February 2006
doc.: IEEE 802.22-06/0032r0
Analysis of Proposed Sensing Schemes
IEEE P802.22 Wireless RANs
Date: 2006-03-06
Authors:
Name
Soo-Young Chang
Company Address
Huawei
6000 J Street, Dept
EEE, Sacramento,
CA 95819-6019
Phone
email
1-916 278 6568 [email protected]
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>
Submission
Soo-Young Chang, Huawei
Slide 1
February 2006
doc.: IEEE 802.22-06/0032r0
ANALYSIS
OF PROPOSED SENSING
SCHEMES
FOR IEEE802.22 WRAN
Soo-Young Chang
Huawei
Submission
Soo-Young Chang, Huawei
Slide 2
February 2006
doc.: IEEE 802.22-06/0032r0
INTRODUCTION
Submission
Soo-Young Chang, Huawei
Slide 3
February 2006
doc.: IEEE 802.22-06/0032r0
BACKGROUND
• Spectrum usage of TV broadcast industries
– the average TV market in the United States uses approximately 7 highpower channels of the 67 that it is allocated. This leaves an abundance
of free channels that could be used for wireless access.
– With both the House and the Senate having recently passed bills
requiring television broadcasts to switch from analog to digital sometime
in early 2009, the 700-MHz band (channels 52 to 69) will be cleared of
programming and moved to lower frequencies (channels 2 to 51). The
700-MHz band will be set aside for public-safety emergency
transponders and for bidding by wireless networks.
 in this contribution only channels 2 to 51 are considered.
• Three possible ways suggested in one article to protect interference
with incumbent users
– Listen-Before-Talk (LBT)
– Geolocation/Database: GPS receivers installed in CPEs
– Local beacon: locally transmitted signal used to identify incumbent
users
Unused Digital TV Channels Could Increase U.S. Wireless Access, Federal action could allow unused channels at lower frequencies to be used
for unlicensed wireless networks, Eric S. Crouch, Medill News Service, PC World, Saturday, November 19, 2005,
http://www.washingtonpost.com/wp-dyn/content/article/2005/11/18/AR2005111800083_pf.html
Submission
Soo-Young Chang, Huawei
Slide 4
February 2006
doc.: IEEE 802.22-06/0032r0
CHANNEL AVAILABILITY
• Questioned whether there will be significant channel availability
for unlicensed use in major urban areas during the DTV
transition.
– There is likely to be substantial channel availability during
transition.
– The issue of channel availability during the DTV transition is likely
to be short-lived.
– In rural areas, there is spectrum available now and there will be for
the foreseeable future.
• Bill Rose’s email to 22 email reflector, Wed, November 23, 2005
10:05 am
– “The analysis shows that even in congested markets like Dallas/Ft.
Worth, 40 percent of the TV channel spectrum will remain unused
after America's DTV transition. In more rural markets like Juneau,
Alaska, as much as 74 percent will be available.”
Submission
Soo-Young Chang, Huawei
Slide 5
February 2006
doc.: IEEE 802.22-06/0032r0
INTERFERENCE WITH INCUMBENT
USERS
•
•
•
•
•
•
•
•
73 million TV sets
DTV disruption issue
Public safety interference
Newsgathering and sports programming production
Interference with theaters, churches, and school events
Will the proposal “permanently chill investment” in spectrum?
Cable services
“Eglin AFB incident”
Submission
Soo-Young Chang, Huawei
Slide 6
February 2006
doc.: IEEE 802.22-06/0032r0
TV CHANNELS IN U.S.
• Currently with 6 MHz bandwidth for each channel,
– VHF low band:
– VHF high band:
– UHF band:
Chs 2-6
Chs 7-13
Chs 14-69
54-88 MHz
174-216 MHz
470-806 MHz *
Chs 2-6
Chs 7-13
Chs 14-51
54-88 MHz
174-216 MHz
470-698 MHz *
• After DTV transition,
– VHF low band:
– VHF high band:
– UHF band:
• In this contribution, channels after DTV transition are
considered.
– Enough channels are expected to be maintained for WRAN.
• For other bandwidths – 7 and 8 MHz – the system concept can
also be applied by changing system parameters.
* Ch 37 is reserved for radio astronomy
Submission
Soo-Young Chang, Huawei
Slide 7
February 2006
doc.: IEEE 802.22-06/0032r0
SPECTRA OF TV CHANNELS
NTSC signal spectrum
DTV signal spectrum
Analyzing the Signal Quality of NTSC and ATSC Television RF Signals.htm, Glen Kropuenske, Sencore
Submission
Soo-Young Chang, Huawei
Slide 8
February 2006
doc.: IEEE 802.22-06/0032r0
NTSC TELEVISION BAND
Conventional Analog Television - An Introduction
Submission
Soo-Young Chang, Huawei
Slide 9
February 2006
doc.: IEEE 802.22-06/0032r0
DTV PILOT FREQUENCY
Conventional Analog Television - An Introduction
Presented at the IEEE Broadcast Technical Society 49th Symposium September 24, 1999
Henry Fries and Brett Jenkins
Thales Broadcast & Multimedia, Inc.
Southwick, MA
Submission
Soo-Young Chang, Huawei
Slide 10
February 2006
doc.: IEEE 802.22-06/0032r0
DTV SIGNAL VIEWED ON A SPECTRUM
ANALYZER
Conventional Analog Television - An Introduction
Presented at the IEEE Broadcast Technical Society 49th Symposium September 24, 1999
Henry Fries and Brett Jenkins
Thales Broadcast & Multimedia, Inc.
Southwick, MA
Submission
Soo-Young Chang, Huawei
Slide 11
February 2006
doc.: IEEE 802.22-06/0032r0
DTV OUT-OF-BAND “SHOULDERS”
Conventional Analog Television - An Introduction
Presented at the IEEE Broadcast Technical Society 49th Symposium September 24, 1999
Henry Fries and Brett Jenkins
Thales Broadcast & Multimedia, Inc.
Southwick, MA
Submission
Soo-Young Chang, Huawei
Slide 12
February 2006
doc.: IEEE 802.22-06/0032r0
VSB TV PARAMETERS (1)
Submission
Soo-Young Chang, Huawei
Slide 13
February 2006
doc.: IEEE 802.22-06/0032r0
VSB TV PARAMETERS (2)
Submission
Soo-Young Chang, Huawei
Slide 14
February 2006
doc.: IEEE 802.22-06/0032r0
ATSC DTV SIGNAL FORMAT
• 313 segments comprise a data field: the first data segment in a
data field is called the data sync segment.
• ATSC DTV general data segment
• ATSC DTV data field sync segment
+7
+5
+3
+1
-1
-3
-5
-7
PN511
Date
Segment
Sync
PN63
PN63
VSB mode+
PN63 Reserved +
Precode
63
63
63
symbols symbols symbols
511 symbols
128
symbols
832 symbols
Submission
Soo-Young Chang, Huawei
Slide 15
February 2006
doc.: IEEE 802.22-06/0032r0
PROTECTION OF PART 74 DEVICES (1)
• Most microphones use analog modulation (FM)
• Bandwidth:200 KHz
• Power: max. 250 mW (24 dBm) in UHF band
– But usually operate at less than 50 mW
– Ex. Power 10 mW, antenna gain -10 dBi, body absorption 27 dB,
range 100 m, then mim. received power level: -95 dBm
• Required WRAN CPE out-of-band emission level to
protect Part 74 devices: 6.2 uV/m (15.8 dBuV/m
measured at 3 m in 120 KHz)
• Path loss needed between microphone receiver and L-E
devices beyond 1 m (required D/U = 20 dB)
– High power WRAN devices (4 W): 129 dB
– Low power L-E devices (100 mW): 113 dB
Submission
Soo-Young Chang, Huawei
Slide 16
February 2006
doc.: IEEE 802.22-06/0032r0
PROTECTION OF PART 74 DEVICES (2)
• Mitigation techniques
– Dynamic frequency selection (DFS)
• Sensing, detection, DFS network behavior to avoid hidden
nodes
• Practical sensing threshold: -107 dBm in 200 KHz
• Max. sensing distance for
– Unfaded microphone: 8.7 Km (free space)
– Faded (27 dB) microphone: 400 m (free space)
• Interference margin at edge of sensing contour for faded
microphone:
– High power WRAN devices (4W): -56.1 dB
– Low power L-E devices (100 mW): -40.4 dB
Submission
Soo-Young Chang, Huawei
Slide 17
February 2006
doc.: IEEE 802.22-06/0032r0
REQUIREMENTS
•
Technical consideration for RF front end circuitry
– Sensitivity
– Linearity and wide bandwidth operation
– Dynamic range
•
FRD
– Sensing measurements and control
• Scheduled quiet periods
• Sensing repetition rate and integration time
