NTIA Technical Report TR-07-448

Measurements to Characterize Land

Mobile Channel Occupancy for Federal

Bands 162-174 MHz and 406-420 MHz in

the Washington, D.C., Area

J. Randy Hoffman

Robert J. Matheson

Roger A. Dalke

u.s. DEPARTMENT OF COMMERCE

Carlos M. Gutierrez, Secretary

John M.R. Kneuer, Assistant Secretary

for Communications and Information

July 2007
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CONTENTS

Page

FIGURES viii

TABLES xi

ACRONYMS xiv

DEFINITIONS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. xv

EXECUTIVE SUMMARY xviii

1 INTRODUCTION 1

1.2 Objective 2

2 LMR SIGNAL CHARACTERISTICS AND EMISSION ENVIRONMENT 4

2.1 Channelization 4

2.2 Adjacent Channel Power Ratio 6

2.3 Emission Environment. 7

3 FIELD MEASUREMENTS DESCRIPTION 8

3.1 Measurement Requirements 8

3.2 Site Selection 9

3.3 System Hardware Components 14

3.4 Measurement Procedures 15

3.5 Real-time Signal Processing 19

3.6 Calibrations 21

4 POST-MEASUREMENT PROCESSING 22

4.1 Broadband Impulsive Noise 22

4.2 Noise Sidebands 25

4.3 Detection Thresholds 26

5 ANALYSIS AND RESULTS 30

5.1 Frequency Groupings 30

5.2 Channelization 30

5.3 Time Scenarios 30

5.4 High Occupancy Channels 31

5.5 Busiest Hour Statistics 31

5.6 General Description ofAnalysis 34

5.7 Summary of Processing 47

5.8 Measurement Results 50

v
5.8.1 Results for 162-174 MHz Band 55

5.8.2 Results for 406-420 MHz Band 66

6 SUMMARY OF MEASUREMENT RESULTS 77

6.1 Overall Results 79

6.1.1 Results for 162-174 MHz band 79

6.1.2 Results for 406-420 MHz band 79

6.2 Diurnal Patterns for Both Bands. . 80

7 ACKNOWLEDGMENTS 81

8 REFERENCES 81

APPENDIX A: SUPPLEMENTAL MEASUREMENT RESULTS A-I

A.1 Usage for Each One-hour Block During the Course ofthe Measurements A-I

A.2 Percent Band Usage for the 162-174 MHz Band. . . . . . . . . . . . . . . . . . . . . . . . .. A-3

A.3 Percent Band Usage for the 406-420 MHz Band A-6

APPENDIX B: CONFIDENCE INTERVALS FOR OCCUPANCY MEASUREMENTS B-1

B.1 Introduction B-1

B.2 Statistical Character ofChannel Occupancy Measurements B-1

B.2.1 Characterization ofthe Process. . B-1

B.2.2 Confidence Intervals B-2

B.2.3 Example B-3

B.3 Average Occupancy for a Band ofChannels B-4

B.4 References B-4

VI
FIGURES

Page

Figure 1. RSMS mobile lab at the St. Elizabeth's Hospital site 10

Figure 2. Aerial view ofWashington, D.C., area showing location ofmeasurement

system 11

Figure 3. Coverage plots for the 162-174 MHz band using the minimum receiver

threshold 12

Figure 4. Coverage plots for the 406-420 MHz band using the minimum receiver

threshold 13

Figure 5. Block diagram ofmeasurement system 14

Figure 6. FFT ofCW signal using LMR measurement parameters.. . 16

Figure 7. Multiple FFT traces ofa carrier signal FM modulated with 3-kHz band-limited

Gaussian noise and a 3-kHz maximum frequency deviation 17

Figure 8. Multiple FFT traces of a carrier signal FM modulated with 3-kHz band-limited

Gaussian noise and a 6-kHz maximum frequency deviation 17

Figure 9. Flow diagram of channel power measurements 19

Figure 10. "Data display" as viewed on the computer (power referenced to spectrum

analyzer input) 21

Figure 11. One-second sample without impulsive noise 24

Figure 12. One-second sample with impulsive noise 24

Figure 13. Removal ofLO noise sidebands 26

Figure 14. APD ofsystem noise 28

Figure 15. Thresholds and median ofmultiple median-of-5 data acquisitions 29

Figure 16. Diagram offictitious data showing the difference between "busiest hour ofthe

week" and "busiest usage by hour." 34

Vll
Figure 17. Sample graph (reference to Figure A-2) ofHourly Band Usage (percent oftime

and total Erlangs) 36

Figure 18. Sample graph (reference to Figure 42) ofBand Occupancy by Time-of-Day

(percent oftime and total Erlangs) 36

Figure 19. Sample graph (reference to Figure 27) ofthe Busiest Hour ofthe Weekfor Each

Channel , " 38

Figure 20. Sample APD (reference to Figure 47) of Channel Power Values for all channels

in a given band 39

Figure 21. Sample graph (reference to Figure 32) ofthe percent ofHourly Channel Percent

Occupancy values exceeding a given percent usage 40

Figure 22. Sample graph (reference to Figure 33) ofthe percent channels exceeding a given

percent usage for Channel Percent Occupancy 41

Figure 23. Sample graph (reference to Figure 34) for percent of channels exceeding a given

percent usage for the Busiest Usage by Time-of-Day during weekdays only.. . ... 42

Figure 24. Sample (reference to Figure 37) cumulative distribution graphs ofthe percent of

channels that exceed a given percent ofhours at greater than or equal to a given

usage (Hourly Channel Percent Occupancy) 44

Figure 25. Calculating mean hourly channel usage 46

Figure 26. Hourly Band Usage (percent oftime and total Erlangs) during the course ofthe

measurements for the 162-174 MHz band (excluding HOCs; minimum

thresholds) 55

Figure 27. Busiest Hour ofthe Weekfor Each Channel in the 162-174 MHz band 55

Figure 28. Hourly Band Usage (percent oftime and total Erlangs) during the course ofthe

measurements for the 162-174 MHz band (including HOCs; minimum

threshold) 56

Figure 29. Band Occupancy by Time-of-Day (percent oftime and total Erlangs) during

different 24-hour time scenarios in the 162-174 MHz band (excluding HOCs;

minimum threshold) 57

Vlll
Figure 30. Band Occupancy by Time~of-Day (percent oftime and total Erlangs) during the

course of24 hours, independent ofthe date, for different channelization scenarios

in the 162-174 MHz bartd{eXCluding HOCs; minimum threshold) 58

Figure 31. Band Occupancy by Time-of-Day (percent oftime and total Erlangs) using

different thresholds, independent ofthe date, for all 934 channels in the 162-174

MHz band (excluding HOCs) 59

Figure 32. Percent ofHourly Channel Percent Occupancy values exceeding a given percent

usage over the course ofthe measurements for the 162-174 MHz band (minimum

threshold) 60

Figure 33. Percent of channels exceeding a given percent usage for Channel Percent

Occupancy over the course ofthe measurements for the 162-174 MHz band

(minimum threshold) 61

Figure 34. Percent of channels exceeding a given percent usage for the Busiest Usage by

Time-of-Day for Each Channel during weekdays only in the 162-174 MHz band

(minimum threshold). . 62

Figure 35. APDs of Channel Power Values for channels in the 162-174 MHz band - entire

week, independent of date or time for different channelization (excluding HOCs;

minimum threshold) 63

Figure 36. APDs ofChannel Power Values for all channels spaced 12.5 kHz apart in the

162-174 MHz band for the busiest hour during the entire week independently for

each frequency for different HOC scenarios (minimum threshold) 64

Figure 37. Cumulative distribution ofthe percent of channels that exceed a given percent of

hours at greater than or equal to a given Hourly Channel Percent Occupancy

(designated by legend) for all channels in the 162-174 MHz band (excluding

HOCs; minimum threshold, entire week) 65

Figure 38. Hourly Band Usage (percent oftime and total Erlangs) during the course ofthe

measurements for the 406-420 MHz band (excluding HOCs; minimum

threshold) 66

Figure 39. Busiest Hour ofthe Weekfor Each Channel in the 406-420 MHz band 66

Figure 40. Hourly Band Usage (percent oftime and total Erlangs) during the course ofthe

measurements for the 406-420 MHz band (including HOCs; minimum

threshold) 67

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Figure 41. Band Occupancy by Time-o.fDay during different 24-hour time scenarios in the

406-420 MHz band (excluding HOCs; minimum threshold) 68

Figure 42. Band Occupancy by Time-o.fDay (percent oftime and total Erlangs) during the

course of24 hours, independent ofthe date, for different channelization scenarios

in the 406-420 MHz band (excluding HOCs; minimum threshold) 69

Figure 43. Band Occupancy by Time-o.fDay (percent oftime and total Erlangs) using

different thresholds, independent ofthe date, for all 1113 channels in the

406-460 MHz band (excluding HOCs) 70

Figure 44. Percent ofHourly Channel Percent Occupancy values exceeding a given percent

usage over the course ofthe measurements for the 406-420 MHz band (minimum

threshold) 71

Figure 45. Percent of channels exceeding a given percent usage for Channel Percent

Occupancy over the course ofthe measurements for the 406-420 MHz band

(minimum threshold) 72

Figure 46. Percent of channels exceeding a given percent usage for the Busiest Usage by

Time-o.fDay for Each Channel during weekdays only in the 406-420 MHz band

(minimum threshold) 73

Figure 47. APDs of Channel Power Values for channels in the 406-420 MHz band - entire

week, independent of date or time for different channelization (excluding HOCs;

minimum threshold) 74

Figure 48. APDs of Channel Power Values for all channels spaced 12.5 kHz apart in the

406-420 MHz band for the busiest hour during the entire week independently for

each frequency for different HOC scenarios (minimum threshold) 75

Figure 49. Cumulative distribution ofthe percent of channels that exceed a given percent of

hours at greater than or equal to a given Hourly Channel Percent Occupancy

(designated by legend) for all channels in the 406-420 MHz band (excluding

HOCs; minimum threshold) 76

Figure A-I. Hourly Band Usage (percent oftime and total Erlangs) during the course ofthe

measurements for all 934 channels in the 162-174 MHz band (excluding

HOCs) A-I

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Figure A-2. Hourly Band Usage (pen::entoftime and total Erlangs) during the course ofthe

measurements for all 11 13 channels in the 406-420 MHz band (excluding

HOCs) A-2

TABLES

Page

Table 1. Center Frequencies for LMR Measurements. . 5

Table 2. Old 25-kHz Channel Assignments in the 162-174 MHz Band 5

Table 3. New 12.5-kHz Channel Assignments in the 162-174 MHz Band 6

Table 4. Minimum ACPR Requirements for Analog and Digital Federal LMR Systems.... 7

Table 5. Measurement Requirements 8

Table 6. Total Number of Statistically Analyzed Channels Spaced 12.5 kHz Apart 35

Table 7. Sample Table Showing Mean Percent Usage and Mean Erlangs for 934 Channels

(Reference to Table A-I) 45

Table 8. Summary ofvalues used in the rectangular approximations ofmean percent

usage 46

Table 9. Figure Numbers for Graphs in the 162-174 MHz Band 51

Table 10. Figure Numbers for Graphs in the 406-420 MHz Band 52

Table 11. Minimum Detection Threshold Values 53

Table A-I. Percent Band Usage and Average ofBusiest Usage by Hour During the Entire

Week for All 934 Channels in the 162-174 MHz Band (Excluding HOCs).... A-3

Table A-2. Percent Band Usage and Average ofBusiest Usage by Hour During Weekdays

Only for All 934 Channels in the 162-174 MHz Band (Excluding HOCs)..... A-4

Table A-3. Percent Band Usage During Weekend Days for All 934 Channels in the

162-174 MHz Band (Excluding HOCs) A-5

Table A-4. Percent Band Usage During Election Day for All 934 Channels in the

162-174 MHz Band (Excluding HOCs) A-5

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Table A-5. Percent Band Usage and Average ofBusiest Usage by Hour During the Entire

Week for All 1113 Channels in the 406-420 MHz Band (Excluding HOCs)... A-6

Table A-6. Percent Band Usage and Average ofBusiest Usage by Hour During Weekdays

for All 1113 Channels in the 406-420 MHz Band (Excluding HOCs). . . . . . .. A-7

Table A-7. Percent Band Usage During Weekend Days for All 1113 Channels in the

406-420 MHz Band (Excluding HOCs) A-8

Table A-8. Percent Band Usage During Election Day for All 1113 Channels in the

406-420 MHz Band (Excluding HOCs) , A-8

XlI
ADC

ACPR

APD

CW

dB

dBc

FFT

FM

HOC

IM

ITS

kHz

LMR

LO

MHz

NOAA

NTIA

OSM

PSWAC

RF

ACRONYMS

analog-to-digital converter.

adjacent channel power ratio.

amplitude probability distribution.

continuous wave.

decibel.

dB relative to carrier power.

fast Fourier transform.

frequency modulation.

high occupancy channel.

intermodulation.

Institute for Telecommunication Sciences.

kilohertz.

Land Mobile Radio.

local oscillator.

megahertz.

National Oceanic and Atmospheric Administration.

National Telecommunications and Information Administration.

Office of Spectrum Management.

Public Safety Wireless Advisory Committee.

Radio Frequency.

XUl
RSMS

RSMS-4

Radio Spectrum Measurement Science.

Radio Spectrum Measurement Science 4th generation measurement system.

DEFINITIONS

Adjacent Channel Power Ratio: The ratio in decibels (dB) between the total transmitter power

that lies within its authorized channel bandwidth and the part ofthe output power that falls

within the bandwidth centered around the frequency assignment ofthe adjacent channel

(expressed in units of dBc).

Amplitude Probability Distribution: A cumulative probability distribution plot representing

the probability of exceeding a given level of power, where the y-axis displays power and the xaxis displays the probability expressed on a Rayleigh scale. A detailed description ofAPDs is

given in a tutorial located in Appendix A of [I].

Area Assignments: Frequency assignments in the Government Master File that do not have

specific coordinates and authorize base and/or mobile stations to operate anywhere within a

defined geographic area (e.g., United States and Possessions).

Average ofBusiest Usage by Hour: Determined by computing the average ofthe Busiest Usage

by Time-of-Day for Each Channel values across all channels in the band, resulting in a single

value for the entire band. The Average ofBusiest Usage by Hour values are displayed in Tables

A-I, A-2, A-5, and A-6.

Band Occupancy by Time-of-Day: Determined by taking the Hourly Band Usage values for

each hour ofthe day, and computing the average for the corresponding hours ofthe measurement

period. Band Occupancy by Time-of-Day values are displayed in Figures 29 through 31 and 41

through 43.

Busiest Usage by Time-of-Day for Each Channel: Determined for each channel by identifying

the Usage by Time-of-Day value that is the largest out ofthe 24 values. There is only one Busiest

Usage by Time-of-Day value for each channel. The Busiest Usage by Time-of-Day for Each

Channel values are summarized in Figures 34 and 46.

Busiest Hour of the Week for Each Channel: Determined for each channel by identifying the

time and date at which the highest Hourly Channel Percent Occupancy value occurs. During the

week, channels will typically have a different date and time when the usage is busiest. Busiest

Hour ofthe Weekfor Each Channel values are displayed in Figures 27 and 39.

Channel Percent Occupancy: Computed for each channel by determining the percent of

Channel Power Values that exceed a detection threshold for each I-second acquisition every day

XIV
ofthe measurement period. For example, if2,280 out ofthe 76,000 total Channel Power Values

for a specific channel are above the detection threshold, then the channel occupancy is 3 percent

at that detection level, for the specifiedchannel. Channel Percent Occupancy values are

summarized in Figures 33 and 45. :?X .

Channel Power Readings: The amount ofreceived power on an individual channel measured

using an Agilent E4440A Spectrum Analyzer in a resolution bandwidth of 5.5 kHz. Five ofthese

basic measurements are used to compute a Channel Power Value, which is the building block for

all further analysis and computations.

Channel Power Value: Determined by computing the median offive consecutive individual

Channel Power Readings measured within a I-second measurement period. The median value of

the 5 independent measurements made for each channel is selected as the single value of

measured power for that channel during that I-second measurement period. All further

processing ofmeasured data is based on this median-of-five measurement technique. For

example, ifthe five individual Channel Power Readings are -77, -70, -75, -69, and -73 dBm, the

median value is -73 dBm. This value is computed for each channel at I-second intervals, in the

4-minute measurement period for each 5-MHz frequency block. Channel Power Values are

summarized in Figures 35, 36, 47, and 48.

Channel Power Values in an Hour: A set ofindividual Channel Power Values measured over a

I-hour period. This is represented by a set of data that typically contains either 240 (162-174

MHz band) or 480 (406-420 MHz band) median-of-5 Channel Power Values for that hour of

that day for a specific channel.

Erlangs: A traffic equivalent to full time occupancy of a channel for an hour - for instance, one

channel used continuously for 60 minutes, or two channels with a combined occupancy of 60

minutes. In this report, the number ofErlangs is determined by multiplying the percent usage by

the total number of channels in the band.

High Occupancy Channel: A channel that exceeds the detection threshold for a large percent of

the time (defined in this paper as > 80% oftime).

Hourly Band Usage: Determined by averaging all ofthe Hourly Channel Percent Occupancy

values in a given hour of a given day for all ofthe channels in the band. The Hourly Band Usage

is displayed in Figures 26, 28, 38, 40, A-I, and A-2.

Hourly Channel Percent Occupancy: Computed for each channel by determining the number

of Channel Power Values in an Hour for a given channel that exceed a detection threshold. For

example, if 14 out of480 total Channel Power Values in an Hour are above the detection

threshold, then the channel occupancy is 3 percent at that detection level, for the specified hour

and channel. Hourly Channel Percent Occupancy values are summarized in Figures 32, 37,44,

and 49.

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Maximum Band Occupancy: The maximum of all Band Occupancy by Time-of-Day values.

This can be identified in Figures 30 and 42.

Occupancy: Channels are considered to be occupied (i.e., in use) whenever the channel contains

Radio Frequency (RF) power above a certain received detection threshold level. By some

definitions a channel may be considered "in use" even if no traffic is being carried during the

time ofmeasurement. For instance, a channel being used by a Secret Service agent protecting the

President may not carry traffic (not occupied) unless there is an emergency. However, the

channel is "in use" in the sense that personnel are monitoring the channel and ready to take

action should a situation require it. In this report, "usage" is used interchangeably with the term

"occupancy," which means "carrying traffic" - not simply being monitored.

Percent Band Usage: Determined by computing the mean of all Hourly Channel Percent

Occupancy values for all channels during the measurement period. The measurement periods

examined include all days, weekdays only, weekend days, and Election Day. Percent Band

Usage values are shown in Tables A-I through A-8.

Specific Location Assignments: Frequency assignments in the Government Master File that

have specific coordinates (latitude and longitude) for the location ofthe base station and a radius

of operation for the associated mobile and portable stations.

