System Design Issues in building a Cognitive Radio Network: IEEE 802.22

1
System Design Issues in building a Cognitive
Radio Network IEEE 802.22
What I did in my summer internship
Detection of DTV signals at very low SNR using
PN sequences
Joint work with Steve Shellhammer (Qualcomm)
Rahul Tandra (U.C. Berkeley)
2
A brief history of Cognitive Radio and IEEE 802.22

• Apparent scarcity of spectrum
• Spectrum use model flawed allocated but not
  utilized
• J. Mitola coins cognitive radio -Ph.D. thesis
  (May 2000)
• FFC issues NPRM for TV bands (May 2004)
• 802.22 is born (Sept 2004)
• How to protect the incumbent ?
• May 2006 v0.1 of the 802.22 Draft is shipped
• Sept. 2006 FCC Docket Retail by Feb 2009.
• Sensing specs. still not met, broadcasters
  dissatisfied
• Unlicensed economic model still attractive
• 3G auction 17 Bn , 34 Bn , 46 Bn
  

3
802.22 deployment scenario
802.22 Fixed wireless broadband access network
operating in TV bands (Channel 2 -51) Cellular
system, central BS, CPEs (Consumer Premise
Equipment) Targeted at but not limited to rural
deployment Strict requirements on protections of
existing licensed services
4
Incumbent protection numerology
Parameter TV broadcasting Part 74 devices
Channel detection time lt 2 sec lt 2sec
Incumbent detection threshold -116 dBm -107dBm
Required prob(detection) 90 90
Max. False alarm allowed 10 10
5
Why do we need to detect at such low SNR?
6
Why do we need to detect at such low SNR?
Shadow faded CPE
7
Why do we need to detect at such low SNR?
Shadow faded CPE
INTERFERENCE
8
Hidden incumbent problem

• An in-band Incumbent appears at a location where
  BS cannot sense it but CPE can.
• CPE wishes to inform BS about incumbent but may
  loose sync to BS due to interference from
  incumbent
• BS continues to transmit on the channel occupied
  by incumbent, causing interference to it.

9
Hidden cell problem
10
Sharing licensed spectrum
Horizontal sharing
Vertical sharing
11
Horizontal spectrum sharing

• An unlicensed user must adhere to FCC guidelines
  for protection of incumbents.
• But other unlicensed systems on the TV bands do
  not enjoy the same protection.
• This means a Cognitive Radio must not only
  detect, but also classify signals.
• Simple narrowband power detection Tandra
  Sahai does not achieve this objective

12
Part IIDetection of DTV signals at very low SNR
using PN sequences
13
Outline of Part II

• The ATSC standard and PN sequences
• Optimal approximate detectors
• Problem with detector a proposed detector
• Our detection algorithms
• Effects of multipath fading on PN correlation
• Fundamental limits in PN seq. detection
• Sensitivity to pilot estimate
• A comparison of PN and pilot detection
• Pilot spectral line detection

14
ATSC DTV numerology

• Symbol rate 10.76 Msymbols/sec
• Data Segment SYNC A 1001 pattern at the
  beginning of each segment
• Data Field SYNC An entire segment containing PN
  sequences PN511 PN63 PN63 PN63

15
ATSC framing structure
A single VSB Data Segment
The Data Field SYNC
16
Typical ATSC DTV spectrum
Pilot tone
VSB spectrum at IF
6 Mhz 1 DTV channel
f_IF 5.38 Mhz
Nyquist Rolloff 0.1152
17
Simulation Methodology
Pull out reqd. of samples
Signal at desired SNR
Detection algorithm

X
DTV signal captures (50 DTV signals captured at
high SNR, provided to us by MSTV Corp.)
Scale
Threshold calibration
Gaussian Noise
Multipath fading, noise
Test locations in NY, Washington
18
The optimal PN seq. detector

• Assumption exactly 1 PN sequence present
• Generalized Likelihood Ratio Test (GLRT) in favor
  of H1 iff
• is the MLE given by
• GLRT is

19
Approximate detector

• Neglect the signal in alternate hypothesis (low
  SNR)
• is the MLE given by
• GLRT is
• Threshold can be found easily by using

simply correlate and compare max value with g
20
A detector proposed by France Telecom

• Correlate the received signal, r(n), with the
  known PN sequence

• Use a simple low pass filter to estimate the mean
  and the variance of the correlator output

• An ATSC DTV is declared detected when

(d and c are constants set by the BS)
21
The Problem with this Detector

• The estimate of the mean approach zero even for
  noise only input
• This implies that the test statistic can approach
  zero even for a noise only input signal
• This results in false alarms. The detector
  threshold c cannot be calibrated for a given
  false alarm probability pFA.