• Sensing SHOULD include capture of signal signature to identify the type of incumbent
and other LE signals and possibly the transmit unit identification
• threshold per incumbent type
• incumbent profile identification
• WRAN device identification from the received RF signal
– Sensing threshold
• DTV threshold: -116 dBm (total ATSC DTV power in the 6 MHz channel)
• Analog TV threshold: -94 dBm (measured at peak of sync of the NTSC picture carrier).
• Wireless microphone threshold: -107 dBm (measured in 200 kHz bandwidth)
Submission
Soo-Young Chang, Huawei
Slide 18
February 2006
doc.: IEEE 802.22-06/0032r0
DETECTION TECHNIQUES (1)
• Matched filtering
– Needs a priori knowledge of incumbent signals: modulation type and
order, pulse shaping, packet format, etc.
– Needs to achieve coherency with incumbent user signals: timing and
carrier synchronization, even channel equalization
– Requires less time to achieve high processing gain due to coherency
– Needs a dedicated receiver for each incumbent class
– O(1/SNR) samples needed to meet a given probability of detection
f(t) +n(t)
integrator
threshold
detector
f(t)
Submission
Soo-Young Chang, Huawei
Slide 19
February 2006
doc.: IEEE 802.22-06/0032r0
DETECTION TECHNIQUES (2)
• Energy detection
– Non coherent detection: amount of energy in a given band is measured
– Use FFTs and average the outputs over a fixed interval
– Increasing FFT size improves frequency resolution: helps narrowband
signal detection
– Longer averaging time reduces the noise power thus improving SNR
– O(1/SNR2) samples needed to meet a given probability of detection
– Drawbacks:
• the threshold is susceptible to unknown or interference signals
• Energy detector does not differentiate between modulated signals, noise,
and interference because it cannot recognize the interference
• Energy detector does not work for spread spectrum signals
Submission
Soo-Young Chang, Huawei
Slide 20
February 2006
doc.: IEEE 802.22-06/0032r0
DETECTION TECHNIQUES (3)
•
Cyclostationary feature detection
– Utilize built-in periodicity  cyclostationary: their statistics, mean and
autocorrelation, exhibit periodicity.
– Cyclostationary signals exhibit correlation between widely separated spectral
components due to spectral redundancy caused by periodicity.
– spectral correlation function (SCF) is defined and also termed as cyclic
spectrum (CSD)
– SCF is two dimensional transform, in general complex valued and the
parameter is called cycle frequency
– Different types of modulated signals can have highly distinct spectral correlation
functions; stationary noise and interference exhibit no spectral correlation
– Detected features are number of signals, their modulation types, symbol rates,
and presence of interferers
– SCF is preserved even in low SNR while energy detector is limited by the large
noise
Submission
Soo-Young Chang, Huawei
Slide 21
February 2006
doc.: IEEE 802.22-06/0032r0
ISSUES TO BE OVERCOME
• Hidden node problem
– Cognitive radio is shadowed
– In severe multipath fading
– Inside buildings with high penetration loss
• Local spectrum sensing
Submission
Soo-Young Chang, Huawei
Slide 22
February 2006
doc.: IEEE 802.22-06/0032r0
REFERENCES
• Danijela Cabric, et al., Implementation Issues in Spectrum Sensing
for Cognitive Radios, Berkeley Wireless Research Center, University
of California, Berkeley,
http://bwrc.eecs.berkeley.edu/Publications/2004/PRESENTATIONS/
dc.smm.asilomar/asilomar_paper_danijela.pdf
• Gerald Chouinard, CRC, IEEE802.22-06/0006r0
Submission
Soo-Young Chang, Huawei
Slide 23
February 2006
doc.: IEEE 802.22-06/0032r0
ETRI/FT/I2R
/MOTOROLA/PHILIPS
/SAMSUNG/THOMSON
Submission
Soo-Young Chang, Huawei
Slide 24
February 2006
doc.: IEEE 802.22-06/0032r0
SUMMARY OF PROPOSED SCHEMES
•
Coarse energy detection sensing: detect existence of signals:
– MRSS
– RSSI
•
Fine/feature detection sensing: categorize the signal type
– Fine energy based detection
– Signal feature detection
• Part 74 detection
• ATSC DTV detection
– Cyclostationary feature detection
– For detection of ATSC signals, having known characteristics: Optimum Radiometer
•
Low complexity
• Taking profit from the ATSC pilot
– For detection of signals with unknown characteristics: Multi-cycle detector
• Higher complexity
• Independent of noise level
• More general use
•
•
Need a separate sensing receiver
Almost all possible detection schemes are suggested for this proposal: 8 schemes
Submission
Soo-Young Chang, Huawei
Slide 25
February 2006
doc.: IEEE 802.22-06/0032r0
PROPOSED SPECTRUM SENSING
SCHEME (1)
•
Dual Sensing Strategy:
–
–
•
Matched Filter Detection
–
•
DTV detection using PN63 sequences (1)
Energy Detection
–
–
–
–
–
•
Energy Detection / Matched Filter Detection
Fine/Feature detection
To meet the speed and power requirement
Power spectrum distribution in the entire band is obtained
On request basis, detect the power level of selected channel in very short time
Examples are MRSS (2), RSSI, DTV detection using segment sync (3)
FFT based spectral analysis: detecting narrowband analog modulated signals, most of
part 74 devices (4)
Fine/Feature Detection
–
–
–
–
Submission
To meet the minimum sensitivity requirement
Fine sensing is applied for the selected channel
Feature Detection: detecting digital modulated signals
Examples include Optimum Radiometer (5), field-sync detection (6), CSFD (7), Multicycle detector (8)
Soo-Young Chang, Huawei
Slide 26
February 2006
doc.: IEEE 802.22-06/0032r0
PROPOSED SPECTRUM SENSING
SCHEME (2)
• Distributed Sensing Strategy : Frequency usage information is
collected and managed at Base-station
• Either the BS makes the detection decision based on the
collective measurement results or CPE’s can make the decision
• Can be implemented as a stand alone sensing block with an
omni-directional antenna
Submission
Soo-Young Chang, Huawei
Slide 27
February 2006
doc.: IEEE 802.22-06/0032r0
Spectrum Sensing Architecture
Matched filter
for DTV (?)
Omni Antenna
Fine/Feature
RFE
Control
MAC
Energy Detection
Submission
Soo-Young Chang, Huawei
Slide 28
February 2006
doc.: IEEE 802.22-06/0032r0
Spectrum Sensing Strategy
Begin Sensing
Energy Detection
for wide band
(Analog, RSSI, MRSS, FFT…)
Spectrum
Usage
Database
MAC
Fine/Feature Detection
for single channel
FFT
CSFD
Field
Sync
Optimum
Radiometer
RSSI
AAC
ATSC
Segment
Sync
Multi-cycle
Detector
(Select
single channel)
Y
occupied?
End Sensing
N
Submission
Soo-Young Chang, Huawei
Slide 29
February 2006
doc.: IEEE 802.22-06/0032r0
MATCHED FILTER DETECTION
• DTV detection using PN63 sequences
Submission
Soo-Young Chang, Huawei
Slide 30
February 2006
doc.: IEEE 802.22-06/0032r0
DTV Detection Using PN63 Sequences
• In ATSC DTV signals, three PN63 sequences are concatenated
together in the field sync segments.
– Three sequences are the same except the middle sequence inverts
on every other field sync segment.
• PN63 sequences can be utilized for DTV feature detection
– Simple Circuitry for identification of PN63
– Peak Detection Can be performed on y1 and y2 or y = max(|y1|,
|y2|)
y1
+
-1
X
Delay line
PN 63
Matched
filter
0
63
126
+
y2
Submission
Soo-Young Chang, Huawei
Slide 31
February 2006
doc.: IEEE 802.22-06/0032r0
Energy Detection Method
• Received signal strength within a given bandwidth is detected
after the RF receiver
• Decision can be made by many different ways
– Analog/digital integration, MRSS, RSSI, FFT
• Full range of spectrum profile can be obtained quickly with low
power consumption
• Integration time and threshold is very important
• BS sets essential parameters (constant)
Filter
Submission