Trunking: The method used in some modem communications systems in which frequency

channels are assigned dynamically as communication is required, usually when there are more

users than available frequency channels. This allows time sharing ofthe same frequencies by

multiple users, thus improving channel usage efficiency. Typically, a control channel is used to

make initial contact, after which a frequency channel is assigned and automatically tuned to by

the user's radio device during the course ofthe connection. This technique is utilized in most

modem cellular phone services since there are far more users than available frequencies.

Usage by Time-of-Day for Each Channel: Determined for each channel by computing the

average of the Hourly Channel Percent Occupancy values for each specific hour of the day

for the corresponding measurement period (e.g., all days, weekdays, weekend days, and

Election Day). For example, channel I will have 24 different Usage by Time-of-Day for

Each Channel values, each for a different hour of the day. These 24 values represent the

mean usage for that 'specific time of day over the course of the several days of the

measurements.

Usage: Refer to the definition for "Occupancy".

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EXECUTIVE SUMMARY

In May 2003, President Bush established the Spectrum Policy Initiative to promote the

development and implementation ofia'lJIiited States spectrum policy for the 21 st century. In

response to the Spectrum Policy Initiative, the Secretary of Commerce established a Federal

Government Spectrum Task Force and initiated a series of public meetings to address

policies affecting spectrum use by the Federal, state, and local governments, and the private

sector. The recommendations resulting from these activities were included in two reports

released by the Secretary of Commerce in June 2004. Based on the recommendations

contained in these reports, the President directed the Federal Agencies on November 30,

2004, to plan the implementation of the 24 recommendations contained in the reports. One

of the recommendations directed the National Telecommunications and Information

Administration (NTIA) to develop analytic approaches, software tools, and engineering

techniques for evaluating and improving the efficiency and effectiveness of Federal spectrum

use.

To satisfy one of the goals of that recommendation, NTIA's Institute for Telecommunication

Sciences (ITS) undertook a series of channel occupancy measurements in the Washington,

D.C., area from October 26 to November 3, 2004 in the Land Mobile Radio (LMR) bands

162-174 and 406--420 MHz. The purpose of these measurements was twofold: first, to

develop channel occupancy measurement techniques for LMR bands and secondly, to gather

actual data on the usage of these bands in the Washington, D.C., area. The measurement

techniques can be used at other metropolitan locations when the need arises to measure the

LMR channel usage. The data gathered for this area and these bands will be used for further

analyses of other aspects of the Presidential Spectrum Policy Initiative.

The measurements were conducted on the grounds of the partially abandoned Saint

Elizabeth's Hospital, centrally located in the Washington, D.C., area, using the fourth

generation of the Radio Spectrum Measurement Science (RSMS) system. The measurements

were conducted 24 hours per day over the course of 8 consecutive days which included the

Presidential Election Day. The measured data were post processed at the ITS Laboratory in

Boulder, Colorado.

The measurement system was designed to have a coverage area of approximately 100-km

radius for base stations, 50-km radius for mobile units, and 25-km radius for portable units.

The measurement results are reported in terms of channel usage for designated LMR

channels, irrespective of whether the individual channels have been assigned or not. The

data, which was based on sampling the received power on individual LMR channels over an

eight-day period of time and comparing those values to specific detection thresholds, was

used to identify whether or not the LMR channels are being used at that location and to

what extent.

XVll
Four types of data are presented in this report: 1) mean channel usage statistics, 2) mean

busiest-hour usage statistics, 3) power level statistics, and 4) statistics on percent of channels

(and hourly channel usage) exceeding a given percent usage.

The measured data contains information on channel usage for two types of frequency

assignments: Specific Location Assignments and Area Assignments. Specific Location

Assignments have specific coordinates (latitude and longitude) for the location of the base

station and a radius of operation for associated mobile and portable stations. Area

Assignments do not have specific coordinates and authorize base and/or mobile stations to

operate anywhere within a specific geographic area (e.g., United States and Possessions).

These two types of frequency assignments were not distinguished during analyses; therefore

the usage statistics are based on both types of assignments.

For the 162-174 MHz band, the mean percent time that all of the channels in the band are

being used for each hour (referred to in this report as Band Occupancy by Time ofDay)

varied between 0.5 and 1.6 percent, with the busiest hours being between 7 am and 5 pm.

For the 406-420 MHz band, the value was 1.2 to 3.6 percent with the busiest hours being

between 5 am and 8 pm.

The Band Occupancy by Time ofDay for conventional LMR systems can be compared to

allowable call-blockage (typically defined as Grade of Service) as recommended in the Final

Report of the Public Safety Wireless Advisory Committee (PSWAC). In that report, the

PSWAC recommends that call-blockage not exceed "one call for service per one hundred

attempts during the average busy hour." That translates to no more than 1 percent usage for

multi-user conventional systems where channels are assigned statically. Since the existing

systems measured in the 162-174 MHz band are conventional systems, the measured channel

usage during the busiest hour of 1.6 percent is consistent with the recommendations made by

the PSWAC.

Each of the two measured bands show approximately the same diurnal pattern of usage,

irrespective of the measurement period (e.g., all days, weekdays, weekends, or Election Day),

with slight variations between them. In the 162-174 MHz band, the highest usage occurs

during the weekdays, exceeding the other time scenarios by about 1 percent. In the

406-420 MHz band, the usage was about the same for all of the time scenarios, except for

about a 1 percent less usage on the weekend mornings, and about a 1 percent greater usage

on the afternoon of the Presidential Election Day.

It should be noted that most of the channels in these bands are statically assigned to

networks or individual users, in contrast to dynamically assigned as is the case with trunked

systems, where there is time sharing of each frequency channel by multiple users. Some of

these assigned channels are reserved for high priority usage in which communication must be

available at all times for a limited number of users, thus resulting in low percent usage. In

XV11l
addition, none of these measurements were made during a major emergency that might have

greatly increased the use of radio channels.

The data can be used for specifying'i'tlie'6vetall performance objectives of a hypothetical

communications system using a different technology (e.g., trunking). By designing the

hypothetical system to provide the same overall communications capability as the existing

LMR systems, the existing and hypothetical systems could then be compared to examine

relative total spectrum usage (number of channels required for each system).

The intent of the measurements was not to examine details of performance and use for the

characterization of individual channels. This individual channel information, as well as more

extensive measurements, may be required for a detailed engineering design for a next

generation system.

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Measurements to Characterize Land Mobile Channel Occupancy for Federal

Bands 162-174 MHz and 406-420 MHz in the Washington, D.C., Area

J. Randy Hoffman, Robert J. Matheson, and Roger A. Dalke!

This report describes field measurements to characterize Land Mobile Radio

(LMR) channel occupancy of Federal bands 162-174 MHz and 406-420 MHz at

a single central1ocation in the Washington, D.C., area. This is part of the

National Telecommunications and Infonnation Administration effort to evaluate

the spectrum efficiency in the Federal frequency bands. Measurements of the

received signal levels in LMR frequency bands 162-174 MHz and 406-420 MHz

were perfonned over an eight day period for the purpose of detennining channel

usage within the measurement system's coverage area of approximately 100-km

radius for base stations, 50-km radius for mobile units, and 25-km radius for

portable units. The measurements were made using new equipment and

techniques that digitize as much as a 5-MHz segment of spectrum and process it

to obtain simultaneous signal levels of up to 400 individual LMR channels.

These techniques provided faster measurements, but also allowed enhanced postprocessing of the data to remove effects of impulsive noise.

Key words: channel occupancy; channel usage; Federal radio usage; Land Mobile Radio

(LMR); measurements; spectrum efficiency

1 INTRODUCTION

In May 2003, President Bush established the Spectrum Policy Initiative to promote the

development and implementation of a United States spectrum policy for the 21 st century. In

response to the Spectrum Policy Initiative, the Secretary of Commerce established a Federal

Government Spectrum Task Force and initiated a series of public meetings to address

policies affecting spectrum use by the Federal, state, and local governments, and the private

sector. The recommendations resulting from these activities were included in two reports

released by the Secretary of Commerce in June 2004. Based on the recommendations

contained in these reports, the President directed the Federal Agencies on November 30,

2004, to plan the implementation of the 24 recommendations contained in the reports. One

of the recommendations directed the National Telecommunications and Infonnation

Administration (NTIA) to develop analytic approaches, software tools, and engineering

techniques for evaluating and improving the efficiency and effectiveness of Federal spectrum

use.

!The authors are with the Institute for Telecommunication Sciences, National Telecommunications and

Information Administration, U.S. Department of Commerce, Boulder, CO 80305.
As discussed in the Spectrum Policy Initiative reports, the radio frequency spectrum is a

critical resource that is used by the Federal Government to perform congressionally mandated

missions. Efficient use of the spectrum is one of the cornerstones for obtaining maximum

usage of the available spectrum. NTIA and the other Federal Agencies realize that the

primary way to satisfy the growing demands for spectrum in the Land Mobile Radio (LMR)

frequency bands is to employ more spectrum efficient technologies.

As part of the effort to meet these objectives, NTIA performed a study that created a

database of frequency assignments from the Government Master File (GMF) in the 162-174

MHz band within a 100-mile radius of Washington, D.C. The Washington, D.C.,

metropolitan area was selected because it is believed to be representative of a spectrally

congested environment. Licensed data from Federal Agency radio systems and agency

interviews were used to understand the services provided by Federal radio systems in this

frequency band, including the coverage areas and other aspects of each radio system. This

information was used to produce "signal capacity" maps that showed the cumulative

coverage areas of all Federal radios in this band, including the number of simultaneous

messages that could be carried at various locations within 100 miles of Washington,

D.C. Results of this work were compiled in a report titled "Federal Land Mobile Operations

in the 162-174 MHz Band in the Washington, D.C., Area" [2].

NTIA's Institute for Telecommunication Sciences (ITS) then undertook a series of channel

occupancy and usage measurements in Washington, D.C., in the LMR bands of 162-174 and

406-420 MHz, the results of which are described in this report. The results of these channel

occupancy measurements can further be used to specify the overall performance objectives of

LMR systems employing different technologies (e.g., trunking).

1.2 Objective

There were two objectives for this project. The first objective was to monitor each

assignable 12.5- and 25-kHz channel in the 162-174 MHz and 406-420 MHz bands in the

Washington, D.C., area to determine the amount of time those channels contained power

above specific thresholds, and to present statistical analysis of channel occupancy based on

number of occurrences exceeding the threshold. The second objective was to develop channel

occupancy and usage measurement techniques for LMR bands using the latest in technology.

1.3 Approach

Using the Radio Spectrum Measurement Science 4th generation measurement system (RSMS4), the measurements were performed during the course of eight consecutive days, including

the Presidential Election Day (October 26 to November 3, 2004). The measurement system

was designed for a receiver coverage of approximately 100-km radius for base stations and

2
repeaters, 50-km radius for mobile units, and 25-km radius for portable units.2 Data were

acquired continuously, 24 hours per day, over the course of the eight-day period and then

analyzed for Federal bands 162-174 MHz and 406-420 MHz to furnish channel loading

statistics.

The measurements were made using new equipment and techniques that digitize as much as

a 5-MHz segment of spectrum and process it to obtain simultaneous signal levels of up to

400 individual LMR channels. These techniques provided faster measurements, but also

allowed enhanced post-processing of the data to remove effects of impulsive noise.

In this report, channels are considered to be occupied (i.e., in use) whenever the channel

contains Radio Frequency (RF) power above a certain received threshold level. The

measurements were made and recorded so that variable threshold levels could be used for

purposes of analyzing the effects of external noise and other factors. This definition of

occupancy is generally consistent with other definitions of usage, although the choice of

received power detection threshold levels is not necessarily uniform among researchers. By

some definitions a channel may be considered "in use" even if no traffic is being carried

during the time of measurement. For instance, a channel being used by a Secret Service

agent protecting the President may not carry traffic (not occupied) unless there is an

emergency. However, the channel is "in use" in the sense that personnel are monitoring the

channel and ready to take action should a situation require it. In this report, "usage" is used

interchangeably with the term "occupancy," which means carrying traffic - not simply being

monitored.

2 Typical reuse distances for base stations and repeaters is approximately 100 km.

3
2 LMR SIGNAL CHARACTERISTICS AND EMISSION ENVIRONMENT

This section provides an overview of the LMR signal characteristics and the other emissions

in the RF environment that were a factor in determining the parameters of the system for

measuring the 162-174 MHz and 406-420 MHz frequency bands. The two LMR signal

characteristics that determine measurement parameters are: channelization (how the

frequencies are assigned in each band), and adjacent channel power ratio (how much a signal

must be attenuated at the adjacent channel). The former determines preselector filter

characteristics, center frequency assignments, the degree of decimation of digitized data, and

the manner in which frequencies are grouped for acquisition. The latter determines the

windowing requirements and data acquisition length (which ultimately determine the

resolution of individual LMR signals that can be measured). The other environmental

emission factors that must be considered in determining the measurement system parameters,

include the range of in-band signal levels, out-of-band signal levels, and the nature of RF

nOIse.

2.1 Channelization

Table 1 summarizes the center frequencies of possible channel assignment in the

162-174 MHz and 406-420 MHz bands. While frequencies in these bands were originally

assigned using a 25-kHz channel spacing scheme (referred to in this report as "the old

25-kHz channels"), frequencies assigned in these bands are now required to use a l2.5-kHz

channel spacing (referred to in this report as "the new 12.5-kHz channels"). To do so

requires that the emission bandwidth of any existing LMR systems be reduced to half the

original bandwidth so that the new l2.5-kHz channels can be inserted between the original

channels, spaced 25 kHz apart. In the 406-420 MHz band, the center frequencies of the old

25-kHz channels are assigned according to the following equation:

(406.125 MHz) + (Nx .025), where N= 0 to 554.

The new 12.5-kHz channelization scheme adds channels midway between the old 25-kHz

channels so that these channels occur at:

(406.1125 MHz) + (N x .025), where N = 0 to 555.

In the 162-174 MHz band, the center frequencies of the old 25-kHz channels and the new

12.5-kHz channels are assigned according to the equations given in Table 2 and Table 3

respectively [3].

4
Table 1. Center Ffequencies for LMR Measurements

Frequency } ... Measurement Center Frequencies

162-174 MHz Multiples of 12.5 kHz starting at 162.0125 MHz

406-420 MHz Multiples of 12.5 kHz starting at 406.1125 MHz

Table 2. Old 25-kHz Channel Assignments in the 162-174 MHz Band

162.025 MHz + N x 0.025, where N = 0-22

162.6125 MHz + N x 0.025, where N = 0-7

162.825 MHz + N x 0.025, where N = 0-22

163.4125 MHz + N x 0.025, where N = 0-7

163.625 MHz + N x 0.025, where N = 0-6

163.8125 MHz + N x 0.025, where N = 0-7

164.05 MHz + N x 0.025, where N = 0-31

164.8625 MHz + N x 0.025, where N = 0-37

165.825 MHz + N x 0.025, where N = 0-23

166.4375 MHz + N x 0.025, where N = 0-8

166.675 MHz + N x 0.025, where N = 0-20

167.2125 MHz + N x 0.025, where N = 0-23

167.825 MHz + N x 0.025, where N = 0-135

171.2375 MHz + N x 0.025, where N = 0-6

171.425 MHz + N x 0.025, where N = 0-70

173.4125 MHz + N x 0.025, where N = 0-23

5
Table 3. New 12.5-kHz Channel Assignments in the 162-174 MHz Band

162.0125 MHz + N x 0.025, where N = 0-23

162.6 MHz + N x 0.025, where N = 0-7

162.8375 MHz + N x 0.025, where N = 0-22

163.425 MHz + N x 0.025, where N = 0-7

163.6125 MHz + N x 0.025, where N = 0-7

163.825 MHz + N x 0.025, where N = 0-6

164.0375 MHz + N x 0.025, where N = 0-32

164.85 MHz + N x 0.025, where N = 0-37

165.8375 MHz + N x 0.025, where N = 0-23

166.45 MHz + N x 0.025, where N = 0-7

166.6625 MHz + N x 0.025, where N = 0-21

167.225 MHz + N x 0.025, where N = 0-22

167.8375 MHz + N x 0.025, where N = 0-135

171.25 MHz + N x 0.025, where N = 0-5

171.4125 MHz + N x 0.025, where N = 0-71

173.425 MHz + N x 0.025, where N = 0-22

2.2 Adjacent Channel Power Ratio

Adjacent channel power ratio (ACPR) is the ratio in decibels (dB) between the total

transmitter power that lies within its authorized channel bandwidth and the part of the output

power that falls within the bandwidth centered around the frequency assignment of the

adjacent channel (expressed in units of dBc). Chapter 5 of the NTIA Manual of Regulations

and Procedures for Federal Radio Frequency Management specify the ACPR standards for

Federal LMR systems in the 162-174 MHz and 406--420 MHz bands [4]. The ACPR

standards are specified for analog and digital wideband (25 kHz channels) and narrowband

(12.5 kHz channels) operations as shown in Table 4. The NTIA ACPR standards are

consistent with those specified by the Telecommunications Industry Association for analog

[5] and digital [6] LMR systems.

6
Table 4. Minimum ACPR Requirements for Analog and Digital Federal LMR Systems

Channel Spacing

Frequency Range Wideband Operation Narrowband Operation

162-174 MHz 50dBc 70dBc

406-420 MHz 70dBc 70 dBc

2.3 Emission Environment

Factors associated with the RF emission environment must also be taken into consideration

in determining the parameters for the measurement system. These factors include range of inband signal levels, out-of-band signal characteristics, and the nature of RF noise. Because

LMR systems by their very nature are mobile, the signal power received at the measurement

system can be time varying and span a range as great as 100 dB in received power - the

weakest signals coming from distant transmissions and the stronger signals coming from

nearby base stations and local mobile and hand-held units that approach the measurement

system. Not only can a single frequency assignment vary greatly in power from time to time,

but power can vary greatly between adjacent frequencies. Because of this broad range of

received signal powers, depending upon the degree of sensitivity of the measurement system,

the system must have a wide instantaneous dynamic range (i.e., be able to resolve the

individual signals without varying the sensitivity of the measurement system across the band

of acquisition).

To prevent overload of the measurement system front-end amplifiers, out-of-band emissions

must be attenuated through proper filtering. The most significant out-of-band emissions that

affect the measurement system requirements are those due to TV station channel 7; this

channel occupies the spectrum between 174 and 180 MHz. This is a very strong signal, and

not only can it saturate the front-end amplifiers of a sensitive system, but it also has strong

enough adjacent channel emissions within the 162-174 MHz LMR band to be detected

significantly above the noise floor of the measurement system (10 dB or more depending

upon the measurement system noise figure).

The other factor in the emission environment that has to be addressed is RF noise.

