Diapositivas presentadas 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
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Tesis Maestria - Presentacion Final
1. A RFID Collision Avoidance
Framework using SDR
Bruno Fernando Espinoza Amaya
2. Basics of RFID
RFID (Radio Frequency Identification) is a technology that
allow little chips to be interrogated from distance.
Consist on both readers and transducers (Tags). It can be
both active or passive. (With or without energy source).
Features depend on the frequency used. UHF RFID is widely
used in warehousing control.
UHF RFID standard is called EPC Gen2 (ISO 1800-6C).
UHF Frequency Range for Australia is 918 – 926 MHz.
Main UHF RFID uses are warehouse management and toll
collection.
3. Slotted ALOHA for UHF RFID
Basically, the reader sends a ‘slot value’ that is received by the tags.
Then, the tags generated a random number based on the slot. When the
reader sends the same slot as the tag, the tag replies.
In UHF RFID, this is done with the QUERY and QUERY-REP
commands. The slot value is called Q and is sent in the QUERY request,
while QUERY-REP updates the slot value.
Image Source: The RF in RFID by Daniel Dobkin
4. RFID Signals Basics
PIE Encoding used by the Reader:
The reader uses a Pulse-like modulation
system that use short pulses for zeros
and larger pulse for ones.
Encoding used by the
Tags: The tags uses two
types of modulation: A
Manchester-like one (FM0)
and the product of this code
with a clock source. (Miller 2,
4 and 8).
Image Source: The EPC Gen2 Specification
5. RFID Inventory (Reading) Process
Collisions can only happen on the RN16 stage, as all tags have a
unique EPC code.
Image Source: The EPC Gen2 Specification
7. RFID Signals - Collisions
Real signals recorded from a Tag at 800 KS/s.
8. Software-defined Radio and RFID
An open source SDR RFID reader was used for
this project.
The reader originally supports only the USRP1
device and GNU Radio 3.3.
The reader allows to control all the aspects of the
RFID decoding process.
Reader was ported to the latest GNU Radio
Version (3.7), allowing other SDR devices to be
used.
Testing on this port was done using the bladeRF
and the USRP1 device.
9. A Framework for RFID Collision
Recovery
A framework for testing FastICA was developed in the Matlab
language. (Octave compatible)
Consist of RFID Signal Generator, RFID Listener and FastICA
Model.
The developed Listener is able to decode real RFID signals
captured with a SDR device, as well as the signals generated
by our signal generator.
The developed Listener will obtain all the information of the
signal from the signal itself, parsing all the parameters.
The FastICA model was developed to test how FastICA
performs under a variety of circumstances. (Such as SNR,
phase shift and amplitude changes).
10. FastICA Algorithm / Blind Signal
Separation
Images from Kyushu Institute of Technology.
11. FastICA Algorithm
Is an algorithm that implements Blind Signal
Separation by separating a signal into its additive
components.
Similar in nature to PCA.
Signals must be statistically independent and non
Gaussian.
The way on how this components are mixed into
the signals is expressed via a Mixing Matrix.
FastICA recovers this matrix.
It requires at least as many input signals as
sources to work properly.
12. FastICA and RFID Collision Recovery
Research by Sun Yuan shows that FastICA can be used for
recovery information from RFID-like signals generated by an
FPGA.
FastICA recovery possible as the values generated for each
tag are independent from each other.
Only certain type of collisions can be recovered.
Signal need to be low-pass filtered to supress high frequency
components that could interfere. This is done by using
Median Filter.
The experiments tests this recovery capability on real RFID
signals recorded with a SDR device.
The developed RFID Listener is able to perform FastICA
when feed with 2 recordings from the collisions.
13. RFID Collisions Recovery
Signal A Signal B Additive
Result
A A 2A
A -A 0
-A A 0
-A -A -2A
A and –A represent the 2 possible levels that the Tag signal could
have. When two opposite levels collide in time, they cancel out, so the
information cannot be recovered.
However, because we are using multiple antennas, those two levels
will have amplitude changes and some delay due to multipath.
Because of this reasons, information can still be recovered.
Image from the Sun Yuan Thesis.
15. RFID FastICA Model
Test the viability of FastICA for collision recovery,
under different scenarios.
Simulation over 10,000 tags readings.
Model simulates amplitude changes, AWGN noise
and phase shift.
Tag Error Rate is calculated under different AWGN
noise scenarios, for each of the 4 available
modulation types.
17. USRP1 Model
A testing scenario for FastICA using the USRP1
device was set.
Single TX and 2 RX, using the RFX-900 boards.
Sampling Rate at 2 MS/s.
Ported version of the RFID reader which supports
capture from multiple antennas.
The developed Listener reads the captured data
and perform the FastICA recovery.
Reader Q=0 and Tag modulation is Miller M=2.
Tested with 1, 2, 3 and 4 tags.
23. Discussion
FastICA can separate RFID collision signals, when
provided with more than 1 signal recording.
Miller schemes perform best in the simulation of
collisions, with Miller M=2 as the best performance.
FM0 performs worst.
USRP1 decoding with FastICA can recover clean
signals up to 3 tag collisions.
Some collisions in the experiment were unable to
be recovered.
Is recommended to have more antennas to
maximize the success rate.