10/20/20151 document title: spectrum consumption modeling tutorial document date: 16 july, 2014...
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Document Title: Spectrum Consumption Modeling TutorialDocument Date: 16 July, 2014Document No: 5-14-0052-02-subs (assigned by document server https://mentor.ieee.org/1900.5/documents)
Author’s Name Affiliation Address Phone email
John Stine MITRE Corporation McLean, VA 703-983-6281 [email protected]
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IEEE 1900.5 Contribution
Doc #: 5-14-0052-02-subs
Purpose
• This document introduces and provides an overview of a proposed approach to model the consumption of spectrum by RF devices and systems
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Spectrum Consumption Modeling Objectives
• Provide means to capture all the relevant parameters and phenomena that affect spectrum consumption
• Provide means to compute compatibility between any two models without dependence on external databases of environmental or system data
• Support methods for computing compatibility that are tractable and definitive
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The Role of Spectrum Consumption Models
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(loose coupler)
Spectrum UseDiversity
Spectrum ManagementDiversity
SCMChannel
configuration
Digital spectrum
policy
Spectrum use
Network Operations and Spectrum Management
RF Coexistence and Dynamic Spectrum Access
Innovation
Innovation
Standardization
SCMs are designed to serve as a loose coupler for the spectrum
management enterprise
Proposal has 12 Constructs• Total power• Spectrum mask• Underlay mask• Power map• Propagation map• Intermodulation masks• Platform• Location• Start time• End time• Minimum power spectral flux density• Protocol or policy
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Captures the spectral content of the signal and the unique characteristics of
spread spectrum systems
Can capture antenna effects
Can capture behaviors that enable compatible reuse
Can capture environmental effects
Captures susceptibility to intermodulation
Enable greater resolution in spectrum management
Captures a definition of interference
Most constructs have probability data elements to declare confidence in parts that are variable or are uncertain
Combining Constructs into Models
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t0700 13 July 2013
1800 13 July 2013
Transmitter____________________________
Receiver____________________________
System____________________________Transmitter_1Transmitter_2
Transmitter_nReceiver_1Receiver_2
Receiver_m
End of System
Collection____________________________System_1System_2
System_iTransmitter_1Transmitter_2
Transmitter_jReceiver_1Receiver_2
Receiver_k
End of Collection
Power
Spectrum Mask
Power Map
1 10 100 1 103
1 104
1 105
160
140
120
100
80
60
40
20
0
Distance (log scale)
Pathloss (dB)
X1 Y1 Z1( )
Propagation Map
Location
Underlay Mask
20 dBm
Intermodulation Mask
XY
Z(
)
Time
A large volume that captures a complete mission
There is an XML schema for model construction
Constructs are used to model transmitters and receivers
Model and Collection Functions• System Model
– Consists of transmitter and receiver models that are part of a system
• Collective Consumption Listing– Lists uses of spectrum by systems,
transmitters and receivers – Heading identifies the time, space,
and frequencies over which the list is complete
• Spectrum Authorization Listing– List of system, transmitter, and receiver models identify
spectrum boundaries within which use is authorized
• Spectrum Constraint Listing– List of system, transmitter, and receiver models
identify existing uses of spectrum that have precedence with which new uses must be compatible
04/21/23 Doc #: 5-14-0052-02-subs 7
Transmitter____________________________
Receiver____________________________
System____________________________Transmitter_1Transmitter_2
Transmitter_nReceiver_1Receiver_2
Receiver_m
End of System
Collection____________________________System_1System_2
System_iTransmitter_1Transmitter_2
Transmitter_jReceiver_1Receiver_2
Receiver_k
End of Collection
Heading identifies the limits in time,
space, and frequencies over
which the list applies
Combining SCMML with Process Data• SCMML only intends to capture spectrum use
boundaries (necessary to be a loose coupler)• Most SM documents will use combinations of
schemata• Complementary schemata functions
– Cataloging models (e.g. modeler identity, version, date, …)
– Database control (e.g. regulatory administration, user ID, database ID, …)
– Enterprise management (e.g. manager ID, user organization, …)
– Negotiating service level agreements (e.g. party ID, price, probability of interference, enforcement data, remediation data, …)
– Markets (e.g. price, bid, signatures, …)– RF device policy (e.g. device ID, security codes, …)
• Complementary data does not need to cross domains
04/21/23 Doc #: 5-14-0052-02-subs 8
Federal Enterprise
Spectrum Market
SpectrumManager
DatabaseAdministrator
DatabaseAdministrator
CustomerDatabase
AdministratorCustomer
Customer
User
User
User
User
User
User
DatabaseAdministrator
Customer
A different complementary
schema may support each domain
What is included in the specification
• Overarching XML schema that defines the model “Spectrum Consumption Modeling Markup Language” (SCMML)– Data types for the fundamental data elements required within each
construct– Explicit data types for each construct– Transmitter, receiver, and system data types– A collection data type for collections of transmitters, receivers, and
system models
• Explanations– What each construct captures– How constructs work collectively to represent use boundaries– Methods and algorithms for computing compatibility between uses
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What models must convey
• The extent of RF emissions – i.e. the power spectral flux density of RF emissions anywhere with respect to a user
• A definition of what is interference – i.e. what emissions from another user would be considered harmful
• Time and location of use• If known, behaviors and features that enable
sharing04/21/23 Doc #: 5-14-0052-02-subs 10
How models are built
• Modeling from scratch requires:– Extensive knowledge of the system
being modeled• What does it emit• What interference is harmful• Understanding of the operational
use of the system
– Environmental data and propagation models
• Modeling will likely be supported by tools that capture the environment, propagation effects, and the unique features of the RF devices, e.g. antennas directivity
• SCM are an abstraction that do not require the detailed data and computations that are part of the tools
04/21/23 Doc #: 5-14-0052-02-subs 11
Knowledge in the model
Spectrum Consumption
Model
Tool 1
RF system characteristicsWhat constitutes interference
How the systems will
be used
Models of terrain and propagation
DETERMINING COMPATIBILITY
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Types of Spectrum Consumption• Transmitter – attenuation from the transmitter
• Receiver – attenuation toward the receiver
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log(d) log(d)
Power in dB scale
Pathloss exponent specifies the rate of attenuation toward the
receiver that secondary transmitters must assume to
assess their compliance
The receiver being protected
log(d) log(d)
Power in dB scalePathloss exponent specifies the rate of attenuation away
from the transmitter
The transmitter given the rightTotal power, propagation
maps and power maps have opposite meanings
Reveals the extent of RF emissions
Reveals what is harmful interference
Spectrum can be consumed without any
emissions
Compatibility Computations
• Constructs are a means to specify the factors that determine a link budget• Modelers build SCMs to identify the power spectral flux density of
transmissions and allowed interference • Assessment of compatibility determines if the interaction of the spectrum mask
of the transmitted signal is compatible with the underlay mask of the receiver
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1 10 100 1 103
1 104
160
140
120
100
80
60
40
20
0
10 log1
L f ht hr 10ld
10 log fr f 10ld
10ld
Distance (meters)
Signal Strength (dB)
Friis equation
2-ray model with vertical polarization, 1.7 meters high antennas
One-meter pathloss
A piecewise linear model Interference
threshold
Total Power +X
Y
Z
Total Power +
Power Spectral Flux Density of a transmission
+ +
Allowed Power Spectral Flux
Density of interference
Transmitter Receiver
A Link Budget Perspective
– TPrcvr – Total Power in the receiver model
– TPtmtr – Total power in the transmitter model
– AGtmtr – Antenna gain from the transmitter power map
– AGrcvr – Antenna gain from the receiver power map
– PL(d) – Pathloss as a function of distance using a propagation map model
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( )rcvr tmtr Masks tmtr rcvrTP TP PM AG AG PL d
General Process for Computing Compatibility
• Determine if uses will overlap in time and spectrum• Determine the constraining points (the point of primary
operation and the point of secondary operation that most restrict the secondary user)
• Compute the allowed transmit power of the secondary
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Primary broadcast user
Secondary mobile userConstraining primary receiver
Constraining secondary transmitter
The variety of means to specify locations and the use of directional antennas make the determination
of constraining points the most challenging part of computing
compatibility
FUNDAMENTAL DATA TYPES
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Fundamental data types
• Data types for commonly used variables: e.g. frequency, bandwidth, power, time, location, and direction
• Unique data types for special SCM data structures: e.g. masks and maps
• These are explicitly described in Chapter 5 of 1900.5-13-0043-02-drft
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Probability data type• Used in many of the modeling constructs and are associated with
particular aspects of the constructs• Data type tries to clarify what probability means in the model
– Approach: cumulative versus alternative
– Nature: fleeting versus persistent• For the fleeting nature, the probability refers to the fraction of time in a state and being in any
state is momentary• For the persistent nature, the probability refers to the likelihood of arriving at a state and being
in that state may persist
– Derivation: judgment versus estimated versus measured
• By default all alternatives are used in computing compatibility• Consideration of probability requires peer-wise agreement on the method• Probabilities of different construct types are considered independent
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0.8 0.8 0.2
1.0Cumulative Alternative
THE SCM CONSTRUCTS
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1 - Total Power
• Usually represents the value of the power driving an antenna at a transmitter and the allowed interference power after the antenna at a receiver
• Other constructs affect the power so there is flexibility to obfuscate specific system capabilities
• The probability element supports identifying a power distribution for systems that adapt their power or the specification of the probabilities of a collection of alternative discrete power levels
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A reference value to which other model
constructs refer20 dBm
2 – Spectrum Mask
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A list of inflection points that form a mask. Each
point consists of a frequency and relative
power. A resolution bandwidth conveys the spectral density of the
power terms, i.e. dB/BW.
