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SpecNet: Spectrum Sensing Sans Frontières

Anand Iyer
April 01, 2011

SpecNet: Spectrum Sensing Sans Frontières

Anand Iyer

April 01, 2011
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  1. SpecNet: Spectrum Sensing
    Sans Frontières
    Anand Iyer*, Krishna Chintalapudi*, Vishnu Navda*,
    Ramachandran Ramjee*, Venkata N. Padmanabhan*
    and Chandra R. Murthy+
    *Microsoft Research India +Indian Institute of Science

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  2. • McHenry “NSF Spectrum Occupancy
    Measurement Project Summary”
    - Average occupancy ~5.2% in 30MHz – 3GHz
    • McHenry et.al. “Chicago Spectrum Occupancy
    Measurements & Analysis” [TAPAS 2006]
    - 17% occupancy in Chicago, 13% in New York
    • China [MobiCom 2009], Singapore [CrownCom
    2008], Germany, New Zealand, Spain…
    Spectrum Measurement Studies
    2

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  3. • McHenry “NSF Spectrum Occupancy
    Measurement Project Summary”
    - Average occupancy ~5.2% in 30MHz – 3GHz
    • McHenry et.al. “Chicago Spectrum Occupancy
    Measurements & Analysis” [TAPAS 2006]
    - 17% occupancy in Chicago, 13% in New York
    • China [MobiCom 2009], Singapore [CrownCom
    2008], Germany, New Zealand, Spain…
    Spectrum Measurement Studies
    Spectrum heavily underutilized
    3
    FM
    TV
    GSM
    CDMA
    Spectrum Occupancy in Bangalore, India

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  4. Impact
    Nov 4, 2008: FCC voted 5-0 to approve Opportunistic
    Spectrum Access (OSA) in licensed bands
    Sep 23, 2010: FCC determines final rules for the use of
    whitespaces. Removes mandatory sensing requirement
    4

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  5. • Studies conducted only at a handful of
    locations
    - Till date, only the US has allowed OSA
    • Represent static spectrum occupancy
    - Future OSA devices may require dynamic spatio-temporal
    occupancy information
    • Through evaluation of OSA proposals from the
    research community is hard
    - Little or no access to real-world data from cross-geographic
    locations
    However…
    5

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  6. • Studies conducted only at a handful of
    locations
    - Till date, only the US has allowed OSA
    • Represent static spectrum occupancy
    - Future OSA devices may require dynamic spatio-temporal
    occupancy information
    • Through evaluation of OSA proposals from the
    research community is hard
    - Little or no access to real-world data from cross-geographic
    locations
    However…
    6
    No infrastructure for measuring real-time
    spectrum occupancy across vast regions

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  7. Remote User
    Spectrum Analyzer
    “A first-of-its-kind platform that allows spectrum analyzers around the
    world to be networked and efficiently used in a coordinated manner for
    spectrum measurement as well as implementation and evaluation of
    distributed sensing applications”
    SpecNet
    7

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  8. SpecNet
    Conduct remote spectrum
    measurements
    Construction & maintenance of
    spatio-temporal usage maps
    Deploy & evaluate real-time
    distributed sensing applications
    8

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  9. 9
    Challenges
    • Expensive ($10K - $40K)
    • Limited availability
    • Support user demands
    • Applications require quick detection
    Complete tasks in minimal time

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  10. • Motivation
    • SpecNet
    – Architecture
    – Components
    – Programmability
    • Spectrum Analyzer Primer
    • Key Challenge – Resource Management
    • Applications
    Overview
    10

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  11. SpecNet Operation
    Master Server
    Slave Servers
    import xmlrpclib;
    APIServer =
    xmlrpclib.ServerProxy(http://bit.ly/Sp
    ecNetAPI, allow_none=True);
    devices = APIServer.GetDevices(None,
    None);
    Users
    Low-level
    GetDevices
    ReserveDevices
    RunCommandOnDevice
    High-level
    GetOccupancy
    GetPowerSpectrum
    FindPowerAtLocation
    LocalizeTransmitter
    11

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  12. Components
    Spectrum Analyzer
    DeviceManager
    CommunicationManager
    Master Server
    VISA
    SCPI
    Slave Server

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  13. Components
    CommunicationManager
    DatabaseManager
    Scheduler ClientManager
    Server Engine
    API Webservice
    Slave Servers
    Users
    SQL Server
    Master Server

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  14. Programmability
    • Sophisticated Users
    – ReserveDevices
    – RunCommandOnDevice
    • Policy Users
    – GetPowerSpectrumHistory
    – GetOccupancyHistory
    • Others (E.g. network operators)
    – LocalizeTransmitter
    – FindPowerAtLocation
    – GetPowerSpectrum
    – GetOccupancy

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  15. • Used to measure the spectral composition of
    waveforms
    • Frequency span (Q) and Resolution
    Bandwidth (RBW, ρ)
    Spectrum Analyzer Primer
    -120.00
    -110.00
    -100.00
    -90.00
    -80.00
    -70.00
    -60.00
    -50.00
    -40.00
    702 702.1 702.2 702.3 702.4
    Received Signal Power (dBm)
    Frequency (MHz)
    1MHz
    30KHz
    10KHz
    1KHz
    15
    Noise Floor

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  16. • Used to measure the spectral composition of
    waveforms
    • Frequency span (Q) and Resolution
    Bandwidth (RBW, ρ)
    Spectrum Analyzer Primer
    -120.00
    -110.00
    -100.00
    -90.00
    -80.00
    -70.00
    -60.00
    -50.00
    -40.00
    702 702.1 702.2 702.3 702.4
    Received Signal Power (dBm)
    Frequency (MHz)
    1MHz
    30KHz
    10KHz
    1KHz
    16
    Noise Floor
    Lowering RBW reveals details about the
    signal, and lowers noise floor