Preliminary investigation shows that in the spectrum region of interest, the mean of the

Gaussian RF background noise power usually lies well enough below the measurement

system noise power so as not to be detected. However, impulsive noise can occur well above

the measurement system noise, and therefore techniques have to be employed to differentiate

this emission source from the LMR signals.

7
3 FIELD MEASUREMENTS DESCRIPTION

This section describes the measurement method and requirements, system configurations, and

calibrations.

3.1 Measurement Requirements

The major objective in making these LMR measurements was to determine, for various

detection thresholds, the proportion of time that a given channel (or group of channels) is

carrying traffic. To meet these objectives, several requirements, as described in Table 5, were

imposed with regard to sensitivity, antenna characteristics, dynamic range, frequency

resolution, out-of-band rejection, noise suppression, speed of acquisition, and location.

Table 5. Measurement Requirements

I Parameters I Requirement I

Threshold Minimum threshold for signal detection set as low as

possible, which for this measurement system is 8 dB above

median system noise. This translates to a field strength of

approximately 8 dB IlV1m. (The noise figure referenced to the

output of the antenna terminals for the 162-174 MHz and

406-420 MHz systems is 13.9 dB and 11.9 respectively.)

Instantaneous Dynamic 84 dB between point of measurement system front-end

Range compression and arithmetic mean system noise power.

Channel Resolution 12.5 kHz, 70 dB below the channel center frequency.

Out-of-band Rejection Preselection filtering to reduce total passband power so that

sensitivity and dynamic range requirements can be

maintained.

Noise Suppression Process data to achieve a probability of no greater than

0.01% that an instantaneous system noise level will exceed

the median system noise by more than 8 dB.

Speed of Acquisition Acquire and store data every 1 second.

Antenna Characteristics Omnidirectional; vertically polarized; Gain = 1 dBi.

Location Place measurements system in the center of the city with the

highest elevation possible.

8
The measurement of LMR signal usage can be technically very demanding. The detection of

very weak LMR signals transmitted;P¥<iistant transmitters requires the use of a very good

system noise figure. However, the possible presence of relatively strong signals from close-in

transmitters means that strong signals'can occasionally push the measurement system

amplifiers into a non-linear region of operation and produce intermodulation (1M) products.

These 1M products appear like real signals to a measurement system. To minimize the

undesired generation of unwanted signals from 1M effects, a measurement system that has a

large instantaneous dynamic range is required.

Strong signals can also mix with local oscillator (LO) noise sidebands (what is left after the

pure sinusoidal signal is subtracted from a local oscillator). These LO noise sidebands create

a region of higher system noise for many channels on either side of the strong signal. To

minimize the effects of LO noise sidebands, it is necessary to obtain "cleaner" LO signals or

to somehow avoid strong signals in the receiver. Sideband noise can also be due to jitter in

the analog-to-digital converter (ADC), and sidebands created when applying a window

function to the raw digitized data; therefore, a high quality ADC and a carefully chosen

window function are required.

Because of the numerous unwanted effects of very strong LMR signals, great care is taken to

keep strong signals out of the measurement receivers. Measurement sites are selected on the

basis of having at least a minimum geographical separation from known sites with strong

transmitters. The measurement system is often used with narrowband preselection filters,

whose function is to limit the frequency range over which strong signals can enter the

measurement system. Known strong signals (e.g., transmitted from a nearby transmitting

tower) can be specifically rejected by tunable notch filters or other techniques. Unfortunately,

some of these techniques to control unwanted strong signals also tend to increase the

measurement system noise figure. Therefore, the actual performance of the measurement

system is often determined by a difficult set of compromises and adjustments that depend

partly on the specific characteristics of the local signal environment.

3.2 Site Selection

These LMR channel occupancy measurements were made using NTIA's Radio Spectrum

Measurement Science (RSMS) mobile laboratory at a site on the grounds of the partiallyabandoned Saint Elizabeth's Hospital located at coordinates N38° 51.427', W7T 0.013'

(Figure 1). The measurements were conducted 24 hours per day over the course of 8

consecutive days (Tuesday, October 26 to Wednesday, November 3, 2004), which included

the Presidential Election Day. The site was chosen for several reasons. It is centrally located

in Washington, D.C., and is elevated above the surrounding area. Because it is partially

abandoned, there is little LMR activity in close proximity. In addition, there are relatively

few strong base stations nearby that could overdrive the measurement system.

9
Figure 2 shows an aerial view of the Washington, D.C., area with a marker designating the

location of the measurement system. Figures 3 and 4 show coverage plots using the LongleyRice irregular terrain model (maximum receiver sensitivity) for three different transmitter

scenarios: 1) a 100-W transmitter with 3-dBi gain and a 30-meter antenna height (typical

base station), 2) a 50-W transmitter with O-dBi gain and a 1.5-meter antenna height (typical

mobile unit), and 3) a 10-W transmitter with -3-dBi gain and a 1.0-meter antenna height

(typical portable unit).3 Figures 3 and 4 are for frequency bands 162-174 MHz and

406-420 MHz respectively.

Figure 1. RSMS mobile lab at the St. Elizabeth's Hospital site.

3More realistically, portable units have a maximum output of 5-6 W, and therefore, the coverage plot for

portable units may be slightly less than that shown in the diagrams.

10
Figure 2. Aerial view ofWashington, D.C., area showing location ofmeasurement system.

11
•

Base, mobile,

hanohelo

Coverage Map

162-174 MHz

BaSe. only

Base and

mobile

Figure 3. Coverage plots for the 162-174 MHz band using the minimum receiver threshold.

12
• Base, mobile,

handheld

Coverage Map

ON 406-420 MHz

Base only

Base and

mobile

7BW 77W 7elf

0EE'3=E'3==C:::EE'3=350c::===::::;1ao~========315=O ===::::i20§:O=========3:250=======:i~O 1'14

Figure 4. Coverage plots for the 406-420 MHz band using the minimum receiver threshold.

13
3.3 System Hardware Components

A generic block diagram of the measurement system is shown in Figure 5. Two separate

fully automated systems were run simultaneously, one to collect data in the 162-174 MHz

band and the other to collect data in the 406-420 MHz band. Two separate vertically

polarized discone antennas, one optimized for each measurement frequency band, were

positioned on top of 10-meter masts. The preselector unit consists of a variable attenuator to

reduce system sensitivity in cases of strong local in-band signals, bandpass filters to reduce

strong signals outside the measurement band so that sensitivity and dynamic range

requirements can be maintained, and a low-noise amplifier to improve the system sensitivity

by reducing the noise figure. The output of the preselector is passed to an Agilent E4440A

spectrum analyzer that downconverts and digitally processes the signal in a specialized

"Base" mode configuration.4 A computer controls the spectrum analyzer and the preselector.

The computer also processes the data and saves it to storage for further post processing and

analysis. The preselector filters for the 162-174 MHz band consist of 3 separate bandpass

filters in the following I-dB bandwidths: 159-164 MHz, 164-169 MHz, and 169-174 MHz.

The filters are inserted into the path through an automated switching routine controlled by

the acquisition software. The 406-420 MHz system has a single bandpass filter with cutoff

frequencies at the edges of the band.

Discone

Preselector

E4440 Spectrum Analyzer

External

Compute

Display

Figure 5. Block diagram ofmeasurement system.

4"Base" mode on an Agilent E4440A spectrum analyzer provides FFT spectrum analysis, as opposed to swept

frequency analysis typically utilized for most spectrum analyzers.

14
3.4 Measurement Procedures

The 162-174 MHz band and the 406::c420'MHz band were each measured in contiguous

several-MHz-wide blocks, beginning at the lowest frequency block, continuing in severalMHz steps until the highest frequency block in the band was reached, and then restarting at

the lowest frequency block in the band. Within each block, signals were measured at 12.5-

kHz channel spacings so that the data could be analyzed for both the old 25-kHz channels

and the new 12.5-kHz channels by processing with the frequencies assigned to the respective

channelization schemes (described in Section 2.1). The 162-174 MHz band was measured in

3 separate frequency blocks: 162-164 MHz (158 channels), 164-169 MHz (400 channels),

and 169-174 MHz (400 channels). Though there is only one bandpass filter that covers the

entire frequency range of the 406-420 MHz band, the measurements were divided into 3

separate frequency blocks, with each having a span no greater than 5 MHz; these consist of

the blocks 406-411 MHz (400 channels), 411-416 MHz (400 channels), and 416-420 MHz

(319 channels). As with the 162-174 MHz band, signals in the 406-420 MHz band were

measured at 12.5-kHz channel spacings.

By setting the proper acquisition time period and using a Flattop window [7], a I-dB

resolution bandwidth of 5.5 kHz is achieved. This results in a 70-dB suppression for signals

outside a IS-kHz range, as demonstrated in Figure 6 which shows a fast Fourier transform

(FFT) of a continuous wave (CW) signal with the same settings used in the LMR

measurements. Figure 7 shows multiple FFT traces of a carrier signal FM-modulated with 3-

kHz band-limited Gaussian noise and a ±3-kHz maximum frequency deviation. Figure 8

shows the same thing but with a ±6-kHz maximum frequency deviation.5 The digital

acquisition time is short enough that, for anyone acquisition, the signal is relatively

stationary at a very narrow range of frequencies. For the different traces, the carrier is shifted

in frequency by the modulating signal but with a shift no greater than the maximum

frequency deviation. However, because there is still a small shift in frequency during the

acquisition, the spectrum of any single trace is "spread," as compared to that seen with a

CW signa1. Using this measurement scheme, it can be seen, therefore, that for two adjacent

channels (Cl and C2) and an FM modulated signal S with a center frequency at Cl,

essentially no power from S is detected at C2 by as much as 70 dB below the peak power

of S when the channel separation is greater than 12.5 kI-Iz for a ±3-kHz maximum frequency

deviation and 15 kHz for a ±6-kHz maximum frequency deviation. Therefore,

irrespective of the channel spacing, this resolution bandwidth can resolve adjacent FM

modulated, LMR-type channels as specified in the measurement requirements (Table 5).

5 Frequency deviation for all FM or PM station classes are not to exceed 5 kHz for analog wideband emissions,

2.5 kHz for analog narrowband emissions, and 3.11 kHz for digital emissions.

15
r-'\

I \ I \

I \

;.

I

I \ ..- .-.: -, -- --

-10

-20

::?.

ID

-30

"iii

c:

<II

E -40

i

en -50

.s

.5 -60

ro

ID

-70

f1.

-80

-90

-0.015 -0.010 -0.005 0.0 0.005

Frequency (MHz)

0.010 0.015 0.020

Figure 6. FFT ofCW signal using LMR measurement parameters.

Since a typical conversation on these Federal channels will last several seconds or more,

there is little advantage in measuring each channel more often than once every second (since

most of the additional measurements will give statistically-redundant information). In most

(but not all) of these LMR systems, the transmitter will be turned on only when the channel

is carrying a message. For these signals, the presence of a message can be detected by

tuning to the channel and noting whether a transmitted signal is present. Usually, this can be

done most easily by simply measuring the amount of RF energy received within the channel

bandwidth, and inferring the presence of a signal if the measured received power is larger

than the power that could reasonably be present from measurement system noise only. Based

on the measurement system noise figure and the windowing bandwidth, a specific "detection

threshold" is calculated, such that any measured channel power higher than the detection

threshold is assumed to indicate the presence of a transmitted signal.

16
0.0 • 0.005

MHz

.().oos

-701" i.-/

-301'············,··············· ., /

-201'-'" ; , "

-40 r--············,··············· ,I

-50f-' , i

E

!g -601'-: .·.·· .. ·.··.··.·i.···.··.··. /.

Figure 7. Multiple FFT traces of a carrier signal FM modulated with

3-kHz band-limited Gaussian noise and a 3-kHz

maximum frequency deviation.

Figure 8. Multiple FFT traces of a carrier signal FM modulated

with 3-kHz band-limited Gaussian noise and a 6-kHz

maximum frequency deviation.

17
The actual percentage of time that a given LMR channel is in use will be expected to

change, depending upon the specific function served by that channel, the time-of-day and

day-of-week, and the random occurrence of specific individual emergencies and other

important events. Therefore, a minimum set of measurements for LMR channel usage should

include data acquisition on each channel over a period of at least one week (including

weekends) on a 24-hr per day basis. Although it is not required that each channel be

measured continuously, it is desirable to include sufficient measurements to characterize

every channel on at least an hourly basis.

As diagramed in Figure 9, all the channels in a given several-MHz frequency block were

measured for 4 minutes, giving 240 measurements on each channel. At the end of 4 minutes,

measurement frequencies were shifted to the next-higher frequency block. Each frequency

block was re-measured every 36 minutes for the 162-174 MHz band and every 12 minutes

for the 406-420 MHz band.6 Thus, although a given frequency block was not measured

continuously, it was sampled for a 4-minute period interleaved with either 32 or 8 minutes

with no measurement (while other frequency blocks were being measured). This was

continued for 24 hours per day throughout the 8-day period. Thus each frequency in the

162-174 MHz band was measured 240 x 40 = 9600 times per day, spread out over 24

hours, giving 76,800 total measurements over an 8-day period. Frequencies in the

406-420 MHz band were measured about three times more often. The resulting measurement

data were saved for further analysis in the NTWITS laboratory in Boulder, Colorado.

6There is an hourly synchronization (± 4 minutes) of data acquisition for the 406-420 MHz band, This could

skew the mean usage (either up or down) if a significant number of transmissions are keyed up at specified times

each hour - though we have no knowledge of this type of timed usage.

18
159MHz 164 MHz 169 MHz 174 MHz

Block 1 Block 2 Block 3

I

5MHz 5MHz 5 MHz

I 12.5 kHz Channel X I

IOpen file for 164-169 MHz Band, 12.5 kHz Channel I

1Start acquisition

ISample and digitize 5 MHz block (approx. 1.07 ms) I

-+

I

Take FFT of 5 MHz block to process all I

four hundred 12.5 kHz channels

o!-

I Save the 400 values temporarilyl

J.

I Has power value for each 12.5 kHz I

No channel been measured 5 times?

I Yes

calculate and store median-of-5 power values for each ofthe four huncted

12.5 kHz channels using each set ofthe 5 sarrples per channel. Discardthe

5 t~oary values.

J. IHas block 2 been measured for I No J Delay till 1 I

4 minutes? I -I second complete

1 Yes

IMove to frequency block 3 for 12.5 kHz channels I

Figure 9. Flow diagram of channel power measurements.

3.5 Real-time Signal Processing

The measurements were performed using some of the specialized hardware and software

features of the Agilent E4440A spectrum analyzer. The spectrum analyzer provides highdynamic-range down-conversion to an IF signal with a bandwidth up to 8 MHz wide. The

8-MHz bandwidth IF signal is digitized with 14 bits of resolution at a 30 MS/s sample rate.

Using the "Base" mode software package, the digital data were processed on a real-time

basis, using a library of software signal processing routines.

The hardware-software package typically produced a measurement of the estimated received

power in each of 400 channels in a 5-MHz band during each I-second period in a 4-minute

19
measurement block. The process used to produce these 400 measurements each second is

described in the following paragraphs.

Once the spectrum analyzer is tuned to the center frequency of the 5-MHz frequency band,

the 14-bit digitizer acquires ADC readings for 1.07 ms, producing a digital record containing

about 32 kilo-samples (where sample size is dependent upon resolution bandwidth

specifications). These 32 kilo-samples are processed inside the spectrum analyzer with

firmware that produces a reading for the RF power at the center frequency of each of the

400 channels in the frequency block. The system has an 84-dB dynamic range, but if a

strong signal overloads the digitizer (approximately -22 dBm at the antenna terminals), an

alarm flag causes the 32 kilo-samples to be discarded and the digitizing process will repeat.

The digital data is windowed and then processed with an FFT to give a resolution bandwidth

of 5.5 kHz, after which the data is decimated7 to give a power reading at the center

frequency of each of the 400 LMR channels (spaced at 12.5 kHz).

These 400 Channel Power Readings are displayed on the front panel of the spectrum

analyzer and also transferred via an ethernet local area network to an external

controller/computer. The process of digitizing, computing, and transferring data for the

frequency block requires about 150 ms, with a majority of the time used by the data transfer

process. The digitizing, computing, and transfer process is repeated five times, ending when

5 sets of 400 data points are obtained, representing five Channel Power Readings of each

channel in the frequency block. At this point, the computer determines the median value

from the 5 measurements for each channel, and the set of 400 median values for each

channel - also referred to as the Channel Power Values - becomes the data output set for

that respective I-second measurement period. The system then waits until the beginning of

the next I-second measurement period, when the median-of-5 measurement cycle begins

again to produce another set of Channel Power Values.

The median-of-5 processing was selected to minimize the effect of amplitude variations

caused by signal modulation, measurement system noise, and external impulsive noise. The

importance of this processing for minimizing errors in determining channel occupancy is

discussed in more detail in section 4.

The Channel Power Values for each of the channels in the frequency block are also

incorporated into a continuously updated (every second) data display on the external

computer as shown in Figure 10. This external display shows the most recent I-second

Channel Power Value (referenced to the spectrum analyzer input) for each measured channel

(blue "+" symbols), as well as a peak value for each channel updated over the current 4-

minute frequency block (black "+" symbols). The operator can position a cursor over a

particular frequency and obtain readouts of these quantities, as well as the exact frequency of

7Decimation, in this case, is the process of eliminating unnecessary data points that occur between center

frequencies of the channels.

20
the selected channel (e.g., this allows a receiver/demodulator to be tuned to a channel-ofinterest). The display on the extemal:Gomp'l.1feris,contiiiu,Hly updated with data from the

most recent I-second Channel PowerVal~e,~hile the spectrum analyzer shows a display of

the current 5-per-second instantaneou~;'ehannel Power Reading from the measurement

process.

'''!

'~~

"',:-"

'rl'

.~

,', " ~~', ,

.:,.",""- + +, +

'" . "

.~~" :I: ,+ -It + + +.t

;:~~1~ .tt~

.~. .J.. . it..

.....+ .... + '+ -....: + ...' +' ........ +

.",., , .~~,

, "':4)6 407 " 'Ida.:.. " ,<4)9 40 ------~il.

Figure 10. "Data display" as viewed on the computer (power referenced to

spectrum analyzer input).

3.6 Calibrations

System calibrations using the noise source Y-factor method were performed immediately

prior to the measurements and again at the end of the week. 8 Certain signals of known

power and 100 percent usage were also checked on a daily basis to monitor the integrity of

the system. Gain factors, as determined by the calibration, were later subtracted from the

measured power levels to reference the power to the output of the antenna terminals. Noisefigure values were used to determine detection thresholds for signal-occupancy processing.

All of the antennas were calibrated at a certified laboratory within 6 months of the

measurements. Antenna correction factors were then used to determine the field strength

based on the received power at the input.

8The Y-factor calibration technique is used here to determine the noise factor and gain of the system [8].