Specifies the power-density spectrum of a
signal399.9 399.925 399.95 399.975 400 400.025 400.05 400.075 400.1
150
100
50
Power Spectral Density
(dB/10 kHz)
Frequency (MHz)
-.025-.05-.075 .075.05.0250
(399.925 MHz, -140 dB/10 kHz)
(399.95 MHz, -100 dB/10 kHz)
(399.975 MHz,-38 dB/10 kHz)
(400.025 MHz, -38 dB/10 kHz)
(400.05 MHz, -100 dB/10 kHz)
(400.075 MHz, -140 d dB/10 kHz)
Actual frequencies:
Relative frequencies:
(399.925, -140, 399.95, -100, 399.975, -38, 400.025, -38, 400.05, -100, 400.075, -140)BW = 10 kHz
(-0.075, -140, -0.05, -100, -0.025, -38, 0.025, -38, 0.05, -100, 0.075, -140)f = 400 MHz, BW = 10 kHz
Spectrum Masks – Continued - 2
• A spectrum mask conveys the spectral content of a signal • Data Structure
– The basic mask is a (1 n) array of real values alternating between frequency and power
– Resolution bandwidth is a real value and applies to all power terms in a mask
– Two versions• Continuous signal – the mask stands alone, frequencies are actual• Frequency hopped and pulsed signal – the mask is accompanied by
additional values, frequencies are relative to a center frequency– A center frequency list or a list of frequency bands,
where the pair identify the beginning and ending frequencies of a frequency band
– A dwell time– A revisit period
04/21/23 Doc #: 5-14-0052-02-subs 23
0 0 1 1, , , , ,x xf p f p f p
0 1 2, , , xf f f f 1 1 2 2, , , , ,b e b e bx exf f f f f f 1 1,b ef f
Spectrum Masks – Continued - 3
• Probabilities may be associated with masks– Alternative – One or the other of a set of masks
applies, e.g. radar scanning versus radar tracking– Cumulative – Multiple masks where those with
higher probabilities subsume those of lower probability, e.g. systems that may adapt the bandwidth of their transmissions
• When probabilities are used, there are multiple masks
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3 – Underlay Masks
04/21/23 Doc #: 5-14-0052-02-subs 25
Specifies limit to the allowed interference by
frequency
Together with the spectrum mask specifies the protection margin
(396, -90, 397, -110, 403, -110, 404, -90)BW = 10 kHz
A list of inflection points that form a mask. Each
point consists of a frequency and relative
power. A resolution bandwidth conveys the spectral density of the
power terms.394 396 398 400 402 404 406
100
50
0
sm2bn 1
sm2n 0 sm2n 0
(396 MHz, -90 dB/10 kHz)
(397 MHz, -110 dB/10 kHz)
(403 MHz, -110 dB/10 kHz)
(404 MHz, -90 dB/10 kHz)
Power Spectral Density
(dB/10 kHz)
Frequency (MHz)
-2-4 420
394 396 398 400 402 404 406
150
100
50
Protection Margin
(396 MHz, -70 dB/10 kHz)
(397 MHz, -90 dB/10 kHz)
(403 MHz, -90 dB/10 kHz)
(404 MHz, -70 dB/10 kHz)
Power Spectral Density
(dB/10 kHz)
Frequency (MHz)
-2-4 420
Underlay Mask – Continued - 2• Underlay masks may be one of two types
– Relative to the spectrum mask and so also dependent on propagation
– Constant over the location of the model so only dependent on the total power and the relative power density of the power map
• Before evaluation for compatibility, spectrum mask and underlay mask power spectral density terms must have the same bandwidth reference
• There are two methods for computing the power margin that results from the interaction of an underlay mask and an interfering signal’s spectrum mask– Total power– Maximum power density
04/21/23 Doc #: 5-14-0052-02-subs 26
394 396 398 400 402 404 406
150
100
50
Protection Margin
(396 MHz, -70 dB/10 kHz)
(397 MHz, -90 dB/10 kHz)
(403 MHz, -90 dB/10 kHz)
(404 MHz, -70 dB/10 kHz)
Power Spectral Density
(dB/10 kHz)
Frequency (MHz)
-2-4 420
394 396 398 400 402 404 406
100
50
0
sm2bn 1
sm2n 0 sm2n 0
(396 MHz, -90 dB/10 kHz)
(397 MHz, -110 dB/10 kHz)
(403 MHz, -110 dB/10 kHz)
(404 MHz, -90 dB/10 kHz)
Power Spectral Density
(dB/10 kHz)
Frequency (MHz)
-2-4 420
Underlay Mask – Continued - 3
• Total power method of computing power margin uses the underlay mask as an inverted filter that reduces the amount of the interfering signal’s energy signal that interferes
04/21/23 Doc #: 5-14-0052-02-subs 27
Frequency
Pow
er o
f S
pect
rum
Mas
kP
ower
of
Und
erla
y M
ask
Frequency
Pow
er o
f S
pect
rum
Mas
kP
ower
of
Und
erla
y M
ask
Energy beneath the underlay mask is subtracted from the
energy under the spectrum mask
Underlay Mask – Continued - 4
• Computing the power margin using total power method has four steps1. Determine the allowed interference the underlay permits2. Adjust the shape of the interfering spectrum mask based
on the shape of the receiver underlay mask3. Compute the total power in the reshaped spectrum mask4. Find the difference between the total power of the
reshaped spectrum mask and the allowed interference specified by the underlay mask
• There is a closed form solution for steps 1 and 3
04/21/23 Doc #: 5-14-0052-02-subs 28
Frequency (MHz)
dB
380 385 390 395 400 405 410 415 42040
20
0
Underlay Mask – Continued - 5
1. Determine the allowed interference the underlay permits
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Defined as the power beneath the lower 3 dB
bandwidth
Underlay Mask – Continued - 62. Adjust the shape of the interfering spectrum mask
based on the shape of the receiver underlay mask
04/21/23 Doc #: 5-14-0052-02-subs 30
Underlay mask
Spectrum mask
Reshaped mask
Mask extends the full bandwidth of the underlay
Frequency (MHz)
dB
380 385 390 395 400 405 410 415 42040
20
0
Frequency (MHz)
dB
380 390 400 410 420100
80
60
40
Frequency (MHz)
dB
380 390 400 410 420150
100
50
Underlay Mask – Continued - 73. Compute the total power in the reshaped spectrum
mask
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Frequency (MHz)
dB
380 390 400 410 420150
100
50
Given two consecutive inflection points,and , , the equation for the line is
where and . . The total power under the segment is determined in the linear scale and so within the segment between and ,
is . For segments where
and , ,
where and , ,
and where , .