22
Test statistic with noise-only input
Correlator output
Detector output
Output of the correlator when only filtered
receiver noise is fed as input.
Ratio shows false peaks
because mean goes very close to zero.
23
Detector operation with DTV signal Noise (SNR
0 dB)
Correlator output
Detector output
Output of the correlator over duration of 1 ATSC
field when DTV signal noise is fed as input.
The peak indicated the position of the PN
sequence.
Ratio again shows false
peaks because mean goes very close to zero
24
A simple fix

• Take absolute value of the correlator output
  before feeding as input to the detector.
• Mean cannot go arbitrarily close to zero
• The ratio is random for noise
  input.

25
Modified Detector with noise input
Correlator output
Detector output
Absolute value of the correlator output when only
filtered receiver noise is fed as input.
Ratio is random
26
Modified detector with DTV Signal Noise (SNR
0 dB)
Correlator output
Detector output
Absolute value of correlator output over duration
of 1 ATSC field when DTV signal noise is fed as
input. The peak indicated the position of the PN
sequence.
Ratio shows peak at
location of PN sequence
27
A simple test statistic

• Correlate received signal with the following
  sequence
• PN511 PN63 63 zeros PN63
• Find the tallest peak in the correlator output
• Compare its magnitude with threshold

28
Performance of a simple correlator
29
The effect of multipath
Phase reversal
48.4 ms
30
The effect of multipath
6 ms
2km dominant echo
Multiple peaks
31
The effect of multipath
6 ms
2km dominant echo
Multiple peaks
Can we utilize multipath in a positive way
? (Lessons from CDMA ?)
32
Fundamental limits in PN detection

• Using a larger received signal for detection does
  not always improve performance.

multipath fading
noise enhancement
Multipath, jitter and small variations in clock
frequency cause timing offsets resulting in
misaligned peaks by /-1,2 samples
33
Using the Data Segment SYNC

• The DATA Segment SNYC is a 1001 pattern
• Very non unique but much more frequent (every
  77.3 ms1 seg.)
• Present in noise and data quite often, but can we
  use its periodicity?
• A long sequence of the following form can be used
  for correlation
• 1001 (828 zeros) 1001 (828 zeros) N
  times

34
Performance of 1001 correlator
35
Aligning peak polarities helps! (sometimes)
36
The issue of Multiple antennas
PN sequence detection
Power detection

• The height and polarity of a PN correlation peak
  depends on the instantaneous fade.
• Two or more independent fades would provide
  different correlation peaks.
• If multiple antennas can provide statistically
  independent fading, they can help.
• A simple system would be to run 2 parallel PN
  detectors and OR their decisions. i.e.
• Miss detection (Miss detection 1) AND (Miss
  detection 2)

• Power detector is affected by shadowing
• Therefore multiple sensors located in INDEPENDENT
  shadow fades would help
• Existence of such independent CPEs not guaranteed
  (incumbents not happy with the idea)
• Multiple antenna on a single CPE do not help
  (same shadow fade)

37
Multiple antennas

• Running 2 parallel detectors
• Assumption Fading processes at two antennas are
  statistically independent
• We use fields from widely time-separated part of
  a DTV signal capture to satisfy independent fade
  assumption
• At 600 Mhz, l/2 25 cm. A practical antenna
  array can be built.

38
The effect of pilot estimation error

• The pilot frequency is used in downconverting a
  passband signal to recover the baseband transmit
  signal.
• How sensitive is PN detection to the estimate of
  the pilot frequency?
• We attempt to measure the effect of pilot
  estimation error on a PN correlation peak

39
The effect of pilot estimation error
40
The effect of pilot estimation error

• At low enough SNR even 0.2 error in pilot
  frequency estimate can be disastrous for PN
  correlation
• Pilot estimation needs to be accurate
• Why not use the pilot line as a means for DTV
  signal detection?

41
Part IIISpectral line detection of a DTV
pilotExtension of Narrowband pilot energy
detection done by Rahul Tandra
42
Power spectrum of a DTV signal at -22 dB
43
Performance of pilot spectral line detection
strong pilot

• Signal shows a strong pilot
• Detector performance is very good even at -25 dB !