LNA
Soo-Young Chang, Huawei
Decision
Slide 32
February 2006
doc.: IEEE 802.22-06/0032r0
MULTI-RESOLUTION SPECTRUM
SENSING (MRSS)
•
•
•
•
•
•
•
•
Analog wideband spectrum sensing and reconfigurable RF front end
Adopted the wavelet transform to provide the multi-resolution sensing
feature
Flexible energy detection based spectrum sensing
Wavelet transform is applied to the input signal and the resulting coefficient
values stand for the representation of the input signal’s spectral contents
with the given detection resolution
MRSS detect spectral components of incoming signal by the Fourier
Transform.
Fourier Transform is performed in analog domain.
MRSS may utilize wavelet transforms as the basis function of the Fourier
Transform.
Bandwidth, resolution and center frequency can be controlled by wavelet
function
Submission
Soo-Young Chang, Huawei
Slide 33
February 2006
doc.: IEEE 802.22-06/0032r0
MRSS DIAGRAM
MRSS is energy detector.
According to this diagram
accumulated energy is calculated.
X
x(t)
Driver Amp

z(t)
y(t)
ADC
CLK#2
w(t)
CLK#1
v(t)*fLO(t)
Timing
Clock
MAC
Wavelet Generator:
use Hann window as a wavelet
Submission
Soo-Young Chang, Huawei
Slide 34
February 2006
doc.: IEEE 802.22-06/0032r0
COMPARISON, SIMPLE DOWN
CONVERSION AND MRSS
DOWN CONVERSION
X
x(t)
Driver Amp
z(t)

