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Cognitive radio experimentation with VESNA platform
Miha Smolnikar
Jozef Stefan Institute
ICTP School on Applications of Open Spectrum and White Spaces Technologies
Concept
• A HW/SW platform for wireless sensor networks• High processing power and low energy consumption• Sensor node & concentrator/gateway capability• Battery, solar or external power supply• Multiple communication technologies• Extensive portfolio of sensors and actuators• JTAG debug interface• OS ports: Contiki, NuttX, (RIOT)• Libraries ports: Arduino (Maple, Spark, …), panStamp, OpenWSN, Wiselib, SensLAB …• Arduino compatibility
• Development, prototyping and testbed platform
• Design files & source code• https://github.com/sensorlab/ 4
Supported …… sensors• Temperature
• Air pressure
• Pressure (absolute, differential)
• Humidity
• Luminance
• Acceleration
• Gyroskop
• GPS/position
• Microwave radar
• Lightning
• Microphone (intensity, spectrum)
• Radio spectrum (ISM, UHF)
• Voltage
… communication interfaces• IEEE 802.15.4
• ZigBee
• 6LoWPAN
• Wireless M-BUS
• Bluetooth 4.0
• Wi-Fi
• GSM/GPRS
• Ethernet
… peripherals• RS-232
• RS-422/485
• CAN
• USB (slave)
• SPI
• I2C
• 1wire
• SDIO
• 4…20 mA
• 1-10 V
…• Current (AC/DC, Hall,
resistor)
• Power quality (parametrization)
• RFID, NFC
• Ultrasound
• IR (PIR, on-off, distance, temperature)
• Capacitive/inductive touch/distance
• Color
• Reflectance
• Hall
• Load cell (weigh)
• Weather station• Rainfall rate
• Wind speed & direction
• Sun radiation (UV, VIS)
…• Gas / Particles
• CO2
• VOC
• NO, NO2, CO, O3, SO2
• PM, Pollen
• Camera
• …
5
Modularity
• VESNA=SNC+SNR+SNE• SNC = 7 cm x 5 cm
• SNR = 3 cm x 5 cm
• SNE = 7 (10) cm x 5 cm
• Existing modules• SNC-STM32
• SNR-TRX, SNR-MOD
• SNE-PROTO, SNE-WG, SNE-WLG, SNE-ISMTV, SNE-ESHTER, SNE-SENS, SNE-AQA, SNE-AMIO, SNE-SH, SNE-BEECO, SNE-PMC
Sensor Node Core (SNC)data acquisition and processing,versatile power supply
Sensor Node Radio (SNR)communication withinthe sensor network
Sensor connector
Power supply and RS-232
USB
SDIO
Battery / solar
Antenna
Radio connector
Sensor Node Expansion (SNE)application specific HW, firmware debugging over JTAG
6
SNC-STM32
• Microcontroller• ST STM32F103xx
• ST STM32L1zzxx
• MRAM
• Instrumentational amplifier
• External / battery / solar power supply + charger
• USB, RS232/UART, SPI, I2C, 12-bit DAC, 12-bit ADC
• SD card slot
7
SNR-TRX (transceiver)
• 315/433 MHz, 868/915 MHz• TI CC1101
• Atmel AT86RF212 (IEEE 802.15.4)
• 2.4 GHz• TI CC2500
• Atmel AT86RF231 (IEEE 802.15.4)
• nRF8001 (BLE)
• Range extenders• TI CC1190 (sub-GHz) / TI CC2590 (2.4 GHz)
8
SNR-MOD (OEM module)
• Digi XBee (ZigBee, proprietary)
• Atmel ATZB-900 (ZigBee)
• Atmel ATZB-24 (ZigBee)
• Telit • ME50-868, (ME50-169) (WMBUS)
• LExx, NEexx (pin compatible, proprietary)
• ZExx-2.4 (pin compatible, ZigBee)
9
SNE-WG (wired gateway)
• Lantronix Xport / Digi ConnectMe (Ethernet)
• Power over Ethernet
• CAN
• RS-485/422
10
SNE-WLG (wireless gateway)
• GainSpan GS1011 (WiFi)
• BlueRadio BR-LE4.0 (Bluetooth 4.0 )
• Telit GL865 (GSM/GPRS)
• uBlox MAX-6G (GPS)