1 1,f p 2 2,f p 1 2f f
0 1p b b f 0 1 1 1b p b f 2 1
12 1
p pb
f f
af bf 1 2a bf f f f 0 1
1010b
a
b b ff
f
p dfRBW
1 0b
a bf f
0 1
10
1
1010
ln 10
b
a
fb b f
f
pRBW b
1 0b a bf f0
1010b
a
fb
f
p f
a bf f 0p
Underlay Mask – Continued - 8
4. Find the difference between the total power of the reshaped spectrum mask and the allowed interference specified by the underlay mask
04/21/23 Doc #: 5-14-0052-02-subs 32
Frequency (MHz)
dB
380 385 390 395 400 405 410 415 42040
20
0
Frequency (MHz)
dB
380 390 400 410 420150
100
50
PMMask = -
Underlay Mask – Continued - 9
• Maximum power density method of computing power margin– Determine the adjustment of the spectrum mask to ensure its power levels
are beneath the underlay mask
04/21/23 Doc #: 5-14-0052-02-subs 33
394 396 398 400 402 404 406100
50
0
Compatible transmission
This spectrum mask violates the boundary of
the underlay mask
Criteria for compatibility with underlay mask using the maximum power density method of power margin
computation
380 390 400 410 420100
50
0
380 390 400 410 420100
50
0
Frequency (MHz)
dB
Frequency (MHz)
-8.56 dB
Underlay Mask - 10
• Variants of the underlay mask allow identifying differences in robustness to interference based on bandwidth, frequency hopping, and duty cycle of interfering signals
• In compatibility computations the spectrum masks are mapped to the least restrictive underlay mask for which they meet the criteria of use
04/21/23 Doc #: 5-14-0052-02-subs 34
394 396 398 400 402 404 406
100
50
0
sm2bn 1
sm2bn 1 8
sm2bn 1 15
sm2bn 1 25
sm2n 0 sm2n 0
Power Spectral Density
(dB/10 kHz) 396, 90,397, 110,403, 100,404, 90
Multiple Mask Structure
396, 82,397, 102,403, 102,404, 82
396, 75,397, 95,403, 95,404, 75
396, 65,397, 85,403, 85,404, 65 @ 25 kHz
@ 100 kHz
@ 250 kHz
Single Mask with Offset Data Structure
396, 90,397, 110,403, 100,404, 90
25,25,100,15,250,8
@ 25 kHz@ 100 kHz@ 250 kHzOtherwise
Frequency (MHz)
190.2 190.25 190.3 190.35 190.4 190.45 190.5 190.55
100
50
0
Data Structure with Bandwidth-Time ProductRatings
190.25, 90,190.3, 110,190.45, 100,190.5, 90
500,30,1500,20,2500,10@ 500 Hz∙sec
@ 1500 Hz∙sec
@ 2500 Hz∙sec
Otherwise
Power Spectral Density
(dB/10 kHz)
Frequency (MHz)
190.2 190.25 190.3 190.35 190.4 190.45 190.5 190.55
100
50
0
Data Structure with Duty CycleRatings
190.25, 90,190.3, 110,190.45, 100,190.5, 90
0.02,10 sec,30,0.05,15 sec,20,0.1,15 sec,10 2% DC, 10 sec DT
5% DC, 15 sec DT
10% DC, 15 sec DT
Otherwise
Power Spectral Density
(dB/10 kHz)
Frequency (MHz)
Accounting for Signal Spaces• Used with underlay masks designed for the maximum power spectral
density method of computing compatibility• Provide separate masks for different narrowband signal spaces
– A signal space is defined as the bandwidth of a signal at 20 dB below its maximum amplitude (This is arbitrary and could be something else. 3 dB did not seem appropriate.)
– Independent masks are made for each signal space or a single mask is used with a list of adjustments of the form (BW0, p0, BW1, p1, …, BWx, px)
04/21/23 Doc #: 5-14-0052-02-subs 35
394 396 398 400 402 404 406
100
50
0
sm2bn 1
sm2bn 1 8
sm2bn 1 15
sm2bn 1 25
sm2n 0 sm2n 0
Frequency (MHz)
Power 396, 90,397, 110,403, 100,404, 90
Multiple Mask Structure
396, 82,397, 102,403, 102,404, 82
396, 75,397, 95,403, 95,404, 75
396, 65,397, 85,403, 85,404, 65 @ 25 kHz
@ 100 kHz
@ 250 kHz
Single Mask with Offset Vector
396, 90,397, 110,403, 100,404, 90
25,25,100,15,250,8
@ 25 kHz@ 100 kHz@ 250 kHzOtherwise
Determining Bandwidth
• Bandwidth at -20 dB from the maximum power
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Frequency (MHz)
Power
23.3 kHz 150 kHz
400 400.25 400.5 400.7595
70
45
20
5
sm9n 1
sm9bn 1
sm9n 0 sm9bn 0
Signal Space Example
• What combinations of interfering signals are tolerable?