LPF
y(t)
ADC
CLK#2
w(t)
fLO(t)
CLK#1
Timing
Clock
MAC
Oscillator
MRSS
X
x(t)
Driver Amp

z(t)
y(t)
ADC
CLK#2
w(t)
v(t)*fLO(t)
CLK#1
Timing
Clock
MAC
Wavelet Generator
Submission
Soo-Young Chang, Huawei
Slide 35
February 2006
doc.: IEEE 802.22-06/0032r0
HANN WINDOW
Submission
Soo-Young Chang, Huawei
Slide 36
February 2006
doc.: IEEE 802.22-06/0032r0
MRSS LAYERD OPERATION
Higher Layers: IP, ATM, 1394, etc.
Convergence Sublayer / Bridge (e.g., 802.1d)
Submission
MAC
MAC
PHY
PHY
PHY
PHY/MAC 1
PHY/MAC 2
PHY/MAC n
...
MAC
Soo-Young Chang, Huawei
Spectrum Manager
Slide 37
February 2006
doc.: IEEE 802.22-06/0032r0
MRSS BUILDING BLOCKS
• Analog wavelet waveform generator
– Wavelet pulse is generated and modulated with I and Q sinusoidal
carrier with the given frequency
– Hann window with 5 MHz bandwidth is selected as the wavelet.
• Analog multiplier
• Local oscillator
– By sweeping the local oscillator (LO) frequency spectrum range with a
certain interval, the signal power and the frequency values are detected
over the spectrum range of interest
• Analog integrator
– to compute the correlation with the wavelet waveform with the given
spectral width, i.e. the spectral sensing resolution
– The resulting correlation with I and Q components of the wavelet
waveforms are inputted to ADC
• Low speed ADC to digitize the calculated analog correlation values
– Digitized values are recorded
Submission
Soo-Young Chang, Huawei
Slide 38
February 2006
doc.: IEEE 802.22-06/0032r0
MRSS OPERATION
• If the correlation values are greater than the certain threshold level,
the sensing scheme determines the meaningful interferer reception.
• Since the analysis is performed in the analog domain, the high
speed operation and low power consumption can be achieved.
• By applying the narrow wavelet pulse and large tuning step size of
LO, the MRSS is able to examine the very wide spectrum span in
the fast and sparse manner.
• On the contrary, very precise spectrum searching is realized with the
wide wavelet pulse and the delicate adjusting LO frequency.
• By virtue of the scalable feature of the wavelet transform, multiresolution is achieved without any additional digital hardware
burdens.
• Unlike the heterodyne based spectrum analysis techniques, the
MRSS does not need any physical filters for image rejection due to
the band pass filtering effect of the window signal
Submission
Soo-Young Chang, Huawei
Slide 39
February 2006
doc.: IEEE 802.22-06/0032r0
Non-linear effect of MRSS
• Effect of the RF Mixer for MRSS is simulated and compared with
Ideal multiplier
• Three input tone (240MHz, 470MHz, 600MHZ) is assumed
• Hann window with 5MHz bandwidth is selected as the wavelet
• RF circuit model of double balanced mixer is used as multiplier
Submission
Soo-Young Chang, Huawei
Slide 40
February 2006
doc.: IEEE 802.22-06/0032r0
Ideal Multiplier
Submission
Soo-Young Chang, Huawei
Slide 41
February 2006
doc.: IEEE 802.22-06/0032r0
LOmax = 10 dBm
Submission
Soo-Young Chang, Huawei
Slide 42
February 2006
doc.: IEEE 802.22-06/0032r0
LOmax = -30 dBm
Submission
Soo-Young Chang, Huawei
Slide 43
February 2006
doc.: IEEE 802.22-06/0032r0
Result of MRSS
• Mixer non-linear effect is significantly depend on the LO power
level
• RF mixer can be used as the multiplier, if operating in the linear
mode
• By adjusting LO power for wavelet generator can suppressing
the unwanted harmonic component
Submission
Soo-Young Chang, Huawei
Slide 44
February 2006
doc.: IEEE 802.22-06/0032r0
40
-50
20
-60
0
-70
-20
-80
PSD (dB)
Power Spectrum Magnitude (dB)
MRSS Simulation Results
Wireless Microphone (FM) Signal
-40
-90
-60
-100
-80
-110
-100
0
0.2
0.4
0.6
0.8
1
1.2
Frequency
1.4
1.6
1.8
2
x 10
The spectrum of the wireless
microphone signal
Submission
-120
0
0.2
6
0.4
0.6
0.8
1
1.2
Frequency (Hz)
1.4
1.6
1.8
2
x 10
6
The corresponding signal spectrum
detected with the MRSS technique
Soo-Young Chang, Huawei
Slide 45
February 2006
doc.: IEEE 802.22-06/0032r0
MRSS FOR OFDM
)
B
d
(
e
d
u
t
i
n
g
a
M
m
u
r
t
c
e
p
S
40
20
30
10
20
)
B
d
(
10
D
S
P
0
r
e
w -10
o
P
-20
-30
0
-10
-20
-30
-40
0
0.5
1
1.5
2
2.5
3
Frequency
3.5
4
4.5
5
0
0.5
7
x 10
Original
Submission
1
1.5
2
2.5
3
Frequency (Hz)
3.5
4
4.5
5
7
x 10
MRSS
Soo-Young Chang, Huawei
Slide 46
February 2006
doc.: IEEE 802.22-06/0032r0
ADVANTEGES OF MRSS
• Full analog signal process
– Drastically reduce power consumption
– Faster recognition
•
•
•
•
Flexibility in sensing resolution and speed
Filter is not required on the sensing path
Wideband operation:
Relaxing RF components constraint (Noise,
Linearity…):
Submission
Soo-Young Chang, Huawei
Slide 47
February 2006
doc.: IEEE 802.22-06/0032r0
DISADVANTAGES OF MRSS
• Frequency information of received signals can be known with
relatively complicated hardware comparing to FFT method
• Merely similar to traditional receiver using mixer, osc., etc. except the
use of wavelet waveform instead of sinusoidal waveform.
• Need to generate wavelet waveform: may need much more complex
circuitry than simple oscillator
Submission
Soo-Young Chang, Huawei
Slide 48
February 2006
doc.: IEEE 802.22-06/0032r0
DTV Detection Using Segment Sync
• Non-coherent segment sync detector
– A two-level (binary) four-symbol data segment sync is inserted at the
beginning of each data segment
– which can be use to detect ATSC DTV signals
– down-conversion to baseband via use of the pilot carrier is not
required
IIR FILTER
BASIC SEGMENT SYNC CORRELATOR
Submission
+
1ALPHA
832-SYMBOL
DELAY
MAGNITUDE
SQUARED
ALPHA
x
4-SYMBOL
SLIDING
WINDOW
ADDITION
CONJUGATE
Soo-Young Chang, Huawei
832-SYMBOL
DELAY
Slide 49
February 2006
doc.: IEEE 802.22-06/0032r0
SIMULATIONS FOR ATSC DETECTION
USING SEGMENT SYNC (1)
AWGN
ATSC signal
generator
+
Pulse
matched
filter
Down
sampling
Non-coherent
segment sync
detector
• ATSC signal generator produce samples with 2x symbol rate
• When ATSC signal generator is turned on, probability of
detection is measured; when it is turned off, probability of false
alarm is measured.
• In the simulations, magnitude squared module is not used in
the non-coherent segment sync detector
Submission
Soo-Young Chang, Huawei
Slide 50
February 2006
doc.: IEEE 802.22-06/0032r0
SIMULATIONS FOR ATSC DETECTION
USING SEGMENT SYNC (2)
• Denote the values in the IIR delay line as {y(k), k=0,…831}
• The magnitude of {y(k)} are computed, denote as {z(k),
k=0,…,831}
• Let max, mean and modified standard deviation be zmax, E{z}, ( z)
, where
831
 ( z) 
1
832
 z  E( z)
k 0
• The decision rule is:
 if zmax  k1E ( z)  k2 ( z), ATSC signal is present