• Power supply
11
SNE-ISMTV (spectrum sensing) 1/2
• SNE-CREWTV
• One PCB with several placement options1. VHF/UHF (TVWS)
• NXP TDA18219HN silicon tuner
• Analog devices AD8307 demodulating logarithmic amplifier
• RF input range: 420 – 870 MHz
• Bandwidth: 1.7 MHz, 8 MHz
• Linearity: ±1 dB
• Dynamic range: 60 dB
12
SNE-ISMTV (spectrum sensing) 2/2
2. Sub-GHz ISM (315, 433, 783, 868, 915 MHz)• TI CC1101
• Receiver sensitivity: -112 dBm @ 868 Mhz
• Programmable output power: 12 dBm
3. 2.4 GHz ISM• TI CC2500
• Receiver sensitivity: -104 dBm
• Programmable output power: 1 dBm
• IEEE 802.15.4 transceiver (ISM 868 MHz)• Atmel AT86RF212
13
SNE-ESHTER (spectrum sensing) – UNDER DEVELOPMENT
• Embedded Sensing Hardware for TVWS Experimental Radio (ESHTER)• http://www.tablix.org/~avian/blog/articles/talks/next_generation_tv_band_r
eceiver_for_vesna.pdf
• Motivation for redesign• Experiment with advanced spectrum sensing methods (require access to
signal magnitude and phase)
• Higher frequency resolution for energy detection (wireless microphones occupy ~200 kHz of spectrum, 1700 kHz narrowest TDA18219HN channel setting)
• Practical problems (form-factor, EMI noise cancellation)
14
SNE-ESHTER (spectrum sensing) – UNDER DEVELOPMENT
15
• Going beyond energy detection• Covariance Absolute Value detector
• Eigenvalue detector
• Information-theoretic detection
• Compressive sensing
• Block diagram
Projects
• Photovoltaic power plant monitoring (Telekom Slovenije)• http://sensors.ijs.si/
• Air quality (FP7 CITI-SENSE)• http://www.citi-sense.eu/
• Sensor support for unexpected & temporary events (FP7 ABSOLUTE)• http://www.absolute-project.eu/
• Robust network infrastructure for smart distribution grids (FP7 SUNSEED)• TBD
• Spectrum sensing and cognitive radio (FP7 CREW)• http://www.crew-project.eu/
17
PV power plant monitoring
• Systematically investigate the pros and cons of different PV technologies (amorphous & crystalline silicon), effect of panels deployment (S, E, W orientation) and impact of environment (weather) conditions
• Sensorics on 5 sets of PV panels• Light intensity in different spectrum (UV/VIS/IR)• Solar pannel U/I characteristic • Performance of inverter MPP tracker• Temperature of a PN junction • Environment conditions (context)
• 7 VESNA sensor nodes, 1 VESNA gateway, ZigBee network @ 868 MHz
18
Air quality
19
• Static indoor unit (Wi-Fi)• T, rH, PM• Gas: CO2 (CO2-IRC-A1), VOC, NH3 (B1)
• Static outdoor unit (Wi-Fi)• Weather: T, rH, wind speed & direction, rainfall rate• Solar radiation: VIS, IR• Lightning • Gas: NO, NO2, SO2, O3, CO (ISB-B4)
• Portable unit (Wi-Fi / BLE)• VESNA SNE-AQA
• T, rH, accelerometer• Gas: NO2, O3, CO (AFE-A4)
Spectrum sensing testbed location
• Deployed in the city of Logatec, Slovenia
• Based on wireless sensor network
• Sensor nodes are (mostly) installed on public light poles
• Infrastructure rewiring ensures 24/7 power supply
• Used to support the experimentally-driven research20
Spectrum sensing VESNA nodesSNE-ISMTV
868 MHz TRX
CC1101
TV UHF RX
TDA18219HN
SPI, GPIO
2.4 GHz TRX
CC2500
868 MHz TRX
AT86RF212