21
4 POST-MEASUREMENT PROCESSING

This section describes post processing techniques used to extract channel occupancy

statistics. This includes setting the proper detection threshold levels, as well as removing the

effects of impulsive noise and measurement system sideband noise.

Although very significant efforts were made in hardware design and field measurement

procedures to minimize measurement defects caused by IM, LO noise sidebands, broadband

impulsive noise, and other problems, the raw measurement data still contains certain defects

from these sources that, for the most part, can be corrected. Since techniques that would

have eliminated these defects completely would also have decreased the ability to measure

weaker signals, we chose to operate with better sensitivity - anticipating that we could

adequately remove most defects with further post-measurement processing. This section

describes those efforts to identify and remove the most common types of measurement

defects.

All of the post-measurement defect-reduction processing is performed on the saved I-second,

median data (Channel Power Values). A key factor in being able to distinguish some of

these defects from the good data that they are embedded in is that the entire set of I-second

data is measured simultaneously across an entire 8-MHz IF bandwidth. The 8-MHz

bandwidth completely captures the 5-MHz sample of signals that can pass through the 5-

MHz (typically) RF bandpass filters in the preselector. That means that the processed data

would be expected to include all of the high-amplitude signals that could have caused IM

products to appear in the computed Channel Power Values - which means that proper

modeling could remove most of the IM effects. However, initial analysis of the data showed

that IM products from strong signals occurred so infrequently during these measurements that

removing them using specialized processing techniques was not warranted.

4.1 Broadband Impulsive Noise

Broadband impulsive noise from electrical machinery or automobile ignition systems is

usually seen on scanning spectrum analyzers as a sequence of impulses appearing at more-orless regularly spaced frequencies across the analyzer display. Actually, the noise impulses are

very broadband, but they show up on swept analyzers at whatever frequency the spectrum

analyzer was measuring at the instant when the noise impulse occurred. However, the

"simultaneous" nature of the 8-MHz IF digital sampling used in these LMR measurements

means that either all frequencies show the noise, or none of them do. If the noise impulse

occurs during the I-ms digitizing period, the effect of the broadband noise will be generally

present at each of the frequencies in the band of measurement. If the noise impulse does not

occur during the I-ms digitizing period, it will occur in none of the frequencies.

22
Therefore, impulsive noise can be eliminated in two very effective ways. The first "line-ofdefense" against impulsive noise is from the median-of-5 measurement algorithm. Unless at

least three of the five independent llle~~llf~lIlents taken :in a I-second period are

contaminated by impulsive noise, th~0;h6iSewill be almost completely eliminated by the

median-of-5 processing because these higher power levels occupy the places of the 2 highest

readings and are ignored (along with the 2 lowest readings). Therefore, most impulsive noise

is eliminated on a real-time basis by the measurement algorithm and is never seen in the

recorded median-of-5 Channel Power Values.

If the median-of-5 Channel Power Values are contaminated with noise, all channels will tend

to be similarly contaminated. This allows contaminated Channel Power Values to be easily

recognized and removed from further data analysis. The noise-contamination algorithm

checks to see whether at least 75%9 of the frequencies in the measured band were 5 dB or

more above the arithmetic mean10 system noise power. If so, that set of Channel Power

Values is judged contaminated by broadband noise and removed from further processing.

Figures 11 and 12 show two sequential measurements, one without impulsive noise and one

with, taken 1 second apart (the threshold being 8 dB above the median system noise). The

impulsive noise in Figure 12 appears as a substantial momentary increase in system noise,

causing that data set to be rejected from any further processing.

9 75% was chosen because it is highly unlikely that 75% of all channels in the band would simultaneously come

on line. Because the signal power for each of the channels is measured simultaneously, the impulsive noise is likely

to raise the noise floor for, at least, 75% of the channels in the band.

10 For median-of-5 traces of Gaussian noise there is a 1.5-dB difference between the arithmetic mean and median

power - mean being the higher of the two. In this report, both mean and median are used under different

circumstances, but each may be translated to the other using the 1.5-dB correction factor.

23
-20,---!!--,-------,---~!-,-------r-_____.--Tf'==:::====:=::'=il

I

° Channel Data

-Threshold

-401--........... , 0,....... • ,..................................... , .. .... ,. ... -

:8- -601--

"

!! -SO

"

1ii 1-100

"

-14~6:-04-------;c16::':4-=-.S-------;c16=S-------;c16::!:S-=-.S-------;c16=6-----:-16:::6:-:;.S-----:-16=7:------:-1:::67:-:;.S-----:-16:::S:------:1:::6S:-:;.S:---------;-:;169

Frequency (MHz)

Figure 11. One-second sample without impulsive noise.

-SO,---.---,---,---,----.--,-----,---,---T[=o==C:='ha=nn=e===1D"'

at

=i1

a

-Threshold

-601-- , '..... , , ,............................... • ···· .. ····· .. ···,···'=====1

.. ... -120..· · ,.......... . ,., , ., ,. .•• • , ·c. ,

-701-- ..···..····,· ..····· .............•. , ,............................ , .

:8-

-80

'§"

$

!! -90

"

1ii -1001--···· , .

-13~6~4------,-16;;';4-;;.S------,-16~S:-------,-16=S:-:;.S------,-16!;;;6:------:1~66c:;.S:------:1!;;;67;-----:1~67c:;.S:----:1~6S;---:1~68c:;.S:-------:-!169

Frequency (MHz)

Figure 12. One-second sample with impulsive noise.

While every effort was made to minimize the effects of noise, there were occasional periods

when impulsive noise raised the power in the entire band enough for individual channels to

exceed the detection threshold but not high enough to trigger a "data discard." It is difficult

24
to determine precisely how often this occurred but it may have occurred enough to skew the

mean usage values somewhat towards higher than expected usage values.

4.2 Noise Sidebands

Noise sidebands, due to either the measurement system local oscillator phase noise, jitter of

the ADC, or sideband characteristics of the windowing :function (and sometimes transmitter

phase noise), can cause apparent signals adjacent to the channel occupied by a strong signal.

In the case of these measurements, the noise sidebands produce additional apparent adjacentchannel signals for any real signal at least 60-70 dB above the system noise level. These

additional responses decrease at the rate of about 0.5-1.0 dB per channel, for channels

further away from the strong signal, and eventually these additional responses disappear

below the measurement system noise. Because of the nature of these additional responses,

they cannot be removed by using real hardware IF bandpass filters.

Since the noise sideband responses can affect a large number of additional channels, it is

especially important to remove these false signals. These noise sideband responses are

eliminated by measuring the levels of a typical noise sideband response and generating a

"mask" that shows how much signal power to subtract (in linear form) from each channel

located adjacent to a strong signal. Fortunately, this mask is typically quite stable and

predictable. Unfortunately, the mask is probabilistic - having an amplitude distribution

similar to Gaussian noise instead of giving a single value at each frequency. This means that

5-10 dB extra power must be subtracted to reliably disc:ard the noise sideband responses.

The major problem with subtracting so much additional signal power is that this process

may also discard some real (but weak) signals located near the strong signal. Figure 13

shows the effect of noise sideband responses on measured signal levels, as well as the

effectiveness of the algorithm in removing this signal contamination.

25
-i3-Original Data

Sideband to be Removed

- Sideband Removed

r.1

~~ifv~ .~ "..,. V

...JiL.. m

.~ .~1 ~~

-20

i -60

.!!1 -80 l\l

c: '§

.l!l -100 l\l

c:

c:

.l!l -120

16

1ii

li:i -140

c...

-160

-40

-180

-200

414.7 414.8 414.9 415 415.1 415.2 415.3 415.4 415.5

Frequency (MHz)

Figure 13. Removal ofLO noise sidebands.

4.3 Detection Thresholds

Once imperfections due to impulsive noise, and sideband noise are removed, the next step is

to determine the presence of real LMR signals. Determining channel traffic reduces to the

problem of determining the portion of time that a signal is detected on the channeL The

obvious way to determine whether a signal is present on a channel is to measure the

received signal power. If the measured received signal power is substantially higher than

some appropriately-selected threshold value, the channel must contain a signaL If it is

substantially lower than this threshold value, the channel probably contains only system noise

- or possibly noise plus a very weak signaL For our purposes, a signal below system noise

is not likely to provide usable service to the LMR user, and therefore it should not be

counted as real traffic at the measurement site.

The selection of an exact detection threshold presents some trade-offs. If a very low

detection threshold is selected (i.e., close to system noise), some statistically expected noise

bursts will occasionally exceed the selected threshold and cause a certain amount of usage to

appear on all radio channels (even unused channels). On the other hand, if a much higher

26
detection threshold is chosen, some weak (but functionally usable) signals may be left

uncounted by the analysis program. The actual threshold level selected for determining

channel usage is therefore a comprol11ise1?etween noise-caused false usage (low detection

thresholds) and missed usage of weaker signals (high detection thresholds). ill some cases,

local external background noise can exceed the system noise, changing the optimal detection

threshold level. Some quantitative insights to the selection of a detection threshold can be

obtained by considering the amplitude probability distribution (APD) [1] for measurement

system noise only. Figure 14 shows an APD for multiple single samples of system noise

(solid line) and for multiple noise samples processed as median-of-5 values (dashed line).

The solid line shows the expected straight line for Gaussian noise, using the "Rayleigh"

graph scaling. The vertical scale is in "dB, relative to the median power." Therefore, both

lines cross the "0 dB value" at the 50% point. The arithmetic mean level of power for the

unprocessed system noise is about 2 dB above the median value. The graph shows how

much of the time system noise is found at various amplitudes. For example, the graph shows

that system noise will be 10 dB above the median value about 0.1% of the time. This means

that if a detection threshold was selected at 10 dB above the median noise value (8.5 dB

above the arithmetic mean noise power), a channel with no real signals would be expected

to show a usage of about 0.1% - since the system noise alone exceeds the lO-dB level 0.1 %

of the time.

15 rr-,---,------,---,----,,------,-----.------r-,----,--,--------,----,--------------,

-15I-;··I··;··········;···········i· qq ·;··q···;······;·.., ; ,·········i···············,···················,······· :>""'~

-20.001.01 .10 1.0 5.0 10 20 3036 50 70 80 90

Percent exceeding ordinate

Figure 14. APD ofsystem noise.

27

95 99
On the other hand, if all measurements are processed with a "median-of-5" routine, system

noise appears to have an APD described by the dashed line. (The horizontal left-hand part of

the curve is an anomaly caused by an insufficient number of measurements; assume that the

actual dashed curve extends the general shape of the remainder of the line.) The dashed line

is more horizontal (i.e., has fewer high-dB or low-dB samples), because the median-of-5

process requires that at least 3 of the 5 measurements be as large as the indicated value

(versus only 1 of the 5 measurements for the single-measurement statistics). Therefore, large

variations are less likely for the median-of-5 process. This allows the detection threshold

value to be set closer to the median noise value without increasing the probability of false

usage readings. For example, allowing 0.1 % of false usage readings, the median-of-5 data

occupancy threshold could be set near 6 dB, nearly a 4-dB improvement over the individual

readings.

Presumably, this detection threshold could be improved even more by taking the median of

even more readings - possibly a median-of-11 or median-of-21 readings. However, this

would have considerably increased the measurement time and would eventually cause some

problems with measurement of short messages. It should be noted that this median-of-5

process is also believed to have removed much of the amplitude variation due to signal

modulation techniques and to have almost completely removed any effects from external

impulsive noise which might otherwise be falsely detected as LMR signals.

In order to achieve a probability of no greater than 0.01 % that an instantaneous system noise

level will exceed the median system noise (as specified in Table 5), a minimum threshold of

8 dB above the median system noise was chosen for processing. This means that, at the

minimum threshold, there is a probability of only 0.01% that system noise could give a false

indication of an LMR signal. Additional higher thresholds were also chosen for processing

for the purpose of displaying statistics on multiple threshold levels.

Due to TV Channel 7 out-of-band emissions, a correction to the minimum detection

threshold is applied in the spectral region between 170.7-174 MHz. Figure 15 shows the

median of multiple median-of-5 Channel Power Values in the frequency range

169-174 MHz. Because some of the out-of-band emissions from TV Channel 7 have a

power as much as 10 dB above the threshold, the minimum detection threshold (where the

threshold is 8 dB above the median system noise - square symbols in Figure 15) is not

sufficient to exclude noise that could be falsely construed as LMR signals. Therefore, in the

region between 170.7-174 MHz, the minimum detection threshold is determined by adding

9 dB to arithmetic mean noise power that is due to TV channel 7. This modified threshold

is represented in Figure 15 by the solid line. Analysis of the TV out-of-band emission

statistics showed that this modified detection threshold would allow the TV out-of-band

emissions to be mistaken for LMR signals only in 0.01 % of the measurements.

Throughout the analysis, statistics are reported for various thresholds - the minimum

threshold, as well as several thresholds at 10 db intervals above the minimum. Because the

28
29

.13~6~9 --=169~5---:-:17~O ----=170~5-----:-:17~1 ----=17:-:1.5,-----:-::::---=172~.5,-----:-:17=-3 ----=173~5---------::.174

Frequency (MHz)

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

I

'4°[]:r===~~l ·50

-110

.120 .

Figure 15. Thresholds and median ofmultiple median-of-5 data acquisitions.

minimum detection threshold in the region between 170.7-174 MHz has been increased by

as much as 15 dB due to Channel 7 out-of-band emissions, all thresholds above the

minimum detection threshold are set§gthat, ~t no point is the threshold less than any other

preceding "lesser" threshold for the ~';siifu~"lrequency channel. Because the detection threshold,

especially the minimum threshold, is not constant across the frequency channels, threshold

values given for statistical analysis are stated in terms of "mean" threshold power.
5 ANALYSIS AND RESULTS

This section discusses the various methods of statistical analysis employed to summarize the

channel usage in various LMR bands. Graphs and tables summarizing the usage for the

different bands are included in the latter half of this section, as well as in Appendix A.

5.1 Frequency Groupings

Two primary frequency groupings were analyzed as follows:

1. 162-174 MHz (excluding NOAAll weather radio channels located at 162.400, 162.425,

162.450, 162.475, 162.500, 162.525, and 162.550 MHz).

2. 406-420 MHz.

5.2 Channelization

As described in Section 2.1, channel assignments in these bands are now required to migrate

toward a 12.5-kHz channelization; however, some LMR systems are still operating under the

25-kHz channelization scheme. To get an understanding of how much the newly created

channels (spaced 12.5 kHz between the old assignments) are being used, analysis was

performed on the following sets of channels:

1. all channels spaced 12.5 kHz apart.

2. channels assigned under the old 25-kHz channelization (spaced 25 kHz apart) -

referred to in this report as "the old 25-kHz channels."

3. channels earmarked for the 12.5-kHz channelization (spaced 25 kHz apart and

located halfway between the old 25-kHz channels) - referred to in this report as

"the new 12.5-kHz channels."

5.3 Time Scenarios

Entire week: Data analyzed as a whole for the entire week Tuesday, October 26,

2004 at 2:00 PM through Wednesday, November 3, 2004 at 4:00 PM, independent

of time or date.

Date and time of day: Data analyzed according to the date and time in one-hour

blocks.

2.

Each of the 2 frequency groupings were analyzed according to 6 different time scenarios as

follows:

1.

liNational Oceanic and Atmospheric Administration.

30
3. Time of day for any day: Data analyzed according to time in one-hour blocks

between 12:00 midnight and 12:00 midnight 24 hours later, independent of date or

type of day (e.g., weekend day).

4. Time of day for Election Day: Data analyzed according to time in one-hour

blocks between 12:00 midnight and 12:00 midnight 24 hours later only on Election

Day (November 2).

5. Time of day for weekdays: Data analyzed according to time in one-hour blocks

between 12:00 midnight and 12:00 midnight 24 hours later only for weekdays,

independent of the type of weekday.

6. Time of day for weekends: Data analyzed according to time in one-hour blocks

between 12:00 midnight and 12:00 midnight 24 hours later only for weekend days,

independent of the type of weekend day.

5.4 High Occupancy Channels

In addition to the frequency and time groupings, data were also analyzed under two

scenarios with regard to high occupancy channels (HOCs). HOCs, as defined for analysis

under these measurements, are channels where the received signal level is above the

detection threshold greater than 80% of the time (other than the NOAA weather radio

channels, which were always excluded from analysis). Known examples of HOCs include

channels used for telemetry (such as hydrology sensors) and control channels used in LMR

trunked systems. Since these HOC channels differ greatly from the much lower percent

usage of LMR channels, HOCs represent "outliers" that would substantially skew the mean

LMR channel usage statistics. For this reason the data were sometimes processed with HOCs

both included and excluded in the analysis, the latter providing a method for determining the

usage for LMR channels that represent the overwhelming majority of signals in the LMR

bands. These HOCs represent 1.1% of channels in the 162-174 MHz band, and 0.5% of

channels in the 406-420 MHz band.

5.5 Busiest Hour Statistics

Several of the statistical summaries are reported for "busy hours," or a similar term, as

applied to the usage of single channels or groups of channels. There are several distinct

defmitions for these processed statistics, which we will carefully describe here (as well as in

sections 5.7) since substantially different numerical results can arise from slightly different

processing algorithms.

The quantity that is loosely called "hourly usage" does not actually contain the results from

60 minutes of measurements. Instead, it represents the averaged results from whatever

measurements were sampled during that hour. Typically, the hourly data were derived from

two 4-minute measurement periods (separated by 32 minutes without measurements) for

31
frequencies in the 162-174 MHz band and from five 4-minute measurement periods (each

separated by 8 minutes without measurements) for frequencies in the 406-420 MHz band. In

about 12% of the hourly blocks in the 162-174 MHz band, the data were derived from a

single 4-minute measurement. Sampling for less than the full hour can skew any of the

"busy hour" results because a shorter sample period gives a greater statistical spread of

percent usage for each channel. Typical usage in many of these channels tends to cluster into

short periods of high activity, possibly with several almost-continuous exchanges between

base and mobile stations, followed by a period of less usage. For a sample time shorter than

a typical message, a given channel will tend to be used 100% of the time or not used at all.

In a longer sample time, the short very-busy periods tend to be more smoothly averaged-out

by the idle periods. Therefore, when looking at any of the busy-hour results, a shorter

sample period tends to skew the data towards higher usage percentages.

In the following descriptions, we observe that the word "hour" has at least two distinct

meanings: 1) a 60-minute period, and 2) a time of the day (e.g., "the hour is late"). In the

"busy-hour" statistics, we will use "hour" only in the sense of an arbitrary 60-minute period,

i.e., any hour of the day, week, or year. Whenever a specific time of the day is described,

the term "time-of-day" will be used. Unless otherwise indicated, "time-of-day" will refer to

the set of 24 one-hour time blocks that has been used to categorize the measurement data.