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  17. Spectrum Analyzer Primer
    • Often users are interested in determining
    which parts of the spectrum are in use.
    - Distinguish between signal and noise
    17

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  18. Spectrum Analyzer Primer
    • Often users are interested in determining
    which parts of the spectrum are in use.
    - Distinguish between signal and noise
    Lowering noise floor helps in reliably
    detecting transmissions
    18

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  19. Spectrum Analyzer Primer
    • Noise floor determines the detection range of
    a spectrum analyzer
    19
    d
    )
    log(
    10
    0
    d
    P
    P
    d



    Lowering noise floor helps in detecting
    transmitters farther away

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  20. • Motivation
    • SpecNet
    – Architecture
    – Components
    – Programmability
    • Spectrum Analyzer Primer
    • Key Challenge – Resource Management
    – When multiple devices are available, how should
    the scanning task be scheduled?
    • Applications
    Overview
    20

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  21. • Depends on Frequency Span (Q) and RBW (ρ)
    • Linear dependency on span, ∝
    Scan Time
    0
    2
    4
    6
    8
    10
    12
    0 10 20 30 40 50 60
    Time to Scan (s)
    Frequency Span (MHz)
    Analyzer 1, RBW=3KHz Analyzer 1, RBW=1KHz
    Analyzer 2, RBW=3KHz Analyzer 2, RBW=1KHz
    21

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  22. • In theory inversely proportional to RBW, ∝ 1

    Scan Time
    0.01
    0.1
    1
    10
    100
    1 10 100 1000 10000 100000 1000000
    Time to scan (s)
    Resolution Bandwidth (Hz)
    Analyzer 1
    Analyzer 2
    Analyzer 3
    In practice… piece-wise linear!
    22

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  23. a. Spectral Load Sharing
    1
    and 2
    split the frequency span
    among themselves
    If
    is the minimum scanning
    time per MHz for
    = max 1
    1
    , 2
    2
    1
    ∶ 2
    = 1
    1
    : 1
    2
    1
    2
    23

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  24. b. Geographical Load Sharing
    1
    2
    1
    and 2
    partition the region of interest
    24

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  25. SpecNet uses a numerical approximation
    to Voronoi partitioning
    b. Geographical Load Sharing
    1
    2
    1
    and 2
    partition the region of interest
    25

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  26. SpecNet uses a numerical approximation
    to Voronoi partitioning
    b. Geographical Load Sharing
    1
    2
    1
    and 2
    partition the region of interest
    Scan time depends on
    detection range as:

    T decreases super-linearly
    26

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  27. c. Geo-Spectral Load Sharing
    27
    S2
    S1
    S3

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  28. c. Geo-Spectral Load Sharing
    28
    S2
    S1
    S3

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  29. c. Geo-Spectral Load Sharing
    29
    S2
    S1
    S3

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  30. c. Geo-Spectral Load Sharing
    30
    S2
    S1
    S3

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  31. c. Geo-Spectral Load Sharing
    31
    S2
    S1
    S3

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  32. c. Geo-Spectral Load Sharing
    32
    S2
    S1
    S3

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  33. 33
    Geo-Spectral Performance
    Spectral Geographical Geo-Spectral
    Time to detect (s) 1118 1205 526

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  34. • Motivation
    • SpecNet
    – Architecture
    – Components
    – Programmability
    • Spectrum Analyzer Primer
    • Key Challenge – Resource Management
    • Applications
    – Remote Measurements
    – Primary Coverage Estimation
    – Spectrum Cop
    Overview
    34

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  35. #1. Doing Simple Scans
    GetDevices([lat,lng,r])
    GetPowerSpectrum(device_id,Fs,Fe,Nf)
    (Lat, Lng)
    r
    • SpecNet maps the
    required noise floor to
    the resolution
    bandwidth
    • Schedules scan tasks
    at each analyzer
    • Runs the job and
    returns the results
    GetDevices([lat,lng,r])
    GetPowerSpectrum(device_id,Fs,Fe,Nf)
    35

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  36. Remote Measurement Studies
    FM
    Radio
    GSM
    Stony Brook, USA 36

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  37. GSM
    FM
    Radio
    Remote Measurement Studies
    Edinburgh, UK 37

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  38. 38
    Remote Measurement Studies
    How does the FM band look like in
    Bangalore, India NOW?

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  39. #2. Spectrum Cop
    • Quickly detect violators
    - Simplicity in writing complex real-time sensing
    applications requiring coordination
     Use GetOccupancy to get an occupancy list in
    the desired frequency span
     For each occupied frequency band, do finer
    scans using GetPowerSpectrum by setting a
    lower RBW,
     Feed the results to LocalizeTransmitter to
    locate the transmitter.
    39

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  40. #2. Spectrum Cop
    • Quickly detect violators
    - Simplicity in writing complex real-time sensing
    applications requiring coordination
    40

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  41. Limitations
    41
    • Benefit to owners
    – Expensive devices
    • Attenuation
    – 5-20 dB attenuation due to buildings
    • Privacy/Security concerns
    – Fine-grained traffic monitoring/user-tracking not
    possible

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  42. Conclusion
    • FCC ruling has spurred tremendous interest,
    both in academia and industry
    • Key requirement is a measurement
    infrastructure that provides real data
    • SpecNet fulfills this need by enabling a
    geographically distributed spectrum analyzer
    network
    SpecNet requests your participation!
    Please contact Anand Iyer ([email protected])
    or Krishna Chintalapudi ([email protected])
    http://bit.ly/SpecNet 42

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