1 Sensing Techniques - IEEE 802 LAN/MAN Standards Committee



1 Sensing Techniques - IEEE 802 LAN/MAN Standards Committee
May 2007
IEEE 802.22-07/0261r1
IEEE P802.22
Wireless RANs
Outline of Informative Annex on Sensing Techniques
Date: 2007-05-31
Steve Shellhammer
5775 Morehouse Drive
San Diego, CA 92121
(858) 658-1874
[email protected]
This document contains an outline of the Informative Annex on sensing techniques.
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page 1
Steve Shellhammer, Qualcomm
May 2007
IEEE 802.22-07/0261r1
1 Sensing Techniques
This annex contains descriptions of a number of sensing techniques. A sensing technique is an implementation of
the spectrum sensing function.
There are several classifications of sensing techniques. First a sensing technique can be classified as either signal
specific or blind. A signal specific sensing technique is based on features of specific signal type. A blind sensing
technique does not rely on features of a specific signal type.
A sensing technique can be classified as either a fine sensing technique or a coarse sensing technique. A fine
sensing technique is able to detect the presence of a signal at the required signal power level. A coarse sensing
technique may not be able to detect the presence of a signal at the required signal power; however, it may still be
useful for detecting higher-power signals often is a shorter period of time.
Each sub-clause in this annex describes a specific sensing technique. The first three sensing techniques are blind
sensing techniques and the next seven are signal specific sensing techniques.
Performance for each of the sensing techniques is also included in each sub-clause. The primary performance
metric is the required SNR at which the probability of detection is greater or equal to 0.9 for all multipath
conditions. For the ATSC signals the multipath was modelled by using twelve representative signals from [1].
For each sensing technique the sensing time is also included. In many cases if the sensing time is increased the
required SNR will decrease.
Some sensing techniques are sensitive to uncertainty in the noise power. In other words the estimate of the noise
power PˆN is with Δ of the true noise power,
PˆN  PN  PE
  PE  
In some sensing techniques the detector threshold is a function of the noise power estimate, so an error in that
estimate can affect the detector performance.
If the sensing technique is sensitive to noise uncertainty then the required SNR is give for various values of the
noise uncertainty parameter Δ.
1.1 Blind Sensing Techniques
A blind sensing technique does not depend on specific signal features. There are three blind sensing techniques
described in this annex: the energy detector, the eigenvalue sensing technique and the multi-resolution sensing
Energy (Power) Detector
page 2
Steve Shellhammer, Qualcomm
May 2007
IEEE 802.22-07/0261r1
Eigenvalue Sensing Technique
Multi-resolution Sensing Technique
1.2 Signal Specific Sensing Techniques
A signal specific sensing technique relies upon specific signal features. There are seven signal specific sensing
techniques described in this annex. Six of the techniques are for ATSC signals and one of the techniques is for
wireless microphones.
ATSC Signature Sequence Correlation Sensing Technique
ATSC FFT-based Pilot Sensing Technique
ATSC PLL-based Pilot Sensing Technique
Wireless Microphone Covariance Sensing Technique
page 3
Steve Shellhammer, Qualcomm
May 2007
IEEE 802.22-07/0261r1
ATSC Pilot Covariance Sensing Technique
ATSC Spectral Correlation Sensing Technique
ATSC Cyclostationary Sensing Technique
Advanced Television Standards Committee, ATSC Recommended Practice: Receiver
Performance Guidelines, ATSC A74, June 2004
page 4
Steve Shellhammer, Qualcomm

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