04/21/23 Doc #: 5-14-0052-02-subs 37
394 396 398 400 402 404 406180
160
140
120
100
80
60
sm2bn 1
sm2bn 1 8
sm2bn 1 15
sm2bn 1 25
Ua n 1
Ub n 1
Uc n 1
Ud n 1
Ue n 1
Uf n 1
sm2n 0 sm2n 0 sm2n 0 sm2n 0 Ua n 0 Ub n 0 Uc n 0 Ud n 0 Ue n 0 Uf n 0
AF
EDCB
Frequency (MHz)
Power
25 kHz
100 kHz
250 kHzSignal BW
(kHz)
PSD (dBM/Hz)
A 25 -93
B 100 -105
C 150 -101
D 25 -88
E 150 -87
F 100 -104
Determining Effective Bandwidth and PSD• Effective bandwidth is the sum of the
bandwidths• Effective maximum power spectral density
(EPD) is a normalized power spectral density of the collection of signals (assumes the same resolution bandwidth)
• If both the effective bandwidth and the EPD are less than the limits of a bandwidth rated mask then the collections of interfering signals is compliant
• Otherwise adjust to the bandwidth of the next highest bandwidth underlay– Spread the power spectral density
to the bandwidth of the mask that is being used
04/21/23 Doc #: 5-14-0052-02-subs 38
max
10
10
10
10 log
xp
xx
xx
BW
EPDBW
101010 log 10
EPD xx
mask
BWBAEPD
BW
Results for the Example
04/21/23 Doc #: 5-14-0052-02-subs 39
Signals Effective
Bandwidth Effective
PSD Mask
Bandwidth
Bandwidth Adjusted
Effective PSD
Mask PSD Criterion
Compliance
A, B 125 kHz -104.8 dB 250 kHz -107.8 dB -102 dB Yes A, C 175 kHz -101.3 dB 250 kHz -102.9 dB -102 dB Yes A, D 50 kHz -90.9 dB 100 kHz -93.9 dB -95 dB No B, C 250 kHz -102.2 dB 250 kHz -102.2 dB -102 dB Yes B, D 125 kHz -94.7 dB 250 kHz -97.7 dB -102 dB No C, D 175 kHz -95.3 dB 250 kHz -96.9 dB -102 dB No
A, B, C 275 kHz -102.3 dB NA No A, B, D 150 kHz -95.3 dB 250 kHz -97.6 dB -102 dB No A, C, D 200 kHz -95.8 dB 250 kHz -96.8 dB -102 dB No B, C, D 275 kHz -97 dB NA No
Using a mask designed for the total power method of mask interaction is usually a better choice for
indicating narrowband signal tolerance
Accounting for Frequency Hopping• Used with either method of computing mask interaction• Provide separate masks for different bandwidth time products
(BTP)– A BTP is the product of the average amount of time a signal exists in the
band of the mask and the bandwidth of the particular signal– A single mask is used with a list BTP vs power adjustment of the form
((BWT)0,p0, (BWT)1,p1, ---(BWT)x,px)
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190.2 190.25 190.3 190.35 190.4 190.45 190.5 190.55
100
50
0
Frequency (MHz)
Power
Data Structure with Bandwidth-Time ProductRatings
190.25, 90,190.3, 110,190.45, 100,190.5, 90
500,30,1500,20,2500,10@ 500 Hz-sec
@ 1500 Hz-sec
@ 2500 Hz-sec
Otherwise
Frequency Hopping Example
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System 1
Spectrum mask: (-0.0125, -20, -0.0075, 0, 0.00750, 0, 0.0125, -20)
Frequency list: ( 190.0, 190.025, 190.050, , 194.975) (i.e. signals spaced every 25 kHz starting at 190 MHz and ending at 194.975 MHz)
Dwell time: 100 sec
Revisit time: 20 msec
System 2
Spectrum mask: (-0.0125, -20, -0.0075, 0, 0.00750, 0, 0.0125, -20)
Frequency band list: (190.0,193.5, 196.5,205.5, 211.0, 218.5)
Dwell time: 200 sec
Revisit time: 1.0 msec
190.2 190.25 190.3 190.35 190.4 190.45 190.5 190.55140
120
100
80
60
40
20
0
@ 500 Hz∙sec@ 1500 Hz∙sec
@ 2500 Hz∙sec
System 1
System 2
Frequency (MHz)
Power
Two frequency hopping systems
Frequency hop power levels at a BTP rated receiver
1 sec10 25 kHz 100 μsec 1250 Hz sec
20 msecBTP
BTP from System 1
BTP from System 2
250 kHz 1 sec50 kHz 200 μsec 125 Hz sec
20,000 kHz 1 msecBTP
Since the combined BTP of the two systems, 1375 Hzsec, which is less than the 1,500 Hzsec mask and the power level of both frequency hop systems is less than the power rating of that mask the use of both is compatible
Channel Definition
Band Definition
Accounting for Duty Cycle
• Used with either method of computing mask interaction• Provide separate masks for different interference duty cycles
– A duty cycle is the fraction of time a signal is turned-on, on average– Each mask is qualified by a duty cycle and the maximum dwell time
when the signal is being transmitted
04/21/23 Doc #: 5-14-0052-02-subs 42
190.2 190.25 190.3 190.35 190.4 190.45 190.5 190.55
100
50
0
Data Structure with Duty CycleRatings
190.25, 90,190.3, 110,190.45, 100,190.5, 90
0.02,10 sec,30,0.05,15 sec,20,0.1,15 sec,10 2% DC, 10 sec DT
5% DC, 15 sec DT
10% DC, 15 sec DT
Otherwise
Power Spectral Density
(dB/10 kHz)
Frequency (MHz)
Probability with Underlay Masks
• Underlay masks may be defined with a cumulative approach and a fleeting nature• This allows consideration of all variations of constructs qualified with fleeting nature
probabilities
04/21/23 Doc #: 5-14-0052-02-subs 43
Probability = 1.00
Probability = 0.99Probability = 0.97Probability = 0.95
Power Spectral Density
(dB/10 kHz)
Frequency (MHz)190.2 190.25 190.3 190.35 190.4 190.45 190.5 190.55
100
50
0
Protocol and Policy Indexing
• Provides a means to account for behaviors that allow spectrum sharing
• A specific underlay mask is associated with a particular protocol or policy definition– Meaning: a coexisting system that uses the
specified protocol or policy may use the associated mask for the assessment of compatibility
04/21/23 Doc #: 5-14-0052-02-subs 44
Selecting the Underlay Mask
• A model of a receiver may use multiple underlay masks
• As described there are criteria that must be met in order to use a particular map
• In assessing compatibility, use the map that is least restrictive for which the criteria is met
04/21/23 Doc #: 5-14-0052-02-subs 45
Map Preliminaries
• Coordinate systems– Earth centric– Earth surface– Platform
• Rotation matrices• Coordinate conversions• Map data structures
04/21/23 Doc #: 5-14-0052-02-subs 46
Earth Centric Coordinates• The earth is shaped as an ellipsoid
– Multiple ellipsoid datums exist that best represent the Earth’s surface at different geographic locations
– We use the same ellipsoid used by GPS, the WGS-84
04/21/23 Doc #: 5-14-0052-02-subs 47
The WGS 84 Ellipsoid Parameters
Parameter Value Units a 6378137 meters b 6356752.31245 meters f 1
298.257223563
e 0.0818191908426 e2 0.00669437999014
2 2 2 21 sin 1 2 sin
a a
e f f
cos cosx h
cos siny h
21 sinz e h
Earth’s Surface Coordinates• The x axis points to the north axis of the earths rotation, the y
axis points east, and the z axis points toward the center of the earth
04/21/23 Doc #: 5-14-0052-02-subs 48
Long,
Lat,
x
y
z
y2
x2
z2
Orientation with respect to earth centric
coordinates changes by location
Platform Coordinates
• x axis points in the direction of travel and the z axis points in the direction that is typically toward the center of the earth
04/21/23 Doc #: 5-14-0052-02-subs 49
x
y
z
Rotation Matrices• Rotations follow the right hand rule