The Hourly Channel Percent Occupancy is computed for each channel, each hour of each

day, by taking all of the Channel Power Values in an hour for a channel, comparing them to

the detection threshold, and then determining the percent of values that exceed the threshold

during that one-hour period.

The Busiest Hour of the Week for Each Channel is the specific 60-minute time block within

the entire I-week measurement period when the average usage on a given channel was

highest. The Busiest Hour of the Week for Each Channel is determined by examining the

Hourly Channel Percent Occupancy every hour of every day over the course of the

measurements for each channel and identifying the "busiest hour" as the date and hour for

the Hourly Channel Percent Occupancy with the largest value for each channel. Different

channels will typically have a different date and time when the usage is highest.

The Busiest Usage by Time-of-Day for Each Channel is the highest average usage measured

for a single channel during a particular time-of-day hourly block, over the course of the

pertinent measurement period. There are 24 time-of-day hourly blocks, each lasting one hour

and beginning and ending exactly on the hour. The Busiest Usage by Time-of-Day for Each

Channel is computed by grouping into 24 separate time-of-day groups all of the Hourly

Channel Percent Occupancy values within the pertinent measurement period (which could be

a day or multiple days). The weighted average for each channel of all of the Hourly Channel

Percent Occupancy values within each one-hour period is then determined. They are

weighted because not all one-hour-periods have the same amount of acquired data. The

highest of these 24 average values is called the Busiest Usage by Hour for Each Channel.

32
Figure 16 is a diagram of fictitious data used to represent the difference between these two

different types of "busiest hour" statistics. This diagram shows the average usage for each

hour of the day of a single channel,<'Sith ~ach of the thin lines representing a different day

during the course of the measuremeilts;lTh6 green dot represents the Busiest Hour of the

Week for a Specific Channel since it is the one hour out of all of the single-day plots for a

specific channel that has the highest value. The thick black line represents an hourly average

by time-of-day over the entire measurement period. The red dot represents the Busiest Usage

by Time-of-Day for a Specific Channel since it is the largest value of the 24 time-of-day

averages. One can say that, in this diagram, the Busiest Hour of the Week for the Specific

Channel occurs at 6:00 AM on Day 1 and the Busiest Usage by Time-of-Day for the Specific

Channel occurs at 3:00 PM.

The Busiest Hour of the Week for Each Channel method is used to determine the time of

occurrence of the busiest hour for each channel (Figures 27 and 39), described later, which

may help show whether "events" may cause high usage in multiple channels within the same

hour. The Busiest Usage by Time-of-Day for Each Channel data is used to compile statistics

showing how many channels were at various levels of usage during their busiest hour (e.g.,

Figures 34 and 46).

The Average ofBusiest Usage by Hour is a single value that is computed by determining the

average of all the usage values corresponding to the Busiest Hour of the Week for Each

Channel across all channels in a band. These values are displayed in Tables A-I, A-2, A-5,

and A-6 as "Busy Hour Usage (24 hours)."

33
2.5

2.0

.. 1.5

#.

..

Cl

..

II>

::::l 1.0

0.5

.~

......... D !(" - •.. D W2 - !!utir we kfo a D !(3

D W4 - D y5 - I- DilV6 - D

~ui - ver Vlel,.""" b I - I-- - -

- ...:= - - .....

- ""-I-- /"-- -

=

I- L....I lI- - F- f=: - - ""-- ,..,.,..- - V I- - .. c--I - ""-- - - F= / ... - '-- le-- ;:::: - Bill est sail by

"--' -

o 4 8 12

Hour of the DaV

16 20 24

Figure 16. Diagram offictitious data showing the difference between

"busiest hour ofthe week" and "busiest usage by hour."

5.6 General Description of Analysis

The data is summarized with variations on 6 types of analysis:

(1) graphs of Hourly Band Usage during different I-hour time periods.

(2) graphs of the Busiest Hour of the Week for Each Channel.

(3) APD graphs of Channel Power Values for all channels across the band.

(4) cumulative distribution graphs of the percent of channels (or hourly channel

usage) exceeding a given percent usage.

(5) cumulative distribution graphs of the percent of channels that exceed a given

percent of hours at greater than or equal to a given percent usage.

(6) tables of Percent Band Usage (during 24 hours and during the hours of 8:00 AM

to 5:00 PM) and Average ofBusiest Usage by Hour (during 24 hours).

Hourly Band Usage is determined by computing the Hourly Channel Percent Occupancy of

each channel and then determining the mean usage of all the channels in the band. A graph

of Hourly Band Usage is demonstrated in Figure 17, which shows both the Hourly Band

Usage of channels in the band and total Erlangs (where Erlangs are determined by

multiplying the Hourly Percent Usage by the total number of channels in the band -

Table 6). Tic marks identify midnight. Each Hourly Band Usage represents a different hour

and day.

34
Figure 18 shows Band Occupancy by Time-of-Day, which is determined by taking the

Hourly Band Usage values for each hour of the day, and computing the average for the

corresponding hours of the measurement period. Results in these example graphs are

summarized for multiple mean thres~qldpo'Wer levels (expressed in power at the antenna

terminals and field strength at the input to the antenna), whereby a channel is considered to

be occupied only if (as described in Section 4.3) the power exceeds the given threshold. As

an example, Figure 18 shows that Band Occupancy by Time-of-Day of this sample data is

approximately 2.8% at 10:00 AM WhYllllsing a mean field-strength threshold of 12 dB

/lV/m. Variations of the Hourly Band Usage and Band Occupancy by Time-of-Day plots

(summarized in Tables 7 and 8) consist of different frequency groupings, time scenarios,

channelization schemes, and detection threshold levels.

While the Band Occupancy by Time-of-Day in Figure 18 varies between approximately

1-3%, readers are cautioned against drawing the conclusion that, because the channels in

these bands were used 1-3% during the course of these measurements, 97-99% of the

channels can be relinquished for other use. Because most of the channels in these bands are

statically assigned to receivers, as opposed to dynamically assigned as is the case with

trunked systems (see Definitions), many of these channels are reserved for high priority

usage in which communication must be available at all times for a limited number of users,

thus resulting in low percent usage. The Public Safety W'ireless Advisory Committee

(PSWAC) recommends in a report [9] that call-blockage (typically defined as Grade of

Service) should not exceed "one call for service per one hundred attempts during the average

busy hour." That translates to no more than 1 percent usage for multi-user conventional

(non-trunked) systems where channels are assigned statically.

It should also be noted that while the Band Occupancy by Time-of-Day in this band varies

between approximately 1-3%, individual agencies may have averages that deviate from these

values - either to a greater or lesser extent. Likewise, none of these measurements were

made during a major emergency that might have greatly increased the use of radio channels.

Table 6. Total Number of Statistically Analyzed Channels Spaced 12.5 kHz Apart

Frequency Band Number ofChannels

Analyzed

162-174 MHz - including HOCs 944

162-174 MHz - excluding HOCs 934

406-420 MHz - including HOCs 1119

406-420 MHz - excluding HOCs 1113

35
45

4.5

3.5

---a- Min Threshold: -117 dBm at aolenna terminals, 12 dB microvol1s1m at anlenna input

-:v- Threshold: -100 dBm 81 antenna lermlnals, 29 dB mlcrovonslm at anlenna Input 50

--&- Threshold; -90 dBm at antenna terminals. 39 dB mlcrovoltslm at anlenna Input

---+- Threshold:...aO dBm mantenna terminals, 49 dB mlcrovonslm at antenna input

-"-,.'--- Thrnhold: ·70 dBm at antenna termInals, 69 dB mlcrovollslm at antenna Input

40

Fn Sot SUn Man Tue Wed

DaysafWeek

Tue Wed Thu

0.5

" 3 1l,

E " F 30 in" 25

ill> 25 t-:"

ill 2 "

g> ::> 20

1.5

Figure 17. Sample graph (reference to Figure A-2) of

Hourly Band Usage (percent oftime and total

Erlangs).

30

20 &

ill

::>

15

10

10 15 20 25

Hour of the Day

3.5 t-"""-==~~~~~~~~~~~~~~~~1140 ---e-- Min Threshold: -117 dBm at antenna terminals, 12 dB mlcrovoUshn at antenna Input

Threshold: -114 dBm at antenna terminals, 15 dB mlcrovoltslm al antenna Input

.....(; --- Threshold: -100 d8m at antenna terminals, 29 dB mlcrovonslm at antenna Input

~--I-- Threshold: ·90 dBm at antenna tennlnals, 39 dB mlcrovonslm at antenna Input 35

Threshold: ~80 dBm at antenna tennlnals, 49 dB mlcrovonslm at antenna Input

2.5f-················ ·, ···· ···1= ·· ,,,/ \, i ·········

F

'0

#

Figure 18. Sample graph (reference to Figure 42) ofBand

Occupancy by Time-of-Day (percent oftime

and total Erlangs).

As previously explained in Section 4.3, the detection threshold values in these figures are

mean threshold values, where the average is determined across the appropriate range of

frequencies.

36
An example of the Busiest Hour of the Week for Each Channel is displayed in the graph in

Figure 19. The x-axis is divided into one-hour blocks throughout the week and the y-axis

represents the individual channel freCl~en~i~s. One-hour time slots in which anomalies

occurred (as described in the latter ~artofthis section) were excluded from processing. The

purpose of this type of graph is to display the distribution of channel usage throughout the

passage of time to identify possible aggregation of channel usage at certain time blocks. For

instance, there are diurnal patterns where the use is heaviest at certain hours of the day, and

during those heaviest-use times, certain groups of adjacent channels were simultaneously

busy. For instance, multiple channels between 173-174 MHz had the heaviest usage at

approximately 3:00 AM on Saturday morning (point A). It should be kept in mind, however,

that whenever large numbers of adjacent frequencies appear to become busy at the same

time, there is a possibility that the measurements were being affected by broadband RF

energy, radiated intentionally or accidentally. Also note that data on different groups of

frequency channels (3 groups for each of the two bands) were acquired at different blocks of

time. Therefore, correlation between these different blocks may not exist since the heavy use

may have occurred during the acquisition of one frequency group but not the others.

Correlation within the frequency groups of simultaneously acquired data could exist if a

significant event triggered multiple use of channels in that group.

37
174

'l .~' , , , I : , , J.,

,~ A :'

:? ,

'"

, 172 .. ......,.. ' f' , , ' , ,

" j , : .,. " :' , .. ", " : I , , ' , ' .. 'c . ; '. ' : , '. , N 170 , : r . ....

: :I: " " " , t ,

" " 1)- ," "

f c: , " , <I> .: , a- 168 _.. .1' : ", . " , . :.' ' " " .. "ij) , ., , ,

c: " , " : ..... c:

<tl , .. , '" .s:: " " " .. 0 166 , "

"

.. , " , " , , .t' f '. " , ", '. , ',' " ,~ , .. ..... , , , .. " , "

, '. : , , ".;- , " 164 ',:. , .... .. . .

" ' " ,, , , , , " , , , • t '" ,', " " j' " , ,~

... .. , : , ; ; .. 162 " , ,

Tue Wed Thu Fri Sat Sun Man Tue Wed

DaysafWeek

Figure 19, Sample graph (reference to Figure 27) ofthe Busiest Hour ofthe Week

for Each Channel,

APD graphs of Channel Power Values are cumulative probability distribution plots

representing the percent probability of a channel exceeding a given Channel Power Value at

anyone moment, where the y-axis displays power and the x-axis displays the probability

expressed on a Rayleigh scale. A detailed description of APDs is provided in a tutorial

located in Appendix A of [1].

Figure 20 shows an APD plot of Channel Power Values for all channels in a band. There

are two lines on the plot, one that shows the percent probability of a channel exceeding a

given Channel Power Value and the other showing the percent probability of exceeding a

given power due only to Gaussian system noise (represented by the slightly sloped horizontal

line), Points on the first line that deviate from the latter line are due to either LMR signals

and/or RF noise that exceeds the system noise. Because most of the impulsive noise was

removed using the techniques described in Section 4.1, points deviating from the system

noise curve are believed to be due primarily to LMR signals. The y-axis is displayed in both

Channel Power Value at the antenna terminals in dBm and field strength in dB /lV/m, For

example, Figure 20 shows that there is a 1 percent chance that the Channel Power Values

38
for the chamlels in the band exceed a field strength of 44 dB flV1m at the measurement

antenna input or -85 dBm at the antenna output.

80

20

"\ 1- ~R .;no.l. I

........'\

\ .......

'\

\

\

\

\

\ 1

I

·110

-120

-40

-30

·130

-50

E -60

co

:8.

~70

.~

.l!! -80 co

<::

iii ·90

iii

·100

a.

.001 01 .10 1.0 5.0 10 20

Percent exceeding ordinate

30 36 50

Figure 20. Sample APD (reference to Figure 47) ofChannel Power

Values for all channels in a given band.

39
Figure 21 shows a representative cumulative distribution graph of Hourly Channel Percent

Occupancy values that exceed a given percent usage for different channelization and HOC

scenarios, whereby a channel is considered to be "occupied" whenever (as described in

Section 4.3) the measured power exceeds a given detection threshold (-113 dEm, in this

example). In this figure, for the case of all channels spaced 12.5 kHz apart with the HOCs

excluded, it can be seen that 13 percent of the Hourly Channel Percent Occupancy Values

have a percent usage of greater than 1 percent, or conversely that 87 percent of all 12.5-kHz

channels have a usage less than 1 percent. Similar conclusions can be determined for the

other channelization cases presented in Figure 21. Note that a channel was considered to be

an HOC when the measurements showed an 80 percent or more mean usage over the 8-day

measurement period. However, it is possible for a channel with mean weekly usage of less

than 80 percent to have some hourly periods where that value is exceeded. Those periods are

still included in these statistics.

100

10

1.0

..... ',,"

..... ....

....-..,

... ~""- !\ \ ....,..... \ \ .. .--~

~~\\.

.. \

'.. ,

.--.:

• •

:"\ ~-

.''V.

-All channels spaced 12.5 kHz apart (HOC inclUded)

. _._.- Old 25 kHz channels (HOC inclUded)

•••• ___ 0 New 12.5 kHz channels (HOC included)

: -All channels spaced 12.5 kHz apart (HOC excluded)

.,.,. Old 25 kHz channels (HOC excluded) ': •••• New 12.5 kHz channels (HOC excluded)

•

0.01 0.10 •1.0 10

Percent of Hourly Channel Percent Occupancy values exceeding ordinate

100

Figure 21. Sample graph (reference to Figure 32) ofthe percent ofHourly

Channel Percent Occupancy values exceeding a given percent usage.

40
Figure 22 shows the Channel Percen.t?cf~pancy for the week of measurements. This is

computed for each channel by taking;eyeiy Channel Power Value for each I-second

acquisition every day and comparing that to the detection threshold to determine an overall

percent occupancy for the specific channel. As shown in Figure 22, for the case of all

channels spaced 12.5 Hz apart with HOC excluded, 15 percent of the Channel Percent

Occupancy values have a mean percent-usage of greater than or equal to 1%, or conversely,

that 85 percent of the Channel Percent Occupancy values have a usage less than 1%.

Similar conclusions can be determined for the other channelization cases presented in Figure

22. For this figure, note that typical measured hourly usage values for a given channel may

vary greatly, with occasional hourly periods of unusually high or low usage. The effect of

averaging the hourly usage values into a weekly channel usage value causes the weekly

values to have much less variability than the corresponding hourly values. This effect is

clearly shown by comparing the case of all channels spaced 12.5 kHz apart (HOC excluded)

in Figures 21 and 22.

100

10

1.0

,-

! I j"" eH

.1:, \'"",,-,

~',

\>

" , "

-AI

-,-,- "'~~ ,~~

12.5 kHz

0.01 0.10 1.0 10

Percent of Channel Percent Occupancy values exceeding ordinate

100

Figure 22. Sample graph (reference to Figure 33) ofthe percent channels

exceeding a given percent usage for Channel Percent Occupancy.

41
The cumulative distribution of usage is also presented in one final form. Figure 23 shows

the percent of channels exceeding a given percent usage for the Busiest Usage by Time-ofDay for Each Channel. In this figure, for the case of all channels spaced 12.5 kHz apart

with HOC excluded (weekdays only), 60 percent of the channels have a Busiest Usage by

Time-of-Day greater than 1%, 10 percent of the channels have a usage greater than 7 percent

and 1 percent of the channels have a usage greater than 34%.

Much of the data presented in this report is represented in the form of "mean usage" which

is meant to convey "typical" usage by a channel. However, because the percent usage

statistics are not Gaussian distributed, and because, as shown in Figure 23, there are a few

channels with relatively high usage (20 percent of the channels with greater than 2 percent

usage) but there are far more channels with relatively low usage (80 percent with less than 2

percent usage) the mean is skewed, due to outliers, towards a larger value than what one

might think of as "typical." This is because the overwhelming majority of usage value are

around 1-3% but there are individual values much greater than this that tend to

computationally bias the mean to a higher value. In this case, the median may be more

representative of what is a "typical" channel usage - depending upon how the statistic is

used. This median value can be easily determined by looking at the 50% point along the xaxis of the cumulative distribution graphs and finding the corresponding percent-usage on the

usage plot. In Figure 23, as an example, the median of Busiest Usage by Time-of-Day is 1.3

percent.

100

10

1.0

f h..

: .....,'l""·i

i .•

''''--"" .~.

\. ~-

..... \

. '"

\\

-'0"

•

;channels spaced ,..i.5 Iz apart (HOL.

.New 12.5 kHz channels .

: : :: ,: :: , · ,.:

0.01 0.10 1.0

Percent of channels exceeding ordinate

10 100

Figure 23. Sample graph (reference to Figure 34 ) for percent of channels

exceeding a given percent usage for the Busiest Usage by Time-of-Day

during weekdays only.

42
Note that Figures 21 and 22 are based on the entire week of measurements, while Figure 23

is based on weekday measurements gnlY.iThis was done because the busiest hours occurred

during the weekdays.;'i i" "

Figure 24 shows a representative cumulative distribution graph of the percent of channels

that exceed a given percent time at greater than or equal to a given usage for the entire 8-

day period of the measurements, where time is broken into I-hour segments for which

average usage is determined. In this case, usage refers to Hourly Channel Percent

Occupancy as defined in Section 5.5. Each hour time-slot represents an average of 6.7

minutes of data acquisition in the 162-174 MHz band and 15 minutes of data acquisition for

the 406-420 MHz band. Each line in the graph represents a unique percent-usage (Hourly

Channel Percent Occupancy) as noted in the graph legend. For example, consider the case of

the line that represents the percent usage of 1 percent. Point A (annotated on the 1 percent

usage line) shows that for this case, approximately 33 percent of the channels have 10

percent or more of the I-hour periods in which the usage is 1.0 percent or greater.