SNC v1.0 SNR-MOD v1.0
ATZB-900-B0
custom code
or
Contiki + custom code
SP
I / UA
RT
21
Spectrum sensing infrastructure
• 50+ sensor nodes are deployed in 3 clusters• City center (23)• Industrial zone (27)• JSI campus
• Management network ZigBee @ 868 MHz, Ethernet gateway
green – UHF, blue - ISM 868 MHz, red - ISM 2400 MHz, yellow - reserve locations23
FP7 project CREW
• Cognitive Radio Experimentation World• http://www.crew-project.eu/• Establish an open federated test platform• Research on advanced spectrum sensing,
cognitive radio and cognitive networking • Horizontal and vertical spectrum sharing in
licensed and unlicensed bands
• LOG-a-TEC• Outdoor• ISM/TVWS• Spectrum sensing and
cognitive radio
25
LOG-a-TEC spectrumsensing infrastructure• 3 clusters
• Sensor nodes (23+27+1)• SNC-STM32
• SNR-MOD (ZigBee mesh @ 868 MHz)
• SNE-ISMTV
• Gateways • SNC-STM32
• SNR-MOD (ZigBee mesh @ 868 MHz)
• SNE-WG
Cit
y o
f Lo
gate
cJS
I Cam
pu
s /
Lju
blja
na
26
LOG-a-TEC spectrum sensing infrastructure
• Web access portal
• User administration and scheduling
• Python library
• SSL connection and protocol proxy
• GRAS-RaPlaT
27
LOG-a-TEC testbed access portal• Testbed access portal available
at www.log-a-tec.eu allows to• Show node status
• Choose particular cluster
• Perform an experiment • Described as a sequence of GET and POST requests
• Remote (over-the-air) reprograming
28
LOG-a-TEC testbed access portalExecution of predefined experiments (sequence of GET and POST requests / Python script)
32
VESNA spectrum sensing experimentation
• VESNA spectrum sensing software
• A batch of pre-prepared spectrum sensing profiles is available
• Once profile is selected VESNA sensor node is accordingly configured
• Experiment is run according to spectrum sensing specifications
• Results are saved locally on the SD card and sent in batches to the server
34
Sensing profile• Frequency band• Channel bandwidth• Averaging• …
GRASS-RaPlaT experimentation
• Integrated Radio Planning Tool (RaPlaT)based on open-source GIS system GRASS • Experiment planning• Tx radio coverage calculation • Visualization • Supporting REM estimation
• Incorporating • Digital Elevation Model• Clutter file• Six path loss prediction models• Ray-tracing approach for rural
and urban environments
35http://www-e6.ijs.si/en/software/grass-raplat
Experimentation in LOG-a-TEC
1. Remote experiments (RE)• Define your experiments• Ask for an account to LOG-a-TEC• Use the Python scripts https://github.com/sensorlab/vesna-alh-tools to develop
your own experiment• Use the web portal to run pre-defined experiments and simulations
https://crn.log-a-tec.eu/
2. On site experiments (OE)• If the experiments requires mobile equipment or a particular type of equipment to
be brought on site
3. A mix of remote and on-site experiments (ME)• A combination of the above
36
Acknowledgements
• Thanks to colleagues in SensorLab who greatly contributed to this work.
• The work reported in this presentation has been partially funded by the European Community through the FP7 project CREW (FP7–258301).
40
Thanks for attention!
http://sensorlab.ijs.si/