Poster presentado para el grado de Magister en Ciencias de la Computacion en University of Queensland. Titulo de la Tesis: A RFID Collision Avoidance Framework based on SDR

1. Project Background:
Motivation:
In high density RFID systems, collisions
happens when multiple tags reply
simultaneously. In current systems, many
methods to prevent collision exist, but nothing
can be done once the collision happens. This
results in overhead, as the reading process for
the tags collided must be started again.
A promising solution that can recover
information from collision data exist: Blind
Signal Separation.
Blind Signal Separation:
Blind Signal Separation (BSS) is a technique
that allows separating multiple signals provided
multiple recordings of such signals exist. It’s
commonly used for de-noising bio-physical
signals and for audio processing.
Some theoretical research about the
application of BSS in RFID exists, however this
has yet to be performed on real signals coming
from RFID tags.
FastICA Algorithm:
FastICA is an efficient algorithm that
implements BSS, focused on separating a
signal into its additive components, given that
the 2 signals are statistically independent. For
this project is used to recover the RFID signals
and pick the best decodable possible.
A RFID Collision Avoidance framework using SDR
Bruno Espinoza Amaya under supervision of Dr. Konstanty Bialkowski
Design Process:
RFID Framework:
Using an existing open source software-defined
radio (SDR) RFID Reader, a framework
consisting on FastICA models, RFID Listener
and a RFID Signal Generator was constructed
to test the viability of FastICA for recovering
information from RFID tag collisions.
Using SDR:
The existing open source SDR reader was
ported to the last version of GNU Radio (3.7.3
at this moment), as it was untouched for years.
Support for new SDR devices besides the
USRP1 was added.
Using this reader and RFID tags, an
experiment for testing feasibility of FastICA is
done using the USRP1.
Results:
In simulation, the performance of FastICA
method was tested in terms of recovery rate
under different levels of noise. Also, the
available modulation methods for tags were
tested, in order to find the one which has best
potential for collision recovery.
For this simulation, Miller schemes were found
to perform better in the FastICA recovery than
the FM0, with Miller M=2 being the one which
perform best.
In the experiment, collisions recorded from real
tags using the USRP1 device were tested, and
information was recovered from 2, 3 and even
4 tag collisions.
Figure 01: Result of the FastICA recovery simulation of a collision between 2 tags.
Figure 02: Testing environment with the USRP1 device and 3 antennas (2 RX and 1 TX). A
collision is recoreded and then the tag is recovered using FastICA by software.