Conversely, 67 percent of the channels have less than 10 percent of the I-hour periods in

which the usage is 1.0 percent or greater. Or 67 percent of the channels have 90 percent or

more of the I-hour periods in which the usage is less than 1.0 percent. Another example is

the case of the line that represents the usage being 5 percent. Point B (annotated on the 5

percent usage line) shows that for this case, approximately 20 percent of the channels have 3

percent or more of the I-hour periods in which the usage is 5.0 percent or greater.

Conversely, 80 percent of the channels have less than 3 percent of the I-hour periods in

which the usage is 5.0 percent or greater. Or 80 percent of the channels have 97 percent or

more of the l..,hour periods in which the usage is less than 5.0 percent. Note that discrete

steps occur in the "percent of hourly periods" lines because there are a discrete number of

one-hour time slots over the course of the measurement. Since there were approximately 196

hours of measurement during the course of the 8 days, a single one-hour time slot represents

a "percent of hourly periods" of 0.51%, two hours is 1%, and three hours represents 1.5%

(consistent with the discrete steps seen in Figure 24).

43
"0

C

Q)

>- 100 ~QZE773J7373E7317373E73IG3ss]-+-0.1% -+-1.0% usage usage ..:\.. -. ......, -+-2.5% usage -::: Q) ..... '\. --- -+-5.0% usage S. .,\c......... +_..7.5% usage ~. ,'\ ... -- .. -+-10.0%usage ! ~\" 25.0% usage •..--l!<\j....\.:,•.•.•...."-...............;............... ••...•.......• •.•.•.." "__...'............... ••......••...........•....•.•.•.•. '1-<>-50.0% usage i '~\"-../ · ......__ =:=~~~~s~~a:e rr·····J·i1••~~·.•...•·~r~.:~ ••••.••.~·~),.~.·.·.;.~~.J.~:.:...l.-,;~~ ..l~,?.•~1..~-~2~~.~21.--,;,,~~1_~~~:---~·~.."";···1·

1 ~?=d.~ ~-

; 10 1'1I'.' .7.-(/:.1::~~~j ::.!:.IZ:[J2J2i2,12S::12\~ElSl211····~••·1 'f .~ .../ .............L.:..J..., ~-~ f·············f······· I· ········ .. ········1····················.···············.............................................................. 1

<I>

§

'0

51 0 10 .'----:':-------:!':-----!::----<---!~---!'~--=':--------:!:,------:!:-------:!::-----:!. r!f . 0 10 20 30 40 50 60 70 80 90 100

Percent of channels exceeding ordinate

Figure 24. Sample (reference to Figure 37) cumulative distribution graphs ofthe

percent of channels that exceed a given percent of hours at greater than

or equal to a given usage (Hourly Channel Percent Occupancy).

Table 7 is a representative table showing Percent Band Usage and Average ofBusiest Usage

by Hour expressed in percent usage. Percent Band Usage is determined by computing the

mean of all Hourly Channel Percent Occupancy values for all channels during the

measurement period. Average ofBusiest Usage by Hour is defined in Section 5.5. The table

shows Percent Band Usage over a 24-hour period, as well as between 8 AM to 5 PM, and

Average ofBusiest Usage by Hour over a 24-hour period. The associated values are given

for 5 different detection threshold levels represented both by power in dBm at the antenna

terminal for the particular antenna and field strength in dB V1m at the antenna input.

Ninety-nine percent confidence intervals, the derivation of which is described in

Appendix A, are given for percent usage values determined at the minimum detection

threshold. The mean usage values for Average ofBusiest Usage by Hour are only reported

for the minimum detection threshold, since the minimum threshold is used to determine

which hour of the day is the busiest. It is not valid to use other thresholds to calculate the

44
Average ofBusiest Usage by Hour. Variations of Table 7 (provided in Appendix A) consist

of different frequency groupings and time scenarios.

Table 7. Sample Table Showing Mean Percent Usage and Mean Erlangs for 934 Channels

(Reference to Table A-I)

IAll Days II Mean Detection threshold I

Threshold.(<iBm)

I

-113

I

-100

I

"90

I

-80

I

-70

I .~,.

., .1-' (dBI1V7IIl) 8 21 31 41 51

Timescale Percent Band Usage

Percent Band Usage (24 hours) 1.08±0.0 112 0.63 I 0.5 I 0.27 I 0.21

Average of Busiest Usage by Hour 2.72±0.08 12 Not applicable

Percent Band Usage (8am-5pm) 1.42±0.0212 0.76 I 0.6 I 0.37 I 0.3

Note: Mean Erlangs can be calculated by multiplying the Percent Band Usage for any

threshold by the number of channels. For example, Mean Erlangs for a threshold of -113

dBm is 10.95 (1.08 * 934).

The relationship between the cumulation distributions (Figures 21 and 22) and the values in

Table 7 can be understood better by considering how Figure 21 can be crudely analyzed to

give the data shown in Table 7. Figure 25 shows the principles of this analysis, using the

corresponding data in each figure. The solid black line in Figure 25 (all channels spaced

12.5 kHz apart, HOC excluded) corresponds to the "1.08" mean percent usage in Table 7

(-113 dBm threshold, 24 hours per day usage). Figure 25 illustrates the process of converting

Figure 21 data into an entry in Table 7.

The area under the solid black cumulative distribution line in Figure 25 (see arrow) can be

approximated by a series of rectangular areas. The leftmost of these areas represents the

point on the line that says .09% of all channels have a usage of approximately 100%. The

general approach will be to see what proportion of channels have what values of usage, to

give a total percent usage for the entire band. The following table summarizes the values

used in the rectangular approximations.

1299% confidence level- assuming an average message length ofno greater than 5 seconds.

45
The derived answer of 1.007% compares to the answer in Table 7 of 1.08%, which is a

reasonable accuracy considering the approximations used.

Table 8. Summary of values used in the rectangular approximations of mean percent usage

Percent of channels Mean usage Total usage

min m ax net (% usage) (channels x usage)

0 0.09 0.09 100% 1.000 x 0.09% = 0.090%

0.09 0.2 0.11 60% 0.600 x 0.11% = 0.066%

0.2 0.5 0.3 40% 0.400 x 0.30% = 0.120%

0.5 I 0.5 25% 0.250 x 0.50% = 0.125%

1 2 I 16% 0.150 x 1.00% = 0.150%

2 5 3 7% 0.070 x 3.00% = 0.210%

5 10 5 3% 0.030 x 5.00% = 0.150%

10 22 12 0.8% 0.008 x 12.0% = 0.096%

Total usage = 1.007%

Figure 25. Calculating mean hourly channel usage.

46
5.7 Summary of Processing

The flowcharts in this section summarize the process that was used for obtaining the

following statistics: Busiest Hour ofthe Week for Each Channel, Busiest Usage by Time-ofDay for Each Channel, Average ofBusiest Usage by Hour, Band Occupancy by Time-of-Day,

and Maximum Band Occupancy.

174 MHz

Flowchart for Busiest Hour

ofthe Week for Each Channel ,

All 958 12.5-kHz channels

Note: in the final processing, HOC and weather channels eliminated.

...

162 MHz

Channel X

For Channel X: typically either 240 or 480 Channel Power Values in an Hour are

stored on disk and measured in a specified hour.

For Channel X: Read Channel Power Values in an Hour and compare to a selected

-113 dBm threshold. Each time the channel power value exceeds the threshold, the

channel is considered occupied. The Hourly Channel Percent Occupancy for a

specific hour is computed for a channel by dividing the number oftimes the channel is

occupied in the specified hour by the total number ofChannel Power Values in an

Hour. Example: Tuesday between 3 p.m. and 4 p.m., 7 out of240 values in Channel X

are above the selected -113 dBm threshold, then the Hourly Channel Percent

Occupancy ofChannel X is 3% for that hour and that day.

Search for the Busiest Hour ofthe Week for Each Channel (Channel X in this case)

over all hours of all days by finding the largest value from all ofthe Hourly Channel

Percent Occupancy values for Channel X. The result is a single data point for Channel X

represented in Figures 27 and 39.

47
162 MHz

Flowchart for Busiest Usage by Time-of-Day

and Average ofBusiest Usage by Hour

174 MHz

,I

All 958 12.5-kHz channels

Note: in the final processing, HOC and weather channels eliminated.

Channel X

For Channel X: typically either 240 or 480 Channel Power Values in an Hour are

stored on disk and measured in a specified hour.

For Channel X: Read Channel Power Values in an Hour and compare to a selected -113

dBm threshold. Each time the channel power value exceeds the threshold, the channel is

considered occupied. The Hourly Channel Percent Occupancy for a specific hour is

computed for a channel by dividing the number oftimes the channel is occupied in the

specified hour by the total number ofChannel Power Values in an Hour. Example:

Tuesday between 3 p.m. and 4 p.m., 7 out of240 values in Channel X are above the

selected -113 dBm threshold, then the Hourly Channel Percent Occupancy ofChannel

X is 3% for that hour and that day.

Compute Usage by Time-of-Day for Each Channel during the entire week by summing

the weighted Hourly Channel Percent Occupancy for a given hour using the minimum

threshold. Usage by Time-of-Day for Each Channel is given by

D

L CijkWjk

W" k=!

!] D •

where uij is the Usage by Time-of-Day for Each Channel for the ,-th channel and theJ-th

hour ofthe day, cilrj is the Hourly Channel Percent Occupancy for the ,-th channel, the fth

day ofthe measurement, and theJ-th hour ofthe day, wkj is the weight factor for the the

day ofthe measurement and theJ-th hour, and D is the number of days during the course of

the measurement. The respective hourly values are weighted proportional to the number

ofmeasurements used in computing the hourly values since not all Hourly Channel

Percent Occupancy values contain data based on an equal number ofmeasurements.

Determine the Busiest Usage by Time-of-Day for Each Channel by fmding, for each

channel, the Usage by Time-ol-Day for Each Channel value that is the largest out ofthe 24

values. There is only one Busiest Usage by Time-ol-Day value for each channel.

Compute the Average of Busiest Usage by Hour by averaging, across all channels, the

~alues for Busiest Usage by Time-ol-Day for Each Channel. Example: Channell, Hour 4,

1.2%; Channel 2, Hour 2,18.6%; ....ChanneI958, Hour 24,5.3%. Average of Busiest

Usage by Hour (P) is given by

(~bi) 1=1 P=--N-'

where bi is the Busiest Usage by Time-ol-Day for the i

th channel, and N is the number of

channels. The result is a single data value for the entire band, displayed in Tables A-I, A2, A-5, and A-6 as the "Average ofBusiest Hour."

48
Flowchart for Band Occupancy by Time of

Day and Maximum Band Occupancy

162 MHz 174 MHz

if

All 958 12.5-kHz channels

Note: in the fInal processing, HOC and weather channels eliminated.

+-

Channel X

For Channel X: typically either 240 or 480 Channel Power Values in an Hour are

stored on disk and measured in a specifIed hour.

For Channel X: Read Channel Power Values in an Hour and compare to a selected -113

dBm threshold. Each time the channel power value exceeds the threshold, the channel is

considered occupied. The Hourly Channel Percent Occupancy for a specifIc hour is

computed for a channel by dividing the number oftimes the channel is occupied in the

specifIed hour by the total number ofChannel Power Values in an Hour. Example:

Tuesday between 3 p.m. and 4 p.m., 7 out of240 values in Channel X are above the

selected -113 dBm threshold, then the Hourly Channel Percent Occupancy ofChannel

X is 3% for that hour and that day.

Compute the Hourly Band Usage by taking all ofthe Hourly Channel Percent

Occupancy values in a given hour ofa given day and averaging across all ofthe channels

in the band. Hourly Band Usage (hjlJ for theJoth hour ofthe k}h day is given by

hjtJI"j'~< where Cijk is the Hourly Channel Percent Occupancy for the loth channel, the k}h day ofthe

measurement, and theJoth hour ofthe day, and N is the number of channels. The result of

this processing is displayed in Figures 26, 28, 38, 40, 50, 52, A-I, and A-2.

Compute the Band Occupancy by Time-of-Day by taking the Hourly Band Usage

values for each hour ofthe day and averaging together the values for corresponding

hours ofthe day across all days ofthe measurement. Band Occupancy by Time-of-Day

(d) for theJoth hour ofthe day is given by

d.Jk~lhjkV J M •

where hj! is the Hourly Band Usage for the k}h day ofthe measurement, and theJoth hour

ofthe day, and M is the number of days during the measurement. The result ofthis

processing is displayed in Figures 29, 30, 31, 41, 42, and 43.

The Maximum Band Occupancy is the maximum ofall the Band Occupancy by Timeof-Day values for a day. It is represented by a single data point on Figure 30 (as

annotated).

49
5.8 Measurement Results

Figures 26 through 49 summarize results using the various graphs described in the previous

section. As a quick reference, Tables 9 and 10 provide figure numbers for various plot types.

For statistics that do not provide results for multiple threshold levels, only the minimum

threshold is used, the values of which are listed in Table 11.

50
Table 9. Figure Numbers for Graphs in the 162-174 MHz Band

Hourly Band Usage X X X

Busiest Hour of the Week for X

Each Channel

Band Occupancy by Time-of-Day X X X

% Hourly Channel Percent X

Occupancy Values Exceeding

% Usage

% Channels Exceeding % Usage X

for Channel Percent Occupancy

% Channels Exceeding % Usage X

for Busiest Usage by Time-of-Day

for Each Channel

APD of Channel Power Values X X

% Channels Exceeding a Given % X

of Hours at Greater than or Equal

to a Given % Usage

Multiple Thresholds X X

Mult Channelization Scenarios X X X X X X X

Multiple HOC Scenarios X X

Multiple Time Scenarios X

Including HOC X X X X

Excluding HOC X X X X X X X X X X X

Entire Week X X X X X X

Date and Time of Day X X X X

Time for Any Day X X X

Election Day X

Weekdays X

Weekend Davs X

All Channels X X X X X X X X X X X X X

25-kHz Channelization X X X X X X X

12.5-kHz Channelization X X X X X X X

Figure Number 26 27 28 29 30 31 32 33 34 35 36 37 A-I

51
Table 10. Figure Numbers for Graphs in the 406-420 MHz Band

Hourly Band Usage X X X

Busiest Hour of the Week for X

Each Channel

Band Occupancy by Time-of-Day X X X

% Hourly Channel Percent X

Occupancy Values Exceeding

% Usage

% Channels Exceeding % Usage X

for Channel Percent Occupancy

% Channels Exceeding % Usage X

for Busiest Usage by Time-of-Day

for Each Channel

APD of Channel Power Values X X

% Channels Exceeding a Given % X

of Hours at Greater than or Equal

to a Given % Usage

Multiple Thresholds X X

Mult Channelization Scenarios X X X X X X X

Multiple HOC Scenarios X X

Multiple Time Scenarios X

Including HOC X X X X

Excluding HOC X X X X X X X X X X X

Entire Week X X X X X X

Date and Time of Day X X X X

Time for Any Day X X X

Election Day X

Weekdays X

Weekend Days X

All Channels X X X X X X X X X X X X X

25-kHz Channelization X X X X X X X

l2.5-kHz Channelization X X X X X X X

Figure Number 38 39 40 41 42 43 44 45 46 47 48 49 A-2

52
Table 11. Minimum Detection Threshold Values

;ii;

Frequency Band dBm at antenna terminals I dB IlV1m field strength

162-174 MHz

I

-113

I

8

I 406-420 MHz -117 12

Several of the channel-usage graphs show anomalies that require further explanation (anomaly,

meaning data that does not reflect what is truly happening). As can be seen in Figure A-I in

Appendix A, as well as Figures 26 and 28, there are three different times (at the beginning,

midway, and at the end of the week) in which all of the usage values go to zero. The reason

for this is that, during this time, no data were collected in the bands of interest, and therefore

usage erroneously appears to be zero. This anomaly occurs only in the 162-174 MHz band.

Another anomaly that occurs - but only in the 162-174 MHz band (as seen in Figures A-I,

26, and 28) - can be seen at approximately 10:00 AM on Thursday, in which usage values for

all data plots exceed 2.5 percent usage. Upon examining the usage data in greater detail it was

determined that this was due to an incomplete data set where the data collected was in a small

section of the spectrum that had greater usage than the average. A third anomaly occurs at

midday on Sunday and Monday in which only the data for the minimum detection threshold

exceed 2.5 percent usage. This occurs in the 162-174 MHz band and can be seen in Figures

A-I, 26, and 28. Examining the usage data in greater detail revealed periods of increased noise

that were high enough to raise the statistics for mean usage on the minimum detection

threshold plot but were not high enough to be detected and removed by the processing

techniques described in Section 4.1. This phenomenon also has an impact on the 24-hour plot

shown in Figure 31, in which only the minimum detection threshold plot appear to have this

anomaly. For APD plots, time periods during which this aberrant noise condition occurred

were excluded from analysis. To improve readability of the week-long plots, the latter

anomalies are often cut off by the top of the graphs, since this data is not relevant to the

usage analysis. As shown in Figure A-2 of Appendix A, none of the anomalies occurred in the

406-420 MHz band.

To give some indication of the degree to which assignments have migrated to the 12.5-kHz

channel spacing, several of the graphs show statistical summaries for 3 different channelization

schemes as described in section 2.1. These include the following:

1. all channels spaced 12.5 kHz apart.

2. the old 25-kHz channels (spaced 25 kHz apart).

3. the new 12.5-kHz channels (spaced 25 kHz apart and located halfway between the

old 25-kHz channels).

Statistics for each of the three categories are determined only for the channel frequencies

indicated. However, because ACPR requirements, as specified in Section 2.2, require 25-kHz

channels only to be attenuated in the adjacent 25-kHz channel, there is likely to be significant

53
signal power in the adjacent channel spaced 12.5 kHz away. Therefore, some of the new

12.5-kHz channels are likely to show usage even though the power simply comes from an

adjacent old 25-kHz channel. From the standpoint of percent-usage of all channels spaced

12.5 kHz apart, a channel 12.5 kHz away from the center frequency of a wider bandwidth

transmission in an old 25-kHz channel is considered to be occupied, even though the power

comes from an adjacent channel; however, because the two adjacent channels 12.5 kHz away

from the center frequency of the wider bandwidth transmission will show less power, the mean

for percent usage of all channels spaced 12.5 kHz apart is likely to be slightly low since their

values may, at times, fall below the threshold. On the other hand, statistics for usage of the

new 12.5-kHz channels are likely to show mean-usage values slightly higher than the true

value because the channel is not being used for a transmission as a new 12.5-kHz channel but

is simply showing usage because there is sideband power in the channel from an adjacent old

25-kHz channel.

54
5.8.1 Results for 162-174 MHz Band

2.5

2

F 1.5

'l5

0.5

---All channels spaced 12.5 kHz apart

- -_.- Old 25-kHz channels

----- New 12.5-kHz channels

O'---...L--'-------'------'-------'------'-------'------'-------'----'----'O Tue Wed Thu Mon Tue Wed

Figure 26. Hourly Band Usage (percent oftime and total Erlangs) during the course ofthe

measurements for the 162-174 MHz band (excluding HOes; minimum thresholds).

