Testbed for Wireless Adaptive Signal Processing Systems György Orosz, László Sujbert, Gábor...
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Transcript of Testbed for Wireless Adaptive Signal Processing Systems György Orosz, László Sujbert, Gábor...
![Page 1: Testbed for Wireless Adaptive Signal Processing Systems György Orosz, László Sujbert, Gábor Péceli Department of Measurement and Information Systems Budapest.](https://reader030.fdocuments.net/reader030/viewer/2022032415/56649f055503460f94c1a984/html5/thumbnails/1.jpg)
Testbed for Wireless Adaptive Signal Processing SystemsGyörgy Orosz, László Sujbert, Gábor Péceli
Department of Measurement and Information SystemsBudapest University of Technology and Economics, Hungary
Instrumentation and Measurement Technology Conference – IMTC 2007Warsaw, Poland, May 1-3, 2007
![Page 2: Testbed for Wireless Adaptive Signal Processing Systems György Orosz, László Sujbert, Gábor Péceli Department of Measurement and Information Systems Budapest.](https://reader030.fdocuments.net/reader030/viewer/2022032415/56649f055503460f94c1a984/html5/thumbnails/2.jpg)
Wireless signal processing Advantages of Wireless Sensor Networks (WSNs)
Easy to install Flexible arrangement
Wireless signal processing Difficulties of utilization of WSN:
Data loss Undeterministic data transfer Limit of the network bandwidth
Purpose of the testbed Considerations in the design
Hardware structure Adequate application
Realistic demands Exploits the resources
![Page 3: Testbed for Wireless Adaptive Signal Processing Systems György Orosz, László Sujbert, Gábor Péceli Department of Measurement and Information Systems Budapest.](https://reader030.fdocuments.net/reader030/viewer/2022032415/56649f055503460f94c1a984/html5/thumbnails/3.jpg)
ANC as test application Principles of Active Noise Control (ANC) Why ANC?
Inherently MIMO systems: plenty of sensors Plant: acoustic system
Scalable Linear Exist everywhere
Various algorithms: No HW modification Comparability of structures
Easy to build and cheap Identification: characterization of signal path
![Page 4: Testbed for Wireless Adaptive Signal Processing Systems György Orosz, László Sujbert, Gábor Péceli Department of Measurement and Information Systems Budapest.](https://reader030.fdocuments.net/reader030/viewer/2022032415/56649f055503460f94c1a984/html5/thumbnails/4.jpg)
Plant to be controlled: acoustic system
Noise sensing:
Berkeley micaz motes
Actuators: active loudspeakers
Gateway: network DSP Signal processing:
DSP board ADSP-21364 32 bit floating point 8 analog output channels 330 MHz
motes
System configuration
mote1
moteG
DSP board
reference signalgateway
mote
codec DSP
mote2
moteN
microphone
![Page 5: Testbed for Wireless Adaptive Signal Processing Systems György Orosz, László Sujbert, Gábor Péceli Department of Measurement and Information Systems Budapest.](https://reader030.fdocuments.net/reader030/viewer/2022032415/56649f055503460f94c1a984/html5/thumbnails/5.jpg)
Research fields related to the testbed Signal processing adaptation to WSN Synchronization Data transmission
Effective algorithms Data compression
Distributed signal processing
MIMO plant
sensor1
sensor2
sensorN
WirelessNetwork
WirelessNetwork
Signalprocessing
Control signals
feedback signalssensors
Synchronization Distributed signal processing
Data transmission Error handling Signal processing
Sync.(WSN DSP)
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Results 1. Implemented ANC algorithms Synchronization algorithm in WSN
Principles of operation
sensor mote
DSP board
gateway mote
active loudspeaker
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Results 2. Deterministic network operation Implicit synchronization messages
Synchronization with continuous data flow No extra load for network
DSP
mote2 mote3
gateway
mote1 mote4
: data messages
: token
: synchron message
Network topology
![Page 8: Testbed for Wireless Adaptive Signal Processing Systems György Orosz, László Sujbert, Gábor Péceli Department of Measurement and Information Systems Budapest.](https://reader030.fdocuments.net/reader030/viewer/2022032415/56649f055503460f94c1a984/html5/thumbnails/8.jpg)
Results 3.
Data transmission methods
Transmission of
row data 1.8 kHz sampling frequency on
the motes Synchronization of WSNDSP LMS and observer based ANC
algorithms Bandwidth restriction:
about 2-3 sensors
Transformed domain
data transmission 1.8 kHz sampling frequency on
the motes Transmission of Fourier-
coefficients Increased number of sensors:
8 sensors (expansion possible)
![Page 9: Testbed for Wireless Adaptive Signal Processing Systems György Orosz, László Sujbert, Gábor Péceli Department of Measurement and Information Systems Budapest.](https://reader030.fdocuments.net/reader030/viewer/2022032415/56649f055503460f94c1a984/html5/thumbnails/9.jpg)
Conclusions Platform for testing wireless systems
Application: ANC Components:
Berkeley micaz motes ADSP-21364 floating point DSP
Main difficulties Data transmission Synchronization
Some codes and technical details available at http://home.mit.bme.hu/~orosz/wireless
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Future work Improvement of the website
http://home.mit.bme.hu/~orosz/wireless Discover the limits of the system
Sensor network: bandwidth limit DSP: computational and memory limits
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![Page 12: Testbed for Wireless Adaptive Signal Processing Systems György Orosz, László Sujbert, Gábor Péceli Department of Measurement and Information Systems Budapest.](https://reader030.fdocuments.net/reader030/viewer/2022032415/56649f055503460f94c1a984/html5/thumbnails/12.jpg)
Synchronization 1
Mechanism of the synchronization
reference timer
S/H controller tuneable timer
–
Ta
Tloc
IT IT
fquartz_2fquartz_ref
Ndiv
reception time of the messages
reference mote
mote to be synchronized
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Synchronization 2
Graph of the reception time of synchronization messages
50 100 1500
1
2
3
4
5
x 10-4
time [sec]
Tx [
sec]
unsynchronized
synchronized
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Synchronization 3
Tdiff = ∆tsend + TSend – Tloc2
Send(packet)
Receive(packet)
moteref
motei
Sampling time instants
tsend
trec
TSend
tsamp_r
tsamp_i
t
tTloc2
∆tsend
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Synchronization 4
t
t
t
Ts
T1_a
T1_b
T1_c
T2_a
T2_b
T2_c
T1_ref T2_ref
Ts
Tloc.a_1
Tloc.b_1
Tloc.c_1
Tloc.a_2
Tloc.b_2
Tloc.c_2
a)
b)
c)
Tloc.a_1 = Tloc.ref
Tloc.b_1 > Tloc.ref
Tloc.c_1 < Tloc.ref
Tloc.ref : the reference value of Tloc.x_y that is the time difference between the sampling time
instant and reception time of the synchronization message
reception time instant of the synchronization message
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Synchronization 5
Indirect proof for synchronization
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Network timingt
t
t
t
t
Tp
DSP
gateway
mote0
mote1
mote2 Twin_0 Twin_1 Twin_2 Twin_0
Twin_i: time gap of ith moteTp: one network period
: data messages: synchronization messages