ATSC signal not present
else,
• The parameters used in the simulations are: k1 =3.0, k2 = 2.0
Submission
Soo-Young Chang, Huawei
Slide 51
February 2006
doc.: IEEE 802.22-06/0032r0
SIMULATIONS FOR ATSC DETECTION
USING SEGMENT SYNC (3)
• Detection time = 35.9ms, simulation run = 1000, SNR= -10 dB
Simulation Conditions
Pd
Pf
toff = 0,
foff = 0
92.4%
5.0%
toff = 0,
foff = 5kHz
93.2%
5.0%
toff = 0,
foff =10kHz
93.7%
5.0%
toff = 250Hz, foff = 0kHz
92.0%
5.0%
toff = 250Hz, foff = 5kHz
90.7%
5.0%
toff = 250Hz, foff =10KHz
91.9%
5.0%
Submission
Soo-Young Chang, Huawei
Slide 52
February 2006
doc.: IEEE 802.22-06/0032r0
SYNCHRONIZATION USING STRONG
DTV SIGNALS
• DTV signal Sensing performance may be improved
– by increasing the accuracy of the timing and/or carrier frequency
references in the receiver, which is difficult to achieve if the DTV
signal for sensing is very weak
• Proposed method: receive a strong station on another
frequency
– Observe the timing and frequency offsets and use the settings to
calibrate the receiver
– It relies on the stability and known frequency allocation of DTV
channels.
– It also relies on the short term stability of the frequency reference in
the receiver.
Submission
Soo-Young Chang, Huawei
Slide 53
February 2006
doc.: IEEE 802.22-06/0032r0
PART 74 ENERGY DETECTION
• Part 74 devices occupy a small portion of the
spectrum
• Thus, use spectral estimation and statistics of the
estimated signal
– Spectral estimation using FFTs (windowing techniques
can also be employed to better localize the spectrum)
• Perform FFT
K 1
1
2
• Average the received
P ( k , m) 
Y ( k  i, m)
K i 0
power for each freq bin
N 1
• Average across freq bin
 k  P ( k , m)
– Compute mean and “variance”
m 0


