverage of the WiFi AP. All 6 users stream a 480P video from Youtube. We show the video streams of the 5 WiFi users in the demo video above. The first part depicts the WiFi-default scenario which represents the current network deployment where user flows are always mapped to WiFi AP if available. Since, all 5 users access their video streams through WiFi, the WiFi AP gets congested resulting in frequent stalls (re-buffering) in the video for all the 5 WiFi users. While the resource utilization of the LTE basestation is low. In the second part, we turn on ATOM which choses the flows of users 1 and 4 to be switched to the LTE network resulting in good QoE and a smooth video stream for all 5 users.

FuildNet: Software-defined Front-haul for a Cloud-driven RAN of Small Cells (2014)

This demo captures the benefit of a software-defined front-haul network in cloud or centralized radio access networks. FluidNet adapts the front-haul configurations on the fly based on observed traffic demand (heavy vs. light) and user profile(static vs. mobile) to effect different wireless transmisssion strategies (like fractional frequency reuse – FFR for increased capacity, distributed antenna system – DAS for increase coverage, etc.) on the access network. This allows it to optimize the system efficiently for various traffic scenarios in a very energy-efficient manner. When employing an FFR solution, FluidNet employs our dynamic FFR solution (FERMI) that was developed in 2012. Update: The experimental set-up shown in the demo has been upgraded from WiMAX to LTE base stations along with a more sophisticated front-haul.

FERMI: Self-organizing Solution for Interference Management of Small Cells (2012)

The video demonstrates live operation of a prototype system implementing the FERMI interference mitigation technology for small cells. The key differentiator of FERMI is to enable joint realization of spatial reuse and resource isolation to optimize network-wide performance for both interference-prone and interference-resilient clients alike. The central controller in FERMI carefully orchestrates the resource allocation in the network adapting to load changes in a software-defined manner.