.'

, .

'''.::' .. "

t

.'

; ....:.... :.. ..: .....................~., ..

..

.

.' +. •

. " . ..

..

,i" .i" ", ,,~ .

•I

. 't.: : "' 4,•••

... '.

.

......:...,;...,:.

.* .. \

t

,

.~

+

..

;. " ...".. ,.,.

"';........

'. +

• +

.'

'. .

++

.'.

+ •

+.

...

164 f-". " """ .. ..' . .

. .

174,----,----,-----r----,----,:--r..----.-.----r----,----;--r-----,

.. . .. . I • .a.. • • .. •

172 r-' ~~.i· .. +. "~, .•..,,,.:: ..;.-~ ,~.~. :.

¥ 170 f- ..

;;§. '.

(;' ::. .. 168 f-..... ... d •••••••.• ••

g ... ~:

' .. :

.. B 166 f-"'" , ,.' •.;~

Tue Wed Thu

Figure 27. Busiest Hour ofthe Weekfor Each Channel in the 162-174 MHz band.

55
, J .'" \

'l .: ". J..": ;in' I :a,Ii\;: ... :'i"I~"" .... ft.! '

.".j...

i!

21- .... ·...

4

3

4.5i--,---,-li-,.-----r---r=c==-====::::I:lI::===:==:::::::==:::::::;l ---All channels spaced 12.5 kHz apart

---.- Old 25-kHz channels

----- New 12.5-kHz channels

1.5

0.5

3.5

F

'0 2 .

5

"#.

.

f

Tue Wed Thu Frl Sat Sun

Days of Week

Figure 28. Hourly Band Usage (percent oftime and total Erlangs) during the course ofthe

measurements for the 162-174 MHz band (including HOes; minimum threshold)Y

13 As previously noted both Figures 26 and 28 have some anomalies that require explanation. There are three different times (at the beginning, midway, and at the end of the week) in which all of the plot values go to

zero. The reason for this is that, during this time, no data were collected in the bands of interest, and therefore

usage erroneously appears to be zero. Another anomaly can be seen at approximately 10:00 AM on Thursday, in

which all data plots exceed 4 percent usage. Upon examining the data in greater detail it was determined that this

was due to an incomplete data set in which the data collected was a small section of the spectrum that had

greater usage than the average. A third anomaly occurs at midday on Sunday and Monday in which only the data

for the minimum threshold exceed 2.5 percent usage. Examining this data in greater detail revealed periods of

increased noise that were high enough to raise the statistics for mean usage on the minimum threshold plot but

were not high enough to be detected and removed by the processing techniques described in Section 4.1. This

phenomenon also has an impact on the 24-hour plot shown in Figure 31, in which only the minimum threshold

plots appear to have this anomaly. To improve readability of the week-long plots, the latter anomalies are cut off

by the top of the graphs, since this data is not relevant to analysis.

56
35

30 gj,

<::

(II

in

25

lI

Q)

20

40

10

15

5

25

-a-Weekdays

-'-'V-- All days

--(~-- Weekend days

. . + . Election day

. .. .. .. J.. . .

4 "Gi'

l

I,

"

"

" .. .. . .. ~... . .. .. ..('1."

: r 1 ; I ,

: , I , /, : I I ·•.. ······ .. ·1· 1'· - .

j •

I ,

I ,

J I j

2

4.5

3.5

\

1

I

I

\ .. ·.. ···1·

f \ :

.......... . ·.. ;;.;;··>f<\,v'>~:k{~···· , :;-'-'&.... .....:v..' ,± ", \

··i.:2;'~:~'¥' ··:",'I'··/·······\··~:':t~i~,:;A··

0.50 5 10 15 20

Hour of the Day

(fl.

.;, 2.5 CI

m::::l

Figure 29. Band Occupancy by Time-of-Day (percent oftime and total Erlangs)

during different 24-hour time scenarios in the 162-174 MHz band

(excluding HOes; minimum threshold).14

14 An anomaly occurs at midday on weekend days in which the data approaches 4 percent usage. Examining this data in greater detail revealed a period of increased noise on Sunday that was high enough to raise the

statistics for mean usage on the minimum threshold plot but were not high enough to be detected and removed by

the processing techniques described in Section 4.1.

57
2.5

2

Ol

E

i=

'01.5

"#.,

Ol

g'

III

:::>

0.5

--All channels spaced 12.5 kHz apart

......... --- Old 25-kHz channels

---- New 12.5-kHz channels

Maximum Band

. Occupancy

o 5 10 15

Hour of the Day

20 25

Figure 30. Band Occupancy by Time-of-Day (percent oftime and total Erlangs)

during the course of 24 hours, independent ofthe date, for different

channelization scenarios in the 162-174 MHz band (excluding HOes;

minimum threshold). 15

15 As discussed earlier, the processed data in Figures 30 and 31 contain measurements on both Specific Location Assignments and Area Assignments. The Maximum Band Occupancy in Figure 30, which inCludes both

types of assignments, is about 1.6 percent at 12 noon. The Maximum Band Occupancy associated with each type

of assignment ("Specific Location" vs "Area") will be different, since Area Assignments mayor may not have

been active during the measurement period within the measurement coverage area. A search of the GMF by OSM

revealed that the number of Specific Location Assignments deemed to be visible to the measurement system is

511, and when the measured data were examined on a channe1-by-channe1 basis for that specific time (12 pm), it

was determined that total number of Erlangs for Specific Location Assignments was 10.98. Therefore, the

Maximum Band Occupancy for Specific Location Assignments was determined to be 2.1 percent.

58
2.5

3i-----;:J=======::!:=======:::r:========'=======:;l -&- Min Threshold: -113 dBm at antenna terminals, 8 dB mlcrovoUslm at antenna Input

Threshold: -110 dBm at antenna terminals, 11 dB microvoltslm at antenna Input

--0-..- Threshold: -100 dBm at antenna terminals. 21 dB microvoltslm at antenna Input 25

--f-Threshold: -90 dBm at antenna terminals. 31 dB mlcrovoltslrn at antenna Input

Threshold: -80 dBm at antenna terminals. 41 dB mlcrovoltslrn at antenna Input

20

21- .. ·····························;····················· ,."" ; ".. , , , , , ; , , -1

i=

'0

1.51--· ·· .. · · ··, ·..· ,.. ··j{l

,

t:::)

0.5Ao-""""~

III

Ol

:ii

15

,

Q)

Ol

m

10 :::)

5

oL-- --'- ---L -'- ...L- ----' 0

o 5 10 15 20 25

Hour of the Day

Figure 31. Band Occupancy by Time-of-Day (percent oftime and total Erlangs)

using different thresholds, independent ofthe date, for all 934 channels

in the 162-174 MHz band (excluding HOes).

59
100

10

1.0

..... ....-..... c.., \

....'t. , \

"'.. \

... \ .. • •

[\\\.

.\

.;

't.

" . • •• ."'"

-All channels spaced 12.5 kHz apart (HOC included)

..' _._.- Old 25 kHz channels (HOC included)

. ---- New 12.5 kHz channels (HOC included)

: -All channels spaced 12.5 kHz apart (HOC excluded)

.,.,. Old 25 kHz channels (HOC excluded)

.. •••• New 12.5 kHz channels (HOC ~,

•

.

•

• 0.01 0.10 1.0 10

Percent of Hourly Channel Percent Occupancy values exceeding ordinate

100

Figure 32. Percent ofHourly Channel Percent Occupancy values exceeding a

given percent usage over the course ofthe measurements for the

162-174 MHz band (minimum threshold).

60
100

10

1.0

,,,--

r. i

! ""., ----:

: \ """1.,

......

-'.

\>

,-,

-AI " iZ~t'~, '\"~ ': -"

'v" 12.5 kHz channels (HOC

0,01 0.10 1.0 10

Percent of Channel Percent Occupancy values exceeding ordinate

100

Figure 33. Percent of channels exceeding a given percent usage for Channel

Percent Occupancy over the course ofthe measurements for the

162-174 MHz band (minimum threshold).

61
100

10

1.0

",,",.

L l,.,., I...".;

L~ "\ '....-

\. , \ •....

'\ \ . \.

.... ~::\

••

12.5 IL af'a,

1-, C'" '\' (HOC •

12.5

•

.., . ., ••

: •

.

0.01 0.10 1.0

Percent of channels exceeding ordinate

10 100

Figure 34. Percent of channels exceeding a given percent usage for the Busiest

Usage by Time-oi-Day for Each Channel during weekdays only in the

162-174 MHz band (minimum threshold).

62
90

80

70

60 :g

.l!l

50

<.> 'E 40 CD

S

.c:

0, 30 c:

l!!

1;;

'0

20 G)

iI

10

-50

-30 ri!,--,---..----,----,---.--;:::==::::::rA::II=Ch=an=ne=ISIsp=aC=e=d1L2::;_5=kH=Za=p=art=rl

-.-.-.. Old 25-kHz channels

-40 -.;-_-~-",;;:-- ---- New 12_5-kHzchannels

- J --....~·r·\ """,,"" System Noise 'I .... 'I,I -\ \_.~----------------,--------------------------,----------------;--------------------- __ , ;. ; -j

----:\.<--, \ --'\-\'-!\.~----' ----------------,-- ----;--------------- ----------------;----------i-- ------::I

-- --"\\ \ ----i-----------\-'~i--.-------.-------------------, .. ------.----;----------------------·----.----------;-----------i------------------::I

.-",,-,~,- -'. -- ;.--_-- ------ -.---- _-- i .-- .. -- -- --;----- -- ---. ------ --.----- --------,-------. ---;---- _____________-1

i

\ \ ----'\~...~,:\\ ..."~-------.-------------- -,----.----.--;---------------------,----------------,----------.•. --------- --::J

.::;!T"L::::c::::;?:-;;;;;;;::;:;;.~"';:_:".~."~.?~,,,.~,,.~'''~,,.;;;;;;;;;;;~;;;:,:::j

M70 c:

'~ -80 OJ

c:

c:

2

!ii -90

'\\i

.... -100

a.

E -60

CD

S

-130 .........................1 .. " ; . -10

001 .01 _10 1n ~o 10

Percent exceeding ordinate

20 30 36 50

Figure 35. APDs ofChannel Power Values for channels in the 162-174 MHz

band - entire week, independent of date or time for different

channelization (excluding HOes; minimum threshold).

63
-30

-40

-50

E -60

aJ

B

-70

c:

'§

2 -80 co

c:

1i -90

1ii i -100

a.

-110

-120

-130

....~--- I 1·-

'~

~\

'\

'~

.~

'"

............

"

90

80

70

60

'"15 50

u

'E 40 aJ

B

30 c:

'0

20 "ij)

u:

10

10

.001 01 .10 1D ~O 10

Percent exceeding ordinate

20 30 36 50

Figure 36. APDs of Channel Power Values for all channels spaced 12.5 kHz apart

in the 162-174 MHz band for the busiest hour during the entire week

independently for each frequency for different HOC scenarios

(minimum threshold).

64
80 90 100

...... . ...-...-... .... j...

................;

.........•.;.. . ..

30 40 50 60 70

Percent of channels exceeding ordinate

20

.......... .

................;. .....

-------

....-----~- -.-....----.--...:.---... -.--...---.,: ....... .. . .. ;.: . : ,:" .

10

-I-- 0.1 % usage •.."' "" , , , , , , 1-1--1.0% usage

'4c.. , ,'"- ,.................... .., , , ,. ..I -I-- 2.5% usage

.. ~"" , , ; , , ; 1-I-- 5.0% usage

-I--7.5% usage , "-""., , "' """'..""" , ·· ..·· ··' 1-1--10.0% usage

25.0% usage ···~............I---B-- 50.0% usage

---B--75.0% usage ..

---B-- 90% usage

...... ... ,;"

..............;.

.................~.

1:J 100 5i

1:J

C

<J)

'(i;

(I)

1:J

(I)

10

c:

(I)

0-

01

<J)

C

1(Jl "8 1.0 'c

8

§

'0

c:

(I)

l::!

(I) a. 0.10 L-__L-_--'__--'-__--'-__----'--__--L__-L__-L__---l-_------l

o

Figure 37. Cumulative distribution ofthe percent of channels that exceed a given

percent of hours at greater than or equal to a given Hourly Channel

Percent Occupancy (designated by legend) for all channels in the

162-174 MHz band (excluding HOCs; minimum threshold, entire

week).16

16 Discrete steps in the "percent of hourly periods" occur because there are a discrete number of one-hour time

slots over the course of the measurement. Since there were approximately 196 hours of measurement during the

course of the 8 days, a single one-hour time slot represents a "percent of hourly periods" of 0.5 I %, two hours

represents I %, and three hours represents 1.5% (consistent with the discrete steps seen in the figure above).

65
5.8.2 Results for 406-420 MHz Band

7

6

5

0>

E

1= 4 '5

"$.

.;,.

m3 :::>

2

C==T===--:r:===2===7===7===~=======:=::=::=:r:=:===;] --- 80 All channels spaced 12.5 kHz apart

- _._- Old 25-kHz channels

L..- N_e_w_ 1.:;!.:.:'i..:-_k_

H_z .c:.':''''.'.'.Il_e_1s_ .

0>

10 i

:::>

o '--__......J. --'-- ---' -'-- ---' ...l... --''-- --'-- ---' 0

Tue Wed Thu Frl Sat Sun

Days of Week

Mon Tue Wed

Figure 38. Hourly Band Usage (percent oftime and total Erlangs) during the course ofthe

measurements for the 406-420 MHz band (excluding HOes; minimum threshold).

420 ::.r .0 '. , 'i .. ,

· : ;. :: r··: "

i :' • . 418 o··~ -.; . : ;

...... .;+ .. t .' o·

?"! . . . .. . . . . .0 ..' .. 416 . ' , ..: . -... , , . N , " . , . :c .... to ••

'" .:. : '0 ,......... .' .0

2§. ... : .. "

· -+ • . .: ,

i:;' 414 c:: '... . 0: ° ". . ! , ; ... o. 0> :"..... - '"

c- ·, ....+:+ :. '~ 0

0, . " f : (j) 412 r" : ~'+O ... ,.: ... .... ,,", .. , .

c:: , 0" .; ..., .c::

Iii : ;. -. . ~'. : . ::::0 u , .. ..... i o.

410

· : .... . · •.,··i.. . . '. . " .' . ·.. 0,. . :, : ° .' 0 .. . ! 408 ". }. ~: ..-. ... ,

"'t:.... ..... . , . . '. , .- . . '. . '. ..' .•. .

· 406 '0

Tue Wed Thu Fri Sat Sun Mon Tue Wed

DayS of Week

Figure 39. Busiest Hour ofthe Weekfor Each Channel in the 406-420 MHz band.

66
8

7

6 _.

Q)

E 5 F

'5

4 .;,

t:J)

mV>

:;:)

3

2

---All channels spaced 12.5 kHz apart 90

_._._.- Old 25-kHz channels 1=

----- New 12.5-kHz channels g. 80

-'"

0.0

N 70

C>.

60 :

0>

lij "" 50 -5

40 .§

.2:-

8

30 '"

20 Io

10 m::::>

o '---__--'- ---l'--- -'- -'- --' -'- -'-- ---l --' 0

Tue Wed Thu Fri Sat Sun

Days afWeek

Man Tue Wed

Figure 40. Hourly Band Usage (percent oftime and total Erlangs) during the course ofthe

measurements for the 406-420 MHz band (including HOes; minimum threshold).

67
--s-Weekdays

4.5 - -v- - All days 50

- ~2> - - Weekend days

+ ... Election day

4 45

40

3.5 III

<I) Ol

E c:

01

F 35 jjj

'0 3 (ii

0 '0 , fo-

<I) 30 ,;, Cl

01 Ol

2.5 01

III

:::l

25

2

20

1.

15

1

0 5 10 15 20 25

Hour oflhe Day

Figure 41. Band Occupancy by Time-af-Day during different 24-hour time

scenarios in the 406--420 MHz band (excluding HOes; minimum

threshold).

68
4 .

3.5

t='0 3

2.5 OJ

l:l

::> 2

1::

m

0-

m

N

50 ::c

""<0

N.....

"C

2l 40 [

II>

II>

Q)

<::

<::

m.r:.

u

30

6 20 lSl

10 ,

::>

i----,-----""""!-----;:===========:::::;l60 --All channels spaced 12.5 kHz apart

----- Old 25-kHz channels

----- New 12.5-kHz channels

5····

.. " . 4.5

o'-- -'- -'-- -.J. ....J- ---' 0

o 5 10 15 20 25

Hour of the Day

Figure 42. Band Occupancy by Time-af-Day (percent of time and total Erlangs)

during the course of 24 hours, independent of the date, for different

channelization scenarios in the 406-420 MHz band (excluding HOes;

minimum threshold).

69
3

L ;:::c========:::r::::========:r=========r========::;J40

3.5 ---a--- Min Threshold: -117 dBm at antenna terminals. 12 dB mlcrovottslm at antenna input

Threshold: -114 dBm at antenna terminals. 15 dB mlcrovoltslm at antenna input

---.3-- Threshold: -100 dBm at antenna terminals. 29 dB microvottstm at antenna Input

--+-- Threshold: -90 dBm at antenna terminals. 39 dB microvoltstm at antenna Input 35

---+-.-. Threshold: -80 dBm at antenna terminals, 49 dB mlcrovolts/m at antenna Input

III

Cl

c:

Ol

25 in

(ii

,

20 8,

Ol

III

:::l

30

15

10

2f-· ·..· ·..···· c /

2.5f-····...... ·.... ·......·........·..,· ..·.... ·..·......··/

l=

'0

';F.

,

Q)

Cl

:::l

m

0.5 L.- -L -'--- ---'- -'- --'

o 5 10 15 20 25

Hour of the Day

Figure 43. Band Occupancy by Time-af-Day (percent of time and total Erlangs)

using different thresholds, independent ofthe date, for all1113 channels

in the 406-460 MHz band (excluding HOes).

70
10

\'

1.0 r2@g§~~~~~? .1?YfJ,,11fX:NJ·IlrU8 All channels spaced 12.5 kHz apart (HOC included) I.....;....•... ;...:...;..:..;.,.:..••......\'...~~l.:.... :.:.. :';.-j

-,-,- Old 25 kHz channels (HOC included) •

... ---·New12.5kHzchannels(HOCincluded)

-All channels spaced 12.5 kHz apart (HOC excluded) \. \ ...,.,. Old 25 kHz channels (HOC excluded) I....·;··.. ;...; ii··;·;·;·;····· '.; .\".;,~~..; :., H

•••• New 12.5 kHz channels (HOC excluded) '-\\~

O. 1£0'0=--:-1--'--'-~~0"-!.0:-:-1-'--~~'='0.c:-1 0::---'-~'-'-''-'-':''1.-':-0--'---'-'~-'-':''::1 0'---'-~'-'L."'--'-':1-':'00

Percent of Hourly Channel Percent Occupancy values exceeding ordinate

Figure 44. Percent ofHourly Channel Percent Occupancy values exceeding a

given percent usage over the course ofthe measurements for the

406-420 MHz band (minimum threshold).

