Spectrum Sensing

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• Spectrum Sensing
• Marjan Hadian

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Outline

• Cognitive Cycle
• Enrgy Detection
• Matched filter
• cyclostationary feature detector
• Interference Temperature
• Spectral Estimation
• Hidden node problem
• Cooperative detection
• detection methods
• log-likelihood combining
• weighted gain combining

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Cognitive Cycle

• Mitola calls cognitive radio cycle cognitive
  radio continually observes the environment,
  orients itself, creates plans, decides, and then
  acts

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• Spectrum Sensing
• A cognitive radio monitors the available spectral
  bands,captures their information, and detects the
  spectrum holes.
• frequencies usage.
• mode identification.

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• Enrgy Detection
• Where T calculated from
• most important problem of this, is which one
  called SNR wall. This problem comes from
  uncertainty.
• SNR wall is a minimum SNR below which signal
  cannot be detected and formulas no longer holds

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• Matched filter
• it maximizes SNR. For implementation of matched
  filter cognitive radio has a priori knowledge of
  modulation type, pulse shaping.
• cyclostationary feature detector
• The main advantage of the spectral correlation
  function is that it differentiates the noise
  energy from modulated signal energy.

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Interference Temperature

• As additional interfering signals appear the
  noise floor increases and then unlicensed devices
  could use that particular band as long as their
  energy is under mention noise floor
• 
  where
  Joules per Kelvin

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Spectral Estimation

• parametric spectral estimation
• Non-parametric spectral estimation
• Periodogram Spectral Estimator (PSE)
• Blackman-Tukey Spectral Estimator (BTSE)
• Minimum Variance Spectral Estimator (MVSE)
• Multi taper Method (MTM)
• Filter Bank Spectral Estimator (FBSE)

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Hidden node problem

• Traditional detection problem (a) Receiver
  uncertainty and (b) shadowing uncertainty5

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Cooperative detection

• prevent the hidden terminal problem also mitigate
  the multipath fading and shadowing effect
• Information from multiple SUs are incorporated
  for primary user detection.
• Implementation
• Centralized manner
• distributed manner

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How SU provide its observation to other nodes?!

• This transmission can overlap to the air
  interfaces already present in the environment, so
  it can change the nature of observations and make
  new problems. In order to solve this problem
  several solutions suggested
• two distinct networks are deployed separately
• the sensor network for cooperative spectrum
  sensing and the operational network for data
  transmission. This method implemented in central
  manner5
• Sharing the analysis model in an off-line method
  when in the environment no SUs is observing the
  radio scene1

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• Without consideration of exchanging method, we
  assume that the observation of SU i is due to its
  position and to the state of radio source, but
  not to the observation of other SU j and .Thus we
  assume that, independent measurements for each
  SUs is presented either in a centralized or
  distributed manner. Now we review two detection
  methods
• log-likelihood combining
• weighted gain combining

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• log-likelihood combining
• Assume that is the vector of SUs
  energy detector output, then we can write
  likelihood ratio test(LRT) as
• weighted gain combining
• where
  and

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• Thanks for your attention.
• Questions?