– Rotations about the x axis moves the y axis toward the z axis
– Rotations about the y axis moves the z axis toward the x axis
– Rotations about the z axis moves the x axis toward the y axis
04/21/23 Doc #: 5-14-0052-02-subs 50
1 0 0
0 cos sin
0 sin cosxR
z
y
x
cos 0 sin
0 1 0
sin 0 cosyR
z
y
x
Slide 50 John A. Stine, MITRE
cos sin 0
sin cos 0
0 0 1zR
z
y
x
Earth to Surface Rotations
• Converts a coordinate system from earth centric coordinates to one on the earth’s surface
• The inverse rotation
04/21/23 Doc #: 5-14-0052-02-subs 51
2 , 90 180E S y z yR R R R
2 , 180 90S E y z yR R R R
Long,
Lat,
x
y
z
x1
y1
z1
Long,
Lat,
x
y
z
x2
y2
z2
Long,
Lat,
x
y
z
90-
y2
x2
z2
Rotation about the y1 axis Rotation about z1 Rotation about y2
Other Rotations• Between Earth’s surface and travel direction
• Between travel direction and platform coordinates
• Between power map coordinates and platform coordinates
04/21/23 Doc #: 5-14-0052-02-subs 52
2 ,S T y zR R R
2 ,T S z yR R R
2 , ,T P x y zR R R R
2 , ,P T z y xR R R R z
y
x
yaw,
roll, pitch,
2 , ,P A x y zR R R R
2 , ,A P z y xR R R R
Coordinate Conversions
• Converting coordinates between earth and surface coordinates involves a translation to the new origin and then a rotation
• The inverse
04/21/23 Doc #: 5-14-0052-02-subs 53
o
2 o
oS WGS84 WGS84
,E S
n x x
e R y y
v z z
o
2 o
oWGS84 S WGS84
,S E
x n x
y R e y
z v z
The Map Data Structure - 1A method to assign values to a solid angle
04/21/23 Doc #: 5-14-0052-02-subs 54
y
x
z
(0, 0, n0,0, 0,1, n0,1, 0,2, …, 360 1, 0, n1,0, 1,1, n1,1, 1,2, …, 360, 2, 0, n2,0, …, nlast, 360, 180)
Annulus
Sector
n1,1 is the value associated with the solid angle that extends from
elevation 1 to 2 and from azimuth 1,1 to 1,2
The Map Data Structure – 2Reduce the map size by eliminating the obvious information
04/21/23 Doc #: 5-14-0052-02-subs 55
(0, 0, n0,0, 0,1, n0,1, 0,2, …, 360 1, 0, n1,0, 1,1, n1,1, 1,2, …, 360, 2, 0, n2,0, …, nlast, 360, 180)
Always begin with 0,0
combination,
The 0 azimuth always follows the 360 –
elevation combination
The map always ends with the
360,180 combination
(n0,0, 0,1, n0,1, 0,2, …, 360 1, n1,0, 1,1, n1,1, 1,2, …, 360, 2, n2,0, …, nlast, 0)
Remove the leading 0,0 combination
Remove the 0 that follows elevations
Use 0 to mean the 360,180 combination
Maps can provide as much resolution as necessary where necessary
Example Maps
04/21/23 Doc #: 5-14-0052-02-subs 56
(0, 0)
(-10 ,360, 90, -10, 150, 5, 165, -10, -360, 105, -10, 0)
(5 , 125, 0, 155, -10, 270, -5, 360, 100, 2, 0)
(-5, 360, 80, 3, 360, 100, -5, 0)
4 – Power Map
04/21/23 Doc #: 5-14-0052-02-subs 57
A variable length n x 1 array that assigns power
levels to solid angles about a point
Specifies the relative power density by
direction
X Y Z( )
(-20, 70, -25, 120, -30, 160, -35, 360, 150, -35, 0)
20 dB/m2
Power Map – Continued - 2
• Provides a directional gain• Together with the total power
and spectrum mask (or underlay mask), specifies the power spectral flux density in a direction
• The direction power spectral flux density is used as the 1-meter power in the linear and piecewise linear log distance pathloss model (Part of a farfield model)
• Power maps may include phenomenology in addition to antenna gain (e.g. insertion loss, environmental effects,…)
04/21/23 Doc #: 5-14-0052-02-subs 58
1 10 100 1 103
1 104
160
140
120
100
80
60
40
20
0
10 log1
L f ht hr 10ld
10 log fr f 10ld
10ld
Distance
Signal Strength (dB)
Friis equation
2-ray model with vertical polarization, antennas 1.7 meters high
A conservative model
1-meter pathloss
Power + +or
= power spectral flux density 2dBm
Hz m
dBm dBHz
2dB
m
Power Map – Continued - 3• Usually, the coordinate system of the power map is the same as the
coordinate system of the propagation map• Exceptions
– When referenced to a platform, rotation may be specified by the angles <, , >
– Direction may be fixed toward a point (antenna steers as the platform moves always pointing in the direction of the specified point)
– Concentric maps used to specify scanning of directional beams, the outer map indicates the scanning region and the inner map defines the directional beam that is scanned
04/21/23 Doc #: 5-14-0052-02-subs 59
z
y
x
X Y Z( )
Hierarchical Power Map
• Scanning region specified by one power map– Logical true value in the direction of
scanning – Logical false in the directions not scanned
• Antenna pattern specified by the second map
04/21/23 Doc #: 5-14-0052-02-subs 60
This beam may be point anywhere in these directions
True
False
5 – Propagation Map
04/21/23 Doc #: 5-14-0052-02-subs 61
X Y Z( )
A variable length n x 1 array that assigns
parameters of a pathloss model to solid angles
about a point. There are two models, linear and
piecewise linear on a dB to log distance
Specifies the rate of attenuation by
direction(2, 40, 2.07, 130, 2.13, 230, 2, 0)
In a linear model a pathloss exponent is assigned to each solid angle. In a piecewise linear model a pathloss exponent, a distance, and a second pathloss exponent is assigned to each direction
(2, 550, 3.2, 40, 2.07, 400, 3.5, 130, 2.13, 350, 3.3, 230, 2, 550, 3.2, 0)
Propagation Modeling Objectives - 1
• Many tools invest heavily in propagation modeling– Databases of terrain features– Models that capture the effects of the terrain features and manmade
objects
• An important feature of spectrum consumption modeling is that the propagation model is a part of the model of spectrum use rather than just a part of a tool– Eliminates the need to have a common tool
• Does not require a common database of terrain• Allows innovation in propagation modeling within tools• Spectrum use decisions can be made at devices
– Abstraction chosen to allow tractable computations of compatibility– Common assessments of compatibility everywhere
04/21/23 Doc #: 5-14-0052-02-subs 62
Propagation Modeling Objectives - 2
• Modelers may use tools of their choice to create propagation maps
• Propagation modeling is artful– Many features in SCM to support differentiation of propagation
effects– Modeling may become a service in a system– Models may be negotiated between parties
04/21/23 Doc #: 5-14-0052-02-subs 63
Does not require all tools to use the same methods of
analyzing propagation or to have common databases of
terrain data
Propagation Map – Continued – 2Linear Log Distance Pathloss Model
• Conveys the rate transmissions attenuate by direction, by providing the pathloss exponent of a log distance pathloss model
04/21/23 Doc #: 5-14-0052-02-subs 64
1 10 log( )RP d RP m n d
1 10 100 1 103
1 104
1 105
160
140
120
100
80
60
40
20
0
Conservative model that puts a bound on maximum signal strength
