Hello, my name is Sultana's from Carnegie Mellon University, and today I am presenting
our paper on developing an ultra low power wi fi tag that works with existing Wi-Fi
infrastructure. In a smart world, there are many things that you want to find that are
not powers such as a bottle pill or a package in a warehouse, RFID is a specific
technology developed for tracking and identifying objects.
There's a battery free tag like a barcode that attaches to the object.
It receives the signal from the reader and reflects back and modulated version of it.
However, because of the deployment complexities, we don't really have RFID
readers in every building, so we ask what if it is an attack that can be detected and
localized with any Wi-Fi connected device?
Nowadays, we have free Wi-Fi almost in any building like homes, restaurants, hotel
rooms. So you can imagine having these tags attached to your wallet, to chain tools,
toys, and then you can just use the Wi-Fi in the building and your personal Wi-Fi devices
like phone or tablet to find them.
However, the main challenge is that the tag reflection is multiple times weaker than the
line of sight or other reflections in the environment, causing a high dynamic range.
This is problematic specifically in wi fi setups where we have separate Wi-Fi
transmitter receiver and no time synchronization between them.
Other papers on why flyback is gathering solve this problem by designing a tag that
reflects the frequency shifted version of the received signal so it won't interfere
with other multiplier signals.
But this requires the transmitter receiver to operate in different wireless channels.
And that's not how Wi-Fi networks work.
The whole idea here is to piggyback tag detection on top of ongoing Wi-Fi packets.
So the main questions we're trying to answer here are how can we backscatter ambient Wi-Fi
traffic without modifying the normal operational Wi-Fi networks, how we can
overcome the dynamic range problem and separate the tag reflexion from other
multiple signals?
And finally, how to locate the type from a single receiver like your phone or tablet.
First, we propose a fully asynchronous hybrid architecture where we separate the
source of power at the time from the backscatter signal we use for tag detection.
We design the tag as simple and low power as possible that it can constantly be on and
modulate any receive signal.
Then the Wi-Fi devices start their normal communication and they take independently
modulated. The reflection from the receiver then captures the signal measurements in the
physical layer known as channel state information and searches for the tag.
So all we need at the peg is a mark switch and a Wi-Fi antenna.
When the switches off the receiver signal will be observed by the load attached to the
antenna. And when the switch is on, the antenna will be shorted and all the receiver
signals will reflect back.
And that's how the tag is communicating with the reader, sending zero one bids by
switching on and off.
But how can we separate the tag reflexion from other multiplier signals to answer this
question? Let's start with an analogy that explains the high level intuition.
Imagine you're out in a dark night and all.
You can see some weak lights in distance that you may not even notice.
However, if one of these lights start blinking, it gets your attention.
And that's basically the intuition we're using to detect a very specific reflection
from the Tegana signal processing pipeline.
So the blinking in the previous example is basically the modulation of the tag
reflection across packets.
But pay attention that because of the asynchronous architecture we talked about
earlier, we don't really know when the time is switching on and off.
So to extract that type reflection, we use a super resolution algorithm that takes
measurements of the signal from multiple packets and combine them together to estimate
the parameters of all multiplier signals, including the reflection.
But why does it work?
Please refer to our paper to find the answer to this question and many others untag
discovery. By the end of this phase, we have the detector that we estimate that it's angle
of arrival and the departure of light, Panetoz.
Now let's see how we can locate the tag from a single point here.
All we need is a direction and the length of the reflective path and the line of sight
between the Wi-Fi devices and the tag to form a triangle and solve it for the time
location. So instead of using multiple receivers for triangulation, we are using the
multipurpose reflection from the tag to form this triangle.
We implemented the attack by multiple prototypes using Off-The-Shelf components as
well as an integrated PXP with a custom designed patch antenna.
We developed the localization system on top of it and tested it in a hundred different
scenarios in the lab and a large arena space.
And we say that we can achieve a median accuracy of about 30 centimeter to locate
these tags in the to the space.
We also develop on augmented reality interface that collects the wireless signals
and locate any number of activities and show it to the user with an air overlay.
Here's another setup with multiple tags, and as you can see, we can detect and localize
all of them at the same time, each of these tags have a different modulation rate, and
that's what we are using to differentiate them from each other.
So to summarize, Pacci is an ultra low power Wi-Fi tag that is compatible with the Wi-Fi
networks in any building to find the objects, we can use any Wi-Fi link in the
building. And such an approach can be more wireless medium into an intelligent sensing
platform in mind.
Wabbits.