Pilot energy detection Tandra
44
Performance of pilot spectral line detection
Moderate pilot

• Signal shows a moderately strong pilot
• Detector begins to fail at -21dB

45
Performance of pilot spectral line detection
Very weak pilot

• Pilot is almost completely absent from signal
• Detector begins to fail at -16 dB

46
Good, moderate and bad pilots
47
Doubling the listening time
Very weak Pilot
48
Doubling the listening time
Moderate Pilot
49
Some gains from listening longer
50
Noise Uncertainty

• For signals with weak pilots, uncertainty in the
  noise power estimate can drastically change
  performance.
• We assume D /- 1 dB.
• How does performance change?

51
Noise Uncertainty
strong pilot

• Signal shows a strong pilot
• Detector performance worse by approx 2.5 dB.
• Detector begins to fail at -24 dB

52
Noise Uncertainty
Moderate pilot

• Signal shows a moderately strong pilot
• Worse by 2 dB
• Detector begins to fail at -17 dB

53
Noise Uncertainty
Very weak pilot

• Pilot is almost completely absent from signal
• Worse by 2 dB
• Detector begins to fail at -12 dB

54
Noise Uncertainty
Very weak pilot

• Pilot is almost completely absent from signal
• Worse by 2 dB
• Detector begins to fail at -12 dB
• If we listen for double the time detector begins
  to fail at -14 dB

55
A comparison of PN detection and pilot energy
detection
PN Sequence
Pilot Energy Detection
Occurs once in 24.2 ms Always present in time
Frequency content over entire DTV spectrum Present at a specific frequency (14 known pilot freq. location)
Power in PN sequence is 1/313rd of the total energy in signal (25 dB below) Power in pilot is 11 dB below avg signal power.
? Need to sense for longer to average out noise Need to sense for shorter duration.
Cannot improve performance by sensing for infinitely long duration. Noise uncertainty results in an SNR wall effect below which signal cannot be sensed.
Requires knowledge of pilot frequency Does not require knowledge of PN seq.
Achieves signal classification. Does not achieve signal classification
56
Proposed dual mode DTV detector

• Pilot detection detects pilot and triggers PN
  detection for signal classification (confirms
  DTV)
• Multiple antennas (help both pilot and PN)
• Detection quiet periods are kept small.

57
Conclusions and future directions

• PN Correlation detector performance limited by
  multipath fading, noise and jitter.
• Difficult to accurately estimate multipath at low
  SNR.
• Multiple antennas on a single detector can help
  (statistically independent fading processes)
• Pilot spectral line detection is promising but
  does not classify signal as DTV.
• A dual mode detector utilizing
• Pilot spectral line detection for detection and
• PN correlation (with multiple antennas) for
  classification.
• can achieve quick and reliable DTV incumbent
  protection

58
The internship experience

• Worked in the standards division of Corporate RD
• Some exposure to systems, IEEE standards
  procedures (tedious).
• Focus on practical feasibility.
• Economic political side of technology.
• Overall a satisfying, busy 3 months
• (no time to work on WINLAB research
  simultaneously ?)

59
Thank you
60
Backup slides
61
Incumbent protection numerology
Required prob(detection) 90 False alarm
allowed 10
62
Hidden wireless microphones
Received power (dBm)

• An example of hidden incumbents
• Microphones are low power devices and can appear
  and disappear on a finer time scale.
• Wireless microphones are likely candidates for
  hidden incumbents.
• Propagation curves show that it Is virtually
  impossible for a BS to detect a microphone at the
  edge of a WRAN cell.

Distance from wireless mic (km)
63
The effect of pilot estimation error
64
The effect of pilot estimation error
65
Do multiple antennas help?

• The height and polarity of a PN correlation peak
  depends on the instantaneous fade.
• Two or more independent fade would provide
  different correlation peaks.
• If multiple antennas can provide statistically
  independent fading, they can help.
• A simple (suboptimal) system would be to run 2
  parallel PN detectors and OR their decisions.
  Therefore
• Miss detection (Miss detection 1) AND (Miss
  detection 2)

66
Multipath Fading
Source Gorka Guerra, Pablo Angueira, Manuel M.
Vélez, David Guerra, Gorka Prieto, Juan Luis
Ordiales, and Amaia Arrinda Field Measurement
Based Characterization of the Wideband Urban
Multipath Channel for Portable DTV Reception in
Single Frequency Networks IEEE TRANSACTIONS ON
BROADCASTING, VOL. 51, NO. 2, JUNE 2005 171