Can use different exponents to prefer near or long range fidelity
Underestimates attenuation at long range
Distance (log scale)
Pathloss (dB)
1-meterpathloss
Propagation Map – Continued – 3Piecewise Linear Log Distance Pathloss Model
• Map stores two exponents and a breakpoint distance per direction
04/21/23 Doc #: 5-14-0052-02-subs 65
1 10 100 1 103
1 104
1 105
160
140
120
100
80
60
40
20
0
Piecewise linear model eliminates the need to compromise
Distance (log scale)
Pathloss (dB)
1
1 2
1 10 log( )
1 10 log 10 log log
breakpoint
breakpoint breakpoint breakpoint
RP m n d d dRP d
RP m n d n d d d d
1-meterpathloss
Propagation Map Data and Meaning
• The map data structures
• Units of exponents are dimensionless and distances are in meters
• The coordinate system of propagation maps is coincident to Earth’s surface coordinates
04/21/23 Doc #: 5-14-0052-02-subs 66
0,0 0,1 0,1 0,2 1 1,0 1,1 2 2,0, , , , ,360 , , , , ,360 , , , ,0lastn n n n n
0,0 0,0 0,0 0,1 0,1 0,1 0,1 0,2 1 1,0 1,0 1,0 1,1 2 2,0 2,0 2,01 , , 2 , , 1 , , 2 , , ,360 , , 1 , , 2 , , , ,360 , , 1 , , 2 , , 1 , , 2 , ,0last last lastn d n n d n n d n n d n n d n
Linear model
Piecewise linear model
Methods to Differentiate Propagation Effects
• Map direction– Use elevations to differentiate antenna height (short range)– Use azimuths to differentiate terrain effects by direction
• Antenna height rated masks – Used for long range terrestrial propagation– Height rating refers to the height of the distant antenna above the
terrain– Only azimuths in the mask have relevance– A model may have multiple height rated masks and pathloss is
interpolated for heights in-between
• Location indexing– Assign different maps to different parts of an operating location
04/21/23 Doc #: 5-14-0052-02-subs 67
1 10 100 1 103 1 10
4 1 105 1 10
6250
200
150
100
50
0
Height Rated Propagation Maps
04/21/23 Doc #: 5-14-0052-02-subs 68
1 10 100 1 103 1 10
4 1 105 1 10
6250
200
150
100
50
0
1 10 100 1 103 1 10
4 1 105 1 10
6250
200
150
100
50
0
1 10 100 1 103 1 10
4 1 105 1 10
6250
200
150
100
50
0
Antenna height 2 mDistance from shore 15 km
Antenna height 10 mDistance from shore 15 km
Antenna height 30 mDistance from shore 15 km
Antenna height 60 mDistance from shore 15 km
Piecewise linear modeln1 = 2dbreakpoint = 25,000
n2 = 7.5
Piecewise linear modeln1 = 2dbreakpoint = 7,200
n2 = 6
Piecewise linear modeln1 = 2dbreakpoint = 19,000
n2 = 7.2
Piecewise linear modeln1 = 2dbreakpoint = 31,000
n2 = 8
Using Probability with Propagation Maps
• Much of the variability in received signal strength is associated with propagation
• Probability may be used with propagation maps to convey the distribution
04/21/23 Doc #: 5-14-0052-02-subs 69
1 10 100 1 103 1 10
4 1 105 1 10
6300
250
200
150
100
50
0
Distance (meters)
Signal Strength (dB)
80009000
11000
Antenna height 2 mDistance from shore 15 km
(2, 11000, 6, 0) h = 2, p = 1.0
(2, 9000, 6, 0) h = 2, p = 0.95
(2, 8000, 6, 0) h = 2, p = 0.90
Any of the parameters can change, here we change the
breakpoint distance
Important Points in Propagation Modeling
• Modelers can differentiate their services by the tools they have to create models
• Both transmitter and receiver models have propagation maps; rules or negotiation determine which to use– Transmitter map is used to assess system compliance to
their proposed emissions– Possible rules for compatibility computations
• Based on user precedence• Give preference to receiver models• …
04/21/23 Doc #: 5-14-0052-02-subs 70
6 – Intermodulation (IM) Mask
04/21/23 Doc #: 5-14-0052-02-subs 71
A list of inflection points, frequency and relative power, that form a filter mask
(394, -100, 396, -50, 398, -40, 402, -40, 404, -50, 406, -100)
Specifies how signals amplitudes are combined for a particular order of
IM distortion
May be associated with a receiver or a transmitter
392 394 396 398 400 402 404 406 408
100
80
60
40
sm8n 1
sm8n 0
(394 MHz, -100 dB) (406 MHz, -100 dB)
(396 MHz, -50 dB)(404 MHz, -50 dB)
(398 MHz, -40 dB) (402 MHz, -40 dB)
Frequency (MHz)
Power
IM Interference
• IM is the creation of frequency components that are the sum and differences of the frequency of signals that mix in non-linear components– For Example, given f1 and f2, f1>f2
• Second order IM: 2f1, 2f2, f1+f2, f1-f2
• Third order IM: 3f1, 3f2, 2f1+f2, f1+2f2, 2f1-f2, 2f2-f1
• IM products may be created within a receiver or be transmitted
04/21/23 Doc #: 5-14-0052-02-subs 72
Receiver IM Interference
• IM products are created in the RF components from adjacent band use of spectrum– that fall within the pass band of receiver and so are
perceived as interference– Includes image frequencies when heterodyning is
used
• An IM Combining (IMC) masks defines how incoming signals combine
04/21/23 Doc #: 5-14-0052-02-subs 73
Using an IMC Mask
• The IMC mask specifies how signals that are inputs are shaped and amplified before combining by the characteristics of the device– The portion of the input mask that falls within the
bandwidth of the IMC mask is scaled by the power level of the IMC mask
04/21/23 Doc #: 5-14-0052-02-subs 74
380 385 390 395 400 405 410 415 420 42580
60
40
20
0
380 385 390 395 400 405 410 415 420 42580
60
40
20
0
380 385 390 395 400 405 410 415 420 425100
80
60
40
20
Input signals IMC Mask Scaled outputs
Using an IMC Mask - 2
• The shaped signals are reduced to four points prior to combining them, the end points to maintain bandwidth and the two highest power points to capture amplitude
04/21/23 Doc #: 5-14-0052-02-subs 75
380 385 390 395 400 405 410 415 420 425100
80
60
40
20
Using an IMC Mask - 3
• Combine signals two at a time– Consider the two masks for signals Sa and Sb
– The IM of the sum (Sa + Sb) is computed as the sum of the frequencies and powers of each point
– The IM of the difference (Sa – Sb) is computed as the difference of the frequencies and the sum of the powers but using the points in Sb in reverse order
04/21/23 Doc #: 5-14-0052-02-subs 76
0 0 1 1 2 2 3 3, , , , , , ,a a a a a a a af p f p f p f p 0 0 1 1 2 2 3 3, , , , , , ,b b b b b b b bf p f p f p f p
0 0 0 0 1 1 1 1 2 2 2 2 3 3 3 3, , , , , , ,a b a b a b a b a b a b a b a bf f p p f f p p f f p p f f p p
0 3 0 3 1 2 1 2 2 1 2 1 3 0 3 0, , , , , , ,a b a b a b a b a b a b a b a bf f p p f f p p f f p p f f p p
Using an IMC Mask - 4
• Consider the intermodulation product (2Sa – Sb)
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380 385 390 395 400 405 410 415 420 425100
80
60
40
20
770 775 780 785 790 795 800 805 810 815100
80
60
40
20
365 370 375 380 385 390 395 400 405 410100
80
60
40
20
Sa
Sb
2Sa
2Sa – Sb
Alternatives to Define IM Product
• Discussions may result in other methods for creating the IM products.