FFT
avg
W.F.
V>k*avg
N 1
 k   P ( k , m)   k
– Detection
max( P(k , m))  k1  k  k 2  k
m 0
How can k values be determined?
Submission
Soo-Young Chang, Huawei
Slide 54
February 2006
doc.: IEEE 802.22-06/0032r0
Part 74 detection (cont.)
• Detection
max( P(k , m))  k1  k  k 2  k
• Theoretical performance
Pr ob _ miss
  ( K , K ) M
Pr ob _ det ection  1  ( K , K ) M
Pr ob _ false _ alarm.  1  ( K , K ) N
Submission
Soo-Young Chang, Huawei
Slide 55
February 2006
doc.: IEEE 802.22-06/0032r0
Narrow-band detection (Part 74):
Theoretical and simulated performance
Submission
Soo-Young Chang, Huawei
Slide 56
February 2006
doc.: IEEE 802.22-06/0032r0
Probability of miss detection and false
alarm
Submission
Soo-Young Chang, Huawei
Slide 57
February 2006
doc.: IEEE 802.22-06/0032r0
FINE/FEATURE DETECTION
• Upon request by the BS, simple energy based detection
• Three detection methods suggested
– Fine energy based detection
• Comparing the energy estimated by using the previous one
– Signal feature detection
• Part 74 devices
• ATSC DTV detection
– Optimum radiometer
– Cyclostationary feature detection
• Single-cycle detector
• Multi-cycle detector
Submission
Soo-Young Chang, Huawei
Slide 58
February 2006
doc.: IEEE 802.22-06/0032r0
Optimum Radiometer
• Optimum radiometer means that we assume the knowledge of the
spectral density of the signal
• Basically, we make a decision with a threshold on a correlation
between the spectrum received and a known signature
– ATSC : digital pilot frequency
– Perform slightly better with OFDM/OQAM
• Complexity is near zero (assuming that the phy layer is OFDM based)
• Performances are quite good (integration time 5ms, Pfa=0.01, Pd =
0.9, ATSC energy needed = -126 dBm)
Submission
Soo-Young Chang, Huawei
Slide 59
February 2006
doc.: IEEE 802.22-06/0032r0
DTV SIGNAL FEATURE DETECION
USING FIELD SYNC/CORRELATION
• Should not be sensitive to frequency selective fading, and
receiver impairments (e.g., frequency error)
• Use field sync correlation detection for ATSC, similar correlation
for other standards
– Compare correlation peak to the mean of the standard deviation of
the correlation
– Characterized the theoretical performance
– Experimental tests
Submission
Soo-Young Chang, Huawei
Slide 60
February 2006
doc.: IEEE 802.22-06/0032r0
CYCLOSTATIONARY FEATURE
DETECTION
• Using underlying periodicities in the signal structure
– Cyclic autocorrelation function (CAF)
– Cyclic spectral density (CSD) or spectral correlation function (SCF)
– Cycle frequency: an integer multiple of the fundamental time period of
the signal
• If CF=0, conventional autocorrelation and PSD
• SCF has symmetry and periodicity: SCF is specified over {0<f<1/2, 0<CF<12f}
• If CF is known for a specific signal among signals superposed, SCF can be
extracted
: this detection can be used for signals whose characteristics are well known
a priori
Submission
Soo-Young Chang, Huawei
Slide 61
February 2006
doc.: IEEE 802.22-06/0032r0
CYCLOSTATIONARITY BASED SIGNAL
DETECTION
Signal attributes
x(n)
X T (n, f ) 
•
Sliding
N-pt
FFT
N / 21

p  N / 2
x(n  p)e
Correlate and
average sum
 j 2 f ( n  p )/ fs
Feature
detector
–Power
–Modulation
–Symbol frequency
1 M / 21
mfs  *
mfs 
S (n, f ) 
X
(
n
,
f


)
X
(
n
,
f

 )
 T
T
MN m M / 2
N 2
N 2

xt
Cyclic spectrum domain reveals signal specific features at
– Modulating frequency
– Carrier frequency
– … (signal frequencies specific to modulation parameters)
•
Various forms of detectors can be derived from cyclic power spectrum
density
– Single-cycle magnitude detector
– Multi-cycle magnitude detector
Submission
Soo-Young Chang, Huawei
Slide 62
February 2006
doc.: IEEE 802.22-06/0032r0
CYCLIC FREQUENCIES OF VARIOUS
SIGNALS
Type of Signal
Cyclic Frequencies
Analog Television
cyclic frequencies at multiples of the TV-signal horizontal
line-scan rate (15.75 kHz in USA, 15.625 kHz in Europe)
AM signal:
x(t )  a(t ) cos( 2f 0 t  0 )
PM and FM signal:
 2 f0
x(t )  cos( 2f 0 t   (t ))
 2 f0
Amplitude-Shift Keying:

x(t )  [  a n p(t  nT0  t 0 )] cos( 2f 0 t  0 )
k / T0 (k  0)
and
 2 f 0  k / T0 , k  0,1,2, 
n  
Phase-Shift Keying:
x (t )  cos[ 2f 0 t 

a
n  
n
p(t  nT0  t0 )].
k / T0 (k  0)
For QPSK,
, and for BPSK
k / T0 (k  0) and  2 f 0  k / T0 , k  0,1,2, 
Since we have knowledge of the cyclic frequencies of interested signals
like TV and wireless microphones (???), we only need to compute the
SCD function at very limited number of discrete cycle frequencies.
Classical spectral analysis method can be used in computing the SCD
functions: For each microphone, a different cycle frequency may be used.
Submission
Soo-Young Chang, Huawei
Slide 63
February 2006
doc.: IEEE 802.22-06/0032r0
LOCAL DETECTION AT EACH CPE
• Signal detection
– Signal x(k), that is transmitted over channel h(k), to be detected in presence of AWGN
n(k)
[signal absent hypothesis]
H 0 : x ( k )  n( k )
[signal present hypothesis]
H 1 : x ( k )  h( k ) * s ( k )  n( k )
• h(k) is the impulse response of channel between Tx and CPE Rx
• Measure received cyclic power spectrum at specific cycle frequencies
– Specific cycle frequencies could be VSB Nyquist frequency (5.38 MHz),
WRAN OFDM symbol frequency (x MHz), etc.
– Declare signal sj present if spectral component detected at corresponding
cycle frequencies { j} (decision fusion)
 Sn0 ( f ),