• Example– Input masks can be divided into multiple bins– The combining of two masks would tally the result of
combining each combination of bins from the two masks– Underlay masks power level would be scaled as
appropriate
04/21/23 Doc #: 5-14-0052-02-subs 78
Assessing Interference• Once the IM product is defined the interference is assessed
like any other signal using the receivers underlay mask
04/21/23 Doc #: 5-14-0052-02-subs 79
Underlay mask
Spectrum mask
Reshaped mask
Mask extends the full bandwidth of the underlay
Frequency (MHz)
dB
380 385 390 395 400 405 410 415 42040
20
0
380 390 400 410 420150
100
50
365 370 375 380 385 390 395 400 405 410100
80
60
40
20
Image Frequencies
• The IMC mask data structure indicates it is used for image frequencies by providing the intermediate frequency (IF) and injection side– The IMC mask models the characteristics of the front end– The IF and injection side identifies the local oscillator
frequency, fLO
04/21/23 Doc #: 5-14-0052-02-subs 80
if Low side injection
if High side injection
if Low side injection
if High side injection
c IF IF c
c IF IF cLO
IF c IF c
c IF IF c
f f f f
f f f ff
f f f f
f f f f
if Low side injection
if High side injectionLO IF
imageLO IF
f ff
f f
2underlay LO imagef f f
Image Frequencies - 2
• Rather than determining the image input to a receiver, create an image underlay mask
04/21/23 Doc #: 5-14-0052-02-subs 81
The image underlay mask is a reflection of the underlay mask
about the local oscillator frequency further shaped by
the IM mask
Use it as any other mask to determine interference
Transmitter IM Interference• IM products are emitted from the transmitter• The transmitter signal is an input to the IM product• Two masks are used, an IMC mask is used to show how
signals combine and an output mask defines how signals are amplified– IMC masks indicates the attenuation to the distant input prior to
combining – The attenuated distant input is combined with the unamplified
transmitter signal defined by the total power and spectrum mask combination
– The output mask indicates the amplification of the IM product prior to the power map
04/21/23 Doc #: 5-14-0052-02-subs 82
7 – Platform
04/21/23 Doc #: 5-14-0052-02-subs 83
The name of a platform
Specifies a facility, platform ,or device where radio systems may be co-located and so interact to
form IMMay be either a specific
platform or a class of platforms
Vehicle #27
2-41 Command Vehicle
8. Location
04/21/23 Doc #: 5-14-0052-02-subs 84
The use of smaller volumes to capture segments of a mission
Locations may be points, volumes,
trajectories, or orbits (piecewise tracks)
Identifies where systems are operated
Location Modeling
• Conveys the location or region where RF components may be
• When an area or volume is given it is assumed that the transmitter or receiver can be anywhere in that space
• Spectrum consumption models do not model terrain and where appropriate terrain effects should be captured in the model’s propagation and power maps
04/21/23 Doc #: 5-14-0052-02-subs 85
Locations
• Point – a fixed location, <,,a>• Terrestrial surface area – a region assumed on the
Earth’s surface with fixed height antennas– Point surface area is defined by a point, <,,a,ah>– Circular area is define by a point and a radius, <,,a,r,ah>– Convex polygon area is defined by a series of points that are
connected in the order given with the last connected to the first, <(0, 0,a 0, 1, 1,a 1,…, n-1, n-1,a n-1)ah>
• Altitudes of locations between points are interpolated
– May specify antenna height relative to ground or relative to average terrain height
04/21/23 Doc #: 5-14-0052-02-subs 86
Locations - 2
• Volume Modeling– Cylinders are specified by a point, a radius and a height
<,,a,r,h>– Polyhedrons are specified by a series of points and a
height <(0, 0,a 0, 1, 1,a 1,…, n-1, n-1,a n-1),h>• Lower surface defined by the lowest altitude
– Lower and upper surfaces are parallel to the WGS- 84 tangent plane
• At a cylinder center• At centroid of the polyhedron for a plane the intersects the
lowest point
04/21/23 Doc #: 5-14-0052-02-subs 87
Locations - 3
• Track– Specified by a point, heading, and velocity
< ,,a,,,v>
04/21/23 Doc #: 5-14-0052-02-subs 88
9 – Start Time
• Used to identify the start of a model and periodic variations of use
• Start time is referenced to Coordinate Universal Time (UTC) <YYYY,MM,DD,hh,mm,ss.s,hh0,mm0>
• Periodic use is specified by three durations <durationd,durationon,durationoff>– Durationd is the displacement of the first on period from
the start time– Durationon and durationoff are what their name implies and
they repeat
04/21/23 Doc #: 5-14-0052-02-subs 89
Start Time - 2
• Durations are expressed in the ISO 8601 format of PnYnMnDTnHnMnS where – nY is the number of years, – nM is the number of months, – nD is the number of days, – nH is the number of hours, – nM after the T value is the number of minutes, and – nS is the number of seconds. – The P designator is always present. – The T designator is only used when one of the time
elements of hours, minutes, or seconds is present.
04/21/23 Doc #: 5-14-0052-02-subs 90
10 – End Time
• Used to identify when the model ends• End time is referenced to Coordinate
Universal Time (UTC) YYYY,MM,DD,hh,mm,ss.s,hh0,mm0>
• The end time should follow the start time
04/21/23 Doc #: 5-14-0052-02-subs 91
11 – Minimum Power Spectral Flux Density
04/21/23 Doc #: 5-14-0052-02-subs 92
-150 dBW/m2/Hz
A reference value used with a transmitter model to imply the
extent of receiver locations
394 396 398 400 402 404 406100
50
0
log(d1)
Po
we
r in
dB
sca
le
Bound on the transmitter power
Primary transmitter
Distance to the model boundary
Signal to interference margin, PMunderlay
Point where the signal attenuates to the minimum power density
Attenuation from the transmitter to the model
boundary
PMr_prop(d1)PMmasks= 0dB
12 – Protocol or Policy
04/21/23 Doc #: 5-14-0052-02-subs 93
Used to specify behaviors that can be exploited or behaviors that are compatible
t
Primary TDMA User
A cooperative DSA Use
t
DSA users vacate the channel at the TDMA boundary of the
primary user
What is a spectrum policy for cognitive radio?
• Policy - – a) A set of rules governing the behavior of a system.
NOTE 1―Policies may originate from regulators, manufacturers, developers, network and system operators, and system users. A policy may define, for example, allowed frequency bands, waveforms, power levels, and secondary user protocols.
– b) A machine interpretable instantiation of policy as defined in (a)NOTE 2―Policies are normally applied post manufacturing of the radio as a configuration to a specific service application.NOTE 3—Definition b) recognizes that in some contexts the term “policy” is assumed to refer to machine understandable policies
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IEEE STD 1900.1, 2008
What is a spectrum policy for cognitive radio? - 2
• Cognitive Radio- – a) A type of radio in which communication systems are
aware of their environment and internal state and can make decisions about their radio operating behavior based on that information and predefined objectivesNOTE ― The environmental information may or may not include location information related to communication systems.
– b) Cognitive radio [as defined in item a)] that uses software-defined radio, adaptive radio, and other technologies to adjust automatically its behavior or operations to achieve desired objectives
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IEEE STD 1900.1, 2008
Model and Collection Functions• System Model
– Consists of transmitter and receiver models that are part of a system
• Collective Consumption Listing– Lists uses of spectrum by systems,
transmitters and receivers – Heading identifies the time, space,
and frequencies over which the list is complete
• Spectrum Authorization Listing– List of system, transmitter, and receiver models identify
spectrum boundaries within which use is authorized
• Spectrum Constraint Listing– List of system, transmitter, and receiver models
identify existing uses of spectrum that have precedence with which new uses must be compatible
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Transmitter____________________________
Receiver____________________________
System____________________________Transmitter_1Transmitter_2
Transmitter_nReceiver_1Receiver_2
Receiver_m
End of System
Collection____________________________System_1System_2
System_iTransmitter_1Transmitter_2
Transmitter_jReceiver_1Receiver_2
Receiver_k
End of Collection
Heading identifies the limits in time,
space, and frequencies over
which the list applies
Recall
What is a protocol?• protocol (1) (supervisory control, data acquisition, and automatic control) A strict procedure required to
initiate and maintain communication. (SWG/SUB/PE) 999-1992w, C37.1-1994, C37.100-1992• (2) A formal set of conventions governing the format and relative timing of message exchange between
two communications terminals. See also: control procedure. (LM/COM) 168-1956w• (3) (software) A set of conventions that govern the interaction of processes, devices, and other
components within a system. (C) 610.12-1990• (4) (STEbus) The signaling rules used to convey information or commands between boards connected to
the bus. (C/MM) 1000-1987r• (5) (MULTIBUS II) The set of signaling rules used to convey information between agents. (C/MM) 1296-
1987s• (6) A set of semantic and syntactic rules that determine the behavior of entities that interact. (C/PA)
14252-1996• (7) A set of rules and formats (semantic and syntactic) that determines the communication behavior of
simulation applications. (DIS/C) 1278.1-1995, 1278.2-1995• (8) A set of conventions or rules that govern the interactions of processes or applications within a
computer system or network. (ATLAS) 1232-1995• (9) (A) A formal set of conventions governing the format and relative timing of message exchange in a
computer system. (B) A set of semantic and syntactic rules that determine the behavior of functional units in achieving meaningful communication. (C) 610.7-1995, 610.10-1994
• (10) A set of semantic and syntactic rules for exchanging information. (C) 1003.5-1999
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IEEE STD 100
Policy or Protocol• Enables finer resolution sharing through behaviors at
components– Means to specify how spectrum sensing may be used to inform
spectrum use decisions– Means to exploit reuse opportunities that come from knowing
the specific behaviors of incumbents
• Protocols specify access mechanisms while policies specify conditions for use – policy driven systems may choose their own access mechanism
• General enough that physical layer characteristics can also be identified, e.g. polarization, adaptive antennas, …
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Protocol or Policy - 2
• Identifies the behavior of the transmitter– The behavior of the system modeled in transmitter models– The behavior of distant transmitters in receiver models
• Consists of– A name for the policy or protocol– A list a parameters
• Assumes another authority defines the policy or protocol names and the required parameters
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Policy Example
• A policy is generalized behavior with no restriction on the protocols used by the system for arbitrating its own access
• Listen before talk– Sense the channel for a particular power threshold, pth
• A duration of non-use indicates availability, tf
– A sensing period for verifying availability, ts
– An abandonment time, ta
• Policy Description
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, , , ,th f s aLBT p t t t
A protocol example• The scenario
– Multiple co-located MANETs
– Goal is to ensure the networks share the channel
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Each circle is a radio and each color is a network and all share the same channel
The protocolSynchronous Collision Resolution
• Time slotted channels with common time boundaries
• Nodes with packets to send contend in every slot
• Signaling is used to arbitrate contention
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CR Signaling
Transmission Slot
…
A paradigm not a specific design
DEMONSTRATION
Some Results
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All nodes have a fair chance to gain accessNodes outlined in yellow are the contention winners
Example giving precedence to a user• The scenario
– Multiple co-located MANETs with one a primary user
– Goal is to ensure primary users get precedence and secondary users can use whatever spectrum the primary users do not use
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Primary users
Filled circles are contending radios
Differentiating Priority of Access
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...