2
0
0
| H ( f ) | S s ( f )  S n ( f ),
S x ( f ) = 0,

 H ( f   ) H * ( f   ) S  ( f ),
s

2
2
Submission
  0, signal absent
  0, signal present
  0, signal absent
  0, signal present
Soo-Young Chang, Huawei
Slide 64
February 2006
doc.: IEEE 802.22-06/0032r0
Multi-cycle detector
•
•
•
•
•
•
•
Telecommunication signals are well modeled as cyclostationary signal
however the noise is usually taken to be stationary.
The test for occupied frequency band is a test for presence of cycles in
the received radio signal.
When possible existing signals in a given band are unknown, a test
over a range of cyclic frequencies can be helpful.
A multi-cycle detector does not suppose any knowledge on signals to
be detected nor on the noise level.
Performances are quite good but the algorithm requires more
computation.
The complexity added by the Multi-cycle detector can be justified when
searching to detect the presence of radio signals with unknown
characteristics (e.g. competitive radio-cognitive systems).
More detailed information may be provided at a later stage, if this
solution is acceptable to be included in the joint proposal
Submission
Soo-Young Chang, Huawei
Slide 65
February 2006
doc.: IEEE 802.22-06/0032r0
Detection algorithm modes
• Basic mode of detection algorithm
– Detection of signal energy (from alpha = 0 spectral content)
– Used in high SNR regimes for pilot/carrier/signature detection type
schemes
– Eg., pilot about 11 dB below at 310 KHz carrier offset from lower
end frequency
• Enhanced mode of detection algorithm
– Detection of spectral features (spectral content at signal symbol
frequency, carrier frequency, …)
– Used in low SNR regimes
– Especially useful during initialization procedures where BS is
looking for an empty channel in possibly low SNR conditions
Submission
Soo-Young Chang, Huawei
Slide 66
February 2006
doc.: IEEE 802.22-06/0032r0
ADVANTAGES OF CYCLOSTATIONARY
DETECTION
• Cyclic spectrum domain: a richer domain for signal analysis than
conventional power spectrum
• Robust to noise
– Stationary noise exhibits no cyclic correlations
 S n0 ( f ),

| H ( f ) |2 S s0 ( f )  S n0 ( f ),


S x ( f ) = 0,

 H ( f   ) H * ( f   ) S  ( f ),
s


2
2
  0, signal absent
  0, signal present
  0, signal absent
  0, signal present
• Better detector performance even in low SNR regions
• Signal classification ability
– Different signals have different cycle frequencies and exhibit distinct
spectral characteristics
• Can be used as an energy detector in alpha = 0 mode
– Flexibility of operation
Submission
Soo-Young Chang, Huawei
Slide 67
February 2006
doc.: IEEE 802.22-06/0032r0
DISADVANTAGES OF
CYCLOSTATIONARY DETECTION
• More complex processing needed than energy detection: high speed
sensing can not be achieved
• A priori knowledge of target signal characteristics needed  can not
be applied for unknown signals: cycle frequency should be known a
priori  practically almost impossible to detect microphone signals
• At one time, only one signal can be detected: for multiple signal
detection, multiple detectors should be implemented or slow
detection should be allowed. That means one detection cycle is
needed for a DTV signal, and then another one is for a NTSC signal,
so on.
Submission
Soo-Young Chang, Huawei
Slide 68
February 2006
doc.: IEEE 802.22-06/0032r0
REFERENCES
• Yongsik Hur, et al, A Wideband Analog Multi-Resolution Spectrum
sensing (MRSS) Technique for Cognitive Radio (CR) Systems,
Information for Paper ID 3534, ISCAS2006
• Marital Bellec, et al, IEEE802.22-06/0004r0, Jan. 2006
• Marital Bellec, et al, IEEE802.22-06/0005r3, Feb. 2006
Submission
Soo-Young Chang, Huawei
Slide 69
February 2006
doc.: IEEE 802.22-06/0032r0
HUAWEI/NEXTWAVE
/RUNCOM/STMICRO
Submission
Soo-Young Chang, Huawei
Slide 70
February 2006
doc.: IEEE 802.22-06/0032r0
METHOD 1 (1)
SENSING INCUMBENT SIGNALS
• TV band signal sensing for one channel band
– Use only spectral components – not time domain components
• Less sensitive on other parameters used to design TV band tuners – for
example, Phase noise, etc.
– Use FFT transform of received TV band signals at the receiver for only
one TV band or a few bands
• After wide band tuning and down converting or down converting and low
pass filtering
– One example
•
•
•
•
•
•
Submission
BW=F=6 MHz for one band case
Sampling interval T=1/B=1/6 us, sampling rate=BW=6 MHz
Frequency resolution (or frequency separation) F0=3 KHz
Time period T0=1/F0=1/3 ms
Number of samples needed N0=T0/T= 2 KHz
Needs 2K point FFTs
Soo-Young Chang, Huawei
Slide 71
February 2006
doc.: IEEE 802.22-06/0032r0
METHOD 1 (2)
SENSING INCUMBENT SIGNALS
Discrete Fourier Transform
T
F0
t
0
f
T0
0
F
Sense Receiver Structure
Sense
antenna
LPF
ADC
FFT
detector
LNA
cos2fpt
where fp: left edge freq. of
the channel
Submission
Soo-Young Chang, Huawei
Slide 72
February 2006
doc.: IEEE 802.22-06/0032r0
METHOD 1 (3)
SENSING INCUMBENT SIGNALS
• Sensing procedure for TV signals
– Several to many frequency components taken in a 6 MHz band
depending on the sensing accuracy
•
for ex., F50, F103, F200, F417, and F1200
– Compare these values
• Correlation method: compare the shape of spectrum of received signals
– Calculate correlations with pre-stored values for NTSC and DTV signals
– If one of these values is larger than predetermined values, the
judgment is that NTSC or DTV signal exists.
• Pilot detection method: check whether a pilot signal exists
– Calculate the ratio of pilot component to another component
– If F417/F1200 > thn, this signal is NTSC
– If F103/F1200 > thd, this signal is DTV
– Average frequency component values for several symbol periods to
have better sensing results
Submission
Soo-Young Chang, Huawei
Slide 73
February 2006
doc.: IEEE 802.22-06/0032r0
METHOD 1 (4)
SENSING INCUMBENT SIGNALS
•
Sensing procedure for wireless microphone signals
– Two types of wireless microphone systems according to frequency usage
• Single frequency systems
• Frequency agile systems
– Wireless systems should NOT be operated on the same frequency as a local TV
station.
• Only open (unoccupied) frequencies should be used. In the U.S., each major city has
different local TV stations.
– Microphone signal detection procedure: sensing the spectral components using
FFT devices
• For ex., for every 3 KHz in a 6 MHz band a spectral component is measured and
compared with other components: two comparison methods used for DTC and NTSC
signals can be applied
• If considerable components in a 200 KHz band exist, a wireless microphone is
considered to be operated in that band:
– For the previous case, if consecutive six components spaced equally in 200 KHz have
considerable amount of energy, a microphone signal is detected.
• Or much correlation with stored microphone signals exists, a wireless microphone is
considered to be operated in that band.
Submission
Soo-Young Chang, Huawei
Slide 74
February 2006
doc.: IEEE 802.22-06/0032r0
METHOD 2 (1)
SENSING INCUMBENT SIGNALS
• After DTV transition in the U.S.,
– VHF low band:
– VHF high band:
– UHF band:
Chs 2-6
Chs 7-13
Chs 14-51
54-88 MHz
174-216 MHz
470-698 MHz *
• n consecutive bands in VHF High or UHF band selected for
WRAN services
– The whole band of n bands is divided into n*l subbands
• Each band has l subbands; each subband has 6000/l KHz bandwidth
– At receiver, the received signal after down conversion is inputted to a
l*n point FFT
• By comparing FFT output signals, currently operated incumbent users can be
identified and categorized – NTSC, DTV, or Part 74 devices
• With this method all incumbent signal throughout the whole band
(n TV bands) can be detected simultaneously
– Periodically all CPEs and BSs can do this sensing to update the list
of active incumbent users
* Ch 37 is reserved for radio astronomy
Submission
Soo-Young Chang, Huawei
Slide 75
February 2006
doc.: IEEE 802.22-06/0032r0
METHOD 2 (2)
SENSING INCUMBENT SIGNALS
• NTSC signal sensing
– After down conversion with (fp+1.25) MHz frequency shift, the received
signal is inputted to l*n point FFT devices
– Compare the FFT outputs
• DTV signal sensing
– After down conversion with (fp+0.30944) MHz frequency shift, the
received signal is inputted to l*n point FFT devices
– Compare the FFT outputs
• Part 74 device sensing
– After down conversion with fp MHz frequency shift, the received signal is
inputted to l*n point FFT devices
– Compare the FFT outputs
• Various comparison methods can be considered
– Correlation method or pilot detection method used in Method 1 is
suggested for TV signals
– If some consecutive strong components in 200 KHz exist, Part 74
device is considered to operate in this band. Or correlation method will
be applied for Part 74 device signals.
Submission
Soo-Young Chang, Huawei
Slide 76
February 2006
doc.: IEEE 802.22-06/0032r0
METHOD 2 (3)
SENSING INCUMBENT SIGNALS
• Select k consecutive bands out of n bands
subband 0
subband 1
subband 2
subband l-1
f
Selected bands
Band 0
WRAN/incumbent WRAN
Submission
Band 1
Band k-1
Incumbent user
WRAN
Soo-Young Chang, Huawei
Slide 77
February 2006
doc.: IEEE 802.22-06/0032r0
SPECTRAL CORRELATION (EXAMPLE)
8 measured
spectral
components
Using 8 measured components, a correlation is calculated.
Submission
Soo-Young Chang, Huawei
Slide 78
February 2006
doc.: IEEE 802.22-06/0032r0
PROPOSED RECEIVER STRUCTURE
•
At receiver, data receiving and incumbent signal sensing are
executed simultaneously.
– Without having separate receiving and processing branches
– Using sensing method 2
– If more precise sensing is needed, sensing method 1 may be
applied with an additional signal processing block – needs one more
ADC and FFT.
receive
antenna
demod
LPF
LNA
Submission
ADC
cos2fpt
where fp: left edge freq. of the
channel (or whole target band)
Soo-Young Chang, Huawei
FFT
detector
Slide 79
February 2006
doc.: IEEE 802.22-06/0032r0
WRAN SENSING SCHEME
NF=7dB
BPF
IF 36MHz
Tuner
LNA
IF OUT
AMP
SAW
6MHz BW
470-860MHz
Freq Info
From WRAN
Modem
AGC-RF
From Processor
To Processor
FFT
Demod.
A/D
10b
To Analyze And
Report
Signal Signatures
• Scanning of +/- 8 channels from both sides of WRAN operating channel
• 50 steps of 2MHz each fed to the tuner
• Extracting signal signature within the scanned band will take 15 msec
Submission
Soo-Young Chang, Huawei
Slide 80
February 2006
doc.: IEEE 802.22-06/0032r0
ADVANTEGES OVER OTHER PROPOSED
SCHEMES
• Advantage over energy detection including MRSS
– At one measurement, all frequency components can be
extracted: whole frequency band can be covered for one FFT
symbol duration
: faster than MRSS which uses sweep oscillators.
– Correlation detection not energy detection
: more intelligent sensing than MRSS
• Advantage over cyclostationary feature sensing
– Can detect Part 74 device signals while cyclostationary sensors
can not detect them while NTSC and DTV signals can be
detected relatively much easier than Part 74 signals.
• Advantage over other proposed schemes
– Need not more hardware to sense: can use OFDM receiving
blocks: only a detector should be added for sensing
– Faster and simpler than other proposed schemes
Submission
Soo-Young Chang, Huawei
Slide 81
February 2006
doc.: IEEE 802.22-06/0032r0
CONSIDERATIONS FOR SELECTION OF
SENSING SCHEMES
• Performance
– Can sense all three types of signals
• NTSC and DTV signals: a priori knowledge available
• Microphone signals: a priori knowledge not available
– Probability of detection
– Sensing time: sensing duration
• Complexity
– Compatible with other hardware structure
– Need separate receiver for different signals
– computational complexity
• Sensing processing time
Submission
Soo-Young Chang, Huawei
Slide 82