...1 2 3 4 5 6 7 8 9EI
Dat
a 2
Dat
a 3
Dat
a 1
Priority Phase
Bro
adca
st
EP
SM
DEMONSTRATION
Large circle shows
range of signals
Pink circles remain
contenders
Grey circles lost the
contention
Overlapping circles show coverage of echo signals
Echo signals defeat more contenders
The Result• The primary always get precedence in access• Secondary users can fill in the spaces around the primary user
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Secondary contenders
are well separate from the primary
contender
Filled circles are the surviving contending radios
Specifying the Protocol
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<SCR, 0.07, 0.05, 40>
Name Parameters
Signal Slot Size Signal Duration Transmission Slot Duration
<SCR PS, 0.05, 0.035, 2>
Name Parameters
Other parameters may be required
e.g., timing, signal shape, priority level,
…
Indexing
• Indexing enables the combining of sets of constructs in the same model contingent on particular conditions– Constructs are associated with each other using
an index number– Location indexing combines the location, start
time, end time, power map, and propagation map – Policy and protocol indexing combine underlay
masks with a particular protocol or policy
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A physical layer example• Polarization can support sharing such as Right Circular Polarized
signals can coexist with Left Circular Polarized Signals• Let the two versions of polarization be named <LCP> and <RCP>• An LCP system could convey its compatibility by
– Using <LCP> in the Policy or Protocol Construct in the transmitter model– Providing two underlay mask
• One for random polarization• A more permissive mask for right circular polarization indexed to a Policy or
Protocol construct with the <RCP> named value
• An RCP system would do the same switching <LCP> and <RCP>
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What is the difference between 5.1 and 5.2?• The SCM of 1900.5.2 can specify
– The boundaries of available spectrum– Constraints to spectrum use– Behaviors radios must use to share spectrum
• Devices can receive SCM as policy and can autonomously determine spectrum use that is compliant
• In 1900.5.2 – Boundaries and the conditions for use are the means to change policy
but the rules for determining compliance are unchanging – It is assumed that users or radios know whether they can execute a
named behavior
• 1900.5.1 differentiates itself from 1900.5.2 in that a policy language can teach users or a radio the rules of the policy and how to behave
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MODELING
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Summary of Modeling Transmission Power Spectral Flux Density• Goal is to define what is happening in the
ether• Captured using three constructs
– Total power– Spectrum mask– Power map
• Constructs may trade power levels so long as they get the power spectral flux density correct
• Different sets of models may be assigned to– Different transmitters– Different locations
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Total Power +X
Y
Z
Power Spectral Flux Density of a transmission
+
Transmitter
Receiver Power Spectral Flux Density• Captured using three constructs
– Total power– Underlay mask– Power map
• May divide a model up into different spaces with each having a different set of constructs for power spectral flux density
• Systems having multiple receivers– Model each individually– Model a set of mobile receivers (e.g. data links and
mobile ad hoc networks) by a single model and a space
• Receiver modeling is not well defined
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Total Power +
+
Allowed Power Spectral Flux
Density of interference
Receiver
Combining Constructs into Models
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Transmitter____________________________
Receiver____________________________
System____________________________
Transmitter_1Transmitter_2
Transmitter_n
Receiver_1Receiver_2
Receiver_m
End of System
Collection____________________________System_1System_2
System_i
Transmitter_1Transmitter_2
Transmitter_jReceiver_1Receiver_2
Receiver_k
End of Collection
Modeling constructs are found in transmitter and receiver models and in
system and collection headings
Constructs define emissions
Constructs define
interference
Proposal provides an XML schema for this type of model construction “Spectrum Consumption Modeling Markup Language” (SCMML)
Models and Lists Supported by SCMML
• Transmitter and Receiver Models• System Model
– Constructs in heading define the boundaries of system operation– Lists transmitter and receiver models with more limiting constructs
• Collective Consumption Listing– Constructs in heading define the limits to which the collection is complete– Lists systems, transmitters and receivers of spectrum consumers that consume
spectrum within the limits of the collection• Spectrum Authorization Listing
– Constructs in the heading define the limits of the overall authorization– The lists of system, transmitter, and receiver models identify available spectrum
• Spectrum Constraint Listing– Constructs in the heading define the limits of the collection of constraints– The lists of system, transmitter, and receiver models identify existing uses of
spectrum that have precedence
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General Process for Computing Compatibility
• Determine if uses will overlap in time and spectrum• Determine the constraining points (the point of primary
operation and the point of secondary operation that most restrict the secondary user)
• Compute the allowed transmit power of the secondary
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Primary broadcast user
Secondary mobile userConstraining primary receiver
Constraining secondary transmitter
Determining Compatible Reuse
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394 396 398 400 402 404 406100
50
0
log(d1)
Po
we
r in
dB
sca
le
Bound on the transmitter power
Primary transmitter
Distance to the constraining point
Signal to interference margin, PMunderlay
log(d2)
Constraining point
Attenuation from the transmitter to the constraining point
Attenuation from the secondary transmitter to
the constraining point
Secondary transmitter
Allowed secondary power density at 1 meter in the
constraining point direction
PMr_prop(d1)
PMprop(d2)
PMmasks= 0dB
d1 – distance between the primary transmitter and the constraining pointd2 – distance between the secondary transmitter and the constraining pointPM – Power margin accounting for masks, underlays, and propagation (prop)
Way Ahead• Draft standard has not yet been completed and
so not ready for typical comment and correction process
• Recommend– Interested participants can make suggestions to the
current incomplete draft and provide directly to me– I will update and complete the draft as time allows– Once complete version is made, begin comment
and resolution process
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