71
100

0,10 1.0 10 100

Percent of channels exceeding ordinate

0,01

-'.

.-...~

'-'~" \

.\

~,

: .\ \ .

\,\\\

,~ ..... ul'u, '\'

_....... 1-,-, \ ,~ \ i ." ~,

'~

•

. •

.

•• , ;; :i \'

1.0

10

0·1£001

Figure 45. Percent of channels exceeding a given percent usage for Channel

Percent Occupancy over the course ofthe measurements for the

406-420 MHz band (minimum threshold).

72
100

0.10 1.0 10 100

Percent of channels exceeding ordinate

0.01

-,,;

...... -~

'-i•.

._--, ~.,..

'.

\ \

\ \\

.~ \ 'i

.......... ,space( (Hz apart (HOC .... 1-,

'~'7'~ , \ ~.5 kH •cllar s

• •

••• \

1.0

0·1£001

10

<II

Cl

01

Ul

::J

J

Figure 46. Percent of channels exceeding a given percent usage for the Busiest

Usage by Time-of-Day for Each Channel during weekdays only in the

406-420 MHz band (minimum threshold).

73
-30

-40

-50

E -60

al

B

-70 c

'~

-80 01

c

c

2

ai -90

OJ

iii -100

c..

-110

-120

-130

1\ All channels spaced 12.5 kHz apart

_.-.-'. Old 25-kHz channels

"'

~\ - - - - New 12.5-kHz channels

".".""" System Noise

.. ,~~-

.. \.;

'''' .....

\,\ ,......

\ \ \.

"\ \.

\. ..'

\'\ '\

\ ..... _\.\

i

90

80

70

:€'

III

60 '8

e

u

50 'E

al

B

.c 40 15l

c

30

iI

20

10

.001 .01 .10 10 5.0 10

Percent exceeding ordinate

20 30 36 50

Figure 47. APDs of Channel Power Values for channels in the 406-420 MHz

band - entire week, independent of date or time for different

channelization (excluding HOes; minimum threshold).

74
-30

-40

-50

E -80

en

"* -70 c

'~

-80 OJ

c

!

lij -90

(;j

-100

a.

-110

-120

-130

"l. I

1=

'\.

"

".~~

-\

\~ ._\

"\"-

90

80

70

:€

1! 80 C5

u

50 'E

en

.s;:

40 OJ

c

1i)

30

u::

20

10

o

001 .01 .10 1~ ~O 10

Percent exceeding ordinate

20 30 38 50

Figure 48. APDs of Channel Power Values for all channels spaced 12.5 kHz apart

in the 40~20 MHz band for the busiest hour during the entire week

independently for each frequency for different HOC scenarios

(minimum threshold).

75
·.~ ....... -+-- 0.1 % usage

-- . ...... -+--1.0% usage

···.·i" .......... -+-- 2.5% usage

..."- -......... -+-- 5.0% usage

'""'-- ---........ --+--7.5% usage

" ........ -+--10.0% usage"

...

25.0% usage

-e-- 50.0% usage

-e-- 75.0% usage ••

!L "!it- 'lL -e-- 90% usage ~. ..... -... -.. '\ 'l; \ 'l; 'l; .~.......

--~ ... -.; -.... "-- ,~ 11!~

.......1~1\ '-

"

D J.....

10 20 30 40 50 60 70

Percent of channels exceeding ordinate

80 90 100

Figure 49. Cumulative distribution ofthe percent of channels that exceed a given

percent ofhours at greater than or equal to a given Hourly Channel

Percent Occupancy (designated by legend) for all channels in the

406-420 MHz band (excluding HOCs; minimum threshold).

76
6 SUMMARY OF MEASUREMENT RESULTS

The measured data presented in this report characterizes channel usage of LMR systems

operating in the 162-174 and 406-420 MHz frequency bands in the Washington, D.C., area.

The analysis of the data is used to present the percent usage for a typical or representative

channel during an 8-day measurement period using sampling procedures for the measurements.

A summary of the measurement results for channel usage for each band is given in the

following sections along with a description of the diurnal patterns. There are several limitations

to the measurements, however, that need to be considered, as follows.

Because the measurement system coverage area for mobile and portable stations is not as

extensive as for base stations and repeaters, and because terrain and structural obstruction may

prevent adequate reception of these mobile radio signals by the measurement system, the usage

statistics may not fully reflect the usage within the bands. However, for each transmission by a

portable or mobile station there is usually a corresponding transmission response from a base

station or repeater that reflects that usage; therefore, for the worst case, where no portable and

mobile station transmissions are detected, the measured usage would need to be doubled

(assuming no talk-around). In reality, the usage statistics lie somewhere in between these two

extremes, since some of the signals from mobile and portable stations were detected by the

measurement system. It is also possible that the measurement system coverage area for base

stations is extensive enough to detect frequency reuse, thus reflecting a higher than expected

average usage.

There are some assignments that, while included in the overall statistical analysis, in reality are

not used for LMR transmissions or cannot be detected. Some cannot be detected for the

reasons described in the previous paragraph. The received power from some assignments may

be below the measurement system sensitivity. Some channels may be assigned for "listening

only" in the sense that they infrequently carry traffic but are monitored continually for

emergency transmissions. In every case, the result is that the usage statistics may show usage

less than what would be expected if the analysis were performed only on channels that are

reserved for transmission and can be detected within the measurement receiver coverage.

Furthermore, any 12.5-kHz channel that has a wideband assignment adjacent to it cannot

generally be used within the measurement system coverage area, and therefore would not show

any activity.

Only 2 out of 36 hydrology channels in the 162-174 MHz band exceeded 80 percent usage and

therefore were excluded from analysis - when HOCs were excluded (see Section 5.4). None of

the 12 hydrology channels in the 406-420 MHz band exceeded the 80 percent usage level and

therefore, none were excluded from analysis. This means that the hydrology channels with less

than 80 percent usage (some with very little, if any, usage) were included in the overall LMR

occupancy statistics. Upon closer examination, it was determined that the non-HOC hydrology

channels in the 162-174 MHz band had a mean usage of 3.7% and the non-HOC hydrology

channels in the 406-420 MHz band had a mean usage of 5.1%. Because the non-HOC

77
hydrology channels are few in number and the mean usage values are only slightly above the

overall LMR band usage, they had little effect upon skewing the results upward.

While every effort was made to minimize the effects of noise, as described in Section 4.1,

there were occasional periods when impulsive noise raised the power in the entire band enough

for individual channels to exceed the detection threshold but not high enough to be identified

as corrupted data and discarded from the analysis. It is difficult to determine precisely how

often this occurred but it may have occurred enough to skew the mean usage values somewhat

towards higher than expected usage values.

Much of the data presented in this report is represented in the form of "mean usage" which is

meant to convey "typical" usage by a channel. However, because the percent usage statistics are

not Gaussian distributed, and because, as shown in Figure 34, there are a few channels with

relatively high usage (20 percent of the channels with greater than 2 percent usage) but far

more channels with relatively low usage (80 percent with less than 2 percent usage) the mean

is skewed, due to outliers, towards a larger value than what one might think of as "typical."

This is because the overwhelming majority of usage values are around 1-3% but there are

individual values much greater than this that tend to computationally bias the mean to a higher

value. In this case, the median may be more representative of what is a "typical" channel usage

and can be extracted from the cumulative distribution plots as described in Section 5.6.

Because most of the channels in these bands are statically assigned to networks or individual

users, as opposed to dynamically assigned as is the case with trunked systems (see Definitions),

many of these channels are reserved for high priority usage in which communication must be

available at all times for a limited number of users. It should also be noted that agencies may

have channel usage that deviates from these values - either to a greater or lesser extent.

Likewise, none of these measurements were made during a major emergency that might have

greatly increased the use of radio channels.

The channel occupancy measurements in this report provide a measure of the level of

communications traffic in the 162-174 MHz and 406-420 MHz LMR bands. The results can

be used for specifying the overall performance objectives of a hypothetical communications

system using a different technology (e.g., trunking). By designing the hypothetical system to

provide the same overall communications capability as the existing LMR systems, the existing

and hypothetical systems could then be compared to examine relative total spectrum usage

(number of channels required for each system).

The intent of the measurements was not to examine details of performance and use for the

characterization of individual channels. This individual channel information, as well as more

extensive measurements, may be required for a detailed engineering design for a next

generation system.

78
6.1 Overall Results

Hourly Band Usage within the measurement system coverage area varies between 0.3-3.8%

(Figures 26 and 38) for the two measured bands, but show the busiest hours to be between

7 AM and 5 PM, with the minimum usage near midnight. Results also show that the newly

created 12.5-kHz channels are not yet used as much as the old 25-kHz channels. Note that

these are average statistics, and usage for individual channels and agencies may deviate

significantly (higher or lower) from the overall band usage.

6.1.1 Results for 162-174 MHz Band

For a mean detection threshold of -113 dBm, in the 162-174 MHz band (HOCs excluded),

Band Occupancy by Time-of-Day within the measurement system coverage area is between

0.6-1.6% for all channels spaced 12.5 kHz apart, 0.9-2.2% for the old 25-kHz channels, and

0.2-1.2% for the new 12.5-kHz channels (see Figure 30). The highest value of the Band

Occupancy by Time-of-Day represents the Maximum Band Occupancy, which is 1.6% for all

channels spaced 12.5 kHz apart and includes both Specific Location and Area frequency

assignments. When the Maximum Band Occupancy for channels spaced 12.5 kHz apart is

calculated based on only the Specific Location assignments, the value is 2.1 percent.

The Band Occupancy by Time-of-Day for conventional LMR systems can be compared to

allowable call-blockage (typically referred to as Grade of Service) as recommended in the Final

Report of the PSWAC. In that report the committee recommends that blockage not exceed "one

call for service per one hundred attempts during the average busy hour." That translates to no

more than 1 percent usage for multi-user conventional systems where channels are assigned

statically. Since the systems measured in the 162-174 MHz band are conventional systems, the

measured usage during the busiest hour of 1.6 percent is relatively consistent with the

recommendations by the PSWAC. [9]

For a mean detection threshold of -113 dBm, the overall Percent Band Usage for the

162-174 MHz band (HOCs excluded) during weekdays is 1.11% over a 24-hour period, 1.53%

between 8 AM and 5 PM, and 3.14% for the Average ofBusiest Usage by Hour (see Table A2). For Busiest Usage by Time-of-Day, 60% of the channels exceed a usage of 1%, while 10%

of the channels exceed 7%, and 1% of the channels exceed 34% (see Figure 34).

6.1.2 Results for 406-420 MHz Band

For a mean detection threshold of -117 dBm, in the 406-420 MHz band (HOCs excluded),

Band Occupancy by Time-of-Day within the measurement system coverage area varies between

1.3-2.7% for all channels spaced 12.5 kHz apart, 2.2-4.1% for the old 25-kHz channels, and

0.4-1.5% for the new 12.5-kHz channels (see Figure 42).

79
For a mean threshold level of -117 dBm, overall Percent Band Usage for the 406-420 MHz

band during weekdays is 2.08% over a 24-hour period, 2.67% between 8 AM and 5 PM, and

4.29% for the Average ofBusiest Usage by Hour (see Table A-6). For Busiest Usage by Timeof-Day, 44% of the channels have a usage that exceeds 1%, while 10% of the channels exceed

13%, and 1% of the channels exceed 60% (see Figure 46).

6.2 Diurnal Patterns for Both Bands

Each of the two bands show about the same diurnal pattern of usage, irrespective of the

whether they were measured for all days, weekdays, weekends, or Election Day (see Figures 29

and 41). However, there are slight variations between the bands. In the 162-174 MHz band, the

highest usage occurs during the weekdays, exceeding the other time scenarios by about 1%.

The other time scenarios show about the same usage except for about a 0.5% less usage in the

midday for Election Day. In the 406-420 MHz band, the usage is about the same for all of the

time scenarios, except for about a 1% less usage on the weekend mornings, and about a 1%

greater usage on the afternoon of Election Day.

For both bands, the times and dates for Busiest Hour of the Week for Each Channel (see

Definitions) are distributed fairly evenly over time-of-day and day-of-week, with the exception

that busiest hours are broadly grouped more in the daytime hours (see Figures 27 and 39).

There are a few occurrences where blocks of adjacent frequencies appear to have the busiest

hour all at the same time. However, such occurrences are not typicaL Whenever large numbers

of adjacent frequencies appear to become busy at the same time, there is a possibility that the

measurements were being affected by broadband RF energy, radiated intentionally or

accidentally.

80
7 ACKNOWLEDGMENTS

This project required technical contributions by various individuals at the Institute for

Telecommunication Sciences. The authors recognize Dr. William Kissick for his vision and

leadership, Brent Bedford for his technical and theoretical support, as well as his leadership and

skills at making the measurements, Iris Tobias for her support and help with the measurements,

Yeh Lo for his work on the preselectors, as well as other system development, Rick Statz and

Steve Engelking for software development, and Margaret Luebs for editorial review.

The authors also wish to recognize Ed Drocella, Robert Sole, Bernard Joiner, Gary Patrick,

Kim Cai, Yang Wang, and Dave Anderson from OSM for their support.

8 REFERENCES

[1] W.A. Kissick, Ed., "The temporal and spectral characteristics of ultrawideband signals,"

Appendix A, NTIA Report 01-383, Jan. 2001, Available:

<http://www.its.bldrdoc.gov/pub/ntia-rpt/01-383/>.

[2] G. Patrick, C. Hoffman, R.J. Matheson, F. Najmy, and R. Wilson, "Federal land mobile

operations in the 162-174 MHz band in the Washington, D.C. area, Phase 1: Study of agency

operations," NTIA Report 06-440, 2006.

[3] Manual ofregulations and procedures for Federal radio frequency management, May 2003

Edition, September 2005 Revision (NTIA Manual), Sections 4.3 and 5.3. Available:

<http://www.ntia.doc.gov/osmhome/redbook/redbook.html>.

[4] NTIA Manual, Sections 5.3.5.1 and 5.3.5.2.

[5] TIA/EIA-I02.CAAA, Digital C4FMICQPSK Transceiver Measurement Methods.

[6] TIA/EIA-603, Land Mobile FM or PM Communications Equipment Measurement and

Performance Standards.

[7] A.V. Oppenheim, and R.W. Schafer, Discrete-time Signal Processing, 2nd ed., Upper Saddle

River, NJ: Prentice-Hall Inc., 1998, pp. 465-478.

[8] F.H. Sanders, B.J. Ramsey, and V.S. Lawrence, "Broadband spectrum survey at San Diego,

California," Appendix D, NTIA Report 97-334, Dec. 1996, Available:

<http://www.its.bldrdoc.gov/pub/surv_sdg/>.

[9] Public Safety Wireless Advisory Committee (PSWAC) Report, Spectrum Requirements

Subcommittee (SRSC) Final Report, Volume 2, Appendix D, Page 76, Sept. 1996.

81
I

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I

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APPENDIX A: SUPPLEMENTAL MEASUREMENT RESULTS

This appendix provides additional results. The first section shows, for the purpose of discussing

anomalies, usage data for each one-hour block during the course of the measurements. The

remaining two sections provide mean usage within the receiver's spatial coverage for the two

frequency bands.

A.I Usage for Each One-hour Block During the Course ofthe Measurements

2

4

6

12 Ul

CI

t::

«l

'C

10

, 6 CI)

g>

Ul

:::>

Fri Sat Sun Mon Tue Wed

Days of Week

Thu

14

-a-- Min Threshold: ·113 dBm at antenna terminals, BdB mlcrovottslln at antenna Input 16

----'V- Threshold: ·100 dBm at antenna terminals, 21 dB mlcrovoUsim at antenna Input

--e- Threshold: ·90 dBm at antenna terminals, 31 dB mlcrovoUsim at antenna Input

-+- Threshold: ·60 dBm at antenna terminals, 41 dB mlcrovottslm at antenna Input 16

Threshold: -70 dBm at antenna terminals. 51 dB mlcrovoRsim at antenna Input

t......._......J.--....J.--.......J.--\\lt-'---.........l.-·-.........l.--.........l.----'--Ilf---'O

2

1.8

1.6

1.4

1.2

F

'5

'#. 1 .

CI)

CI

«l !S 0.8

0.6

0.4

0.2

0

Tue Wed

Figure A-I. Hourly Band Usage (percent oftime and total Erlangs) during the

course ofthe measurements for all 934 channels in the

162-174 MHz band (excluding HOes).

A-I
4.5 ...... c......•• 1 --e-- Min Threshold: -117 dBm at antenna terminals. 12 dB microvollstm at antenna InpUl

--v-- Threshold: -100 dBm at antenna terminals. 29 dB mlcrovollstm at antenna Input

--B- Threshold: -90 dBm at antenna terminals. 39 dB microvoRstm at antenna Input

--t- Threshold: -80 dBm al antenna terminals. 49 dB mlcrovoRstm at antenna Input

41-········ ··;··········1 ---+-- Threshold: -70 dBm at antenna terminals. 59 dB mlcrovoRs/m at antenna Input

50

45

3.5

3

F

2.5 ...

2 :;)

1.5

0.5

40 ......; -1

35

ac:

30 in'"

25

8.

20 :3'"

15

10

5

OL----l L...-__-'-__--'- L-__-'--__-'-__---'__---IO

Tue Wed Fri Sat Sun

Days of Week

Tue Wed

Figure A-2. Hourly Band Usage (percent oftime and total Erlangs) during the

course ofthe measurements for all 1113 channels in the

406-420 MHz band (excluding HOes).

A-2
A.2 Percent Band Usage for the 162-174 MHz Band

Tables A-I through A-4 contain the Percent Band Usage data for the 162-174 MHz band for

the entire week, weekdays only, weekends only and Election Day only. As described in greater

detail in Section 5.6, the data is presented in terms of a 24 hour period and a period of 8 AM

to 5 PM for each table for that measurement time. Note that for the entire week and weekdays

only tables, data is included for the Average ofBusiest Usage by Hour. That information is not

relevant to the weekend only and Election Day tables and is not included for those

measurement times since the busiest times happen during the weekdays.

Table A-I. Percent Band Usage and Average ofBusiest Usage by Hour During the Entire

Week for All 934 Channels in the 162-174 MHz Band (Excluding HOCs)

All Days Mean Detection Threshold

......1

1 .1.i(<ll3n1) -80

.......1·

• 1 .,. (dnJ.l~/l1l)i> ..•.. S 21 3ir 41 51

Timescale Percent Band Usage

Percent Band Usage (24 hours) 1.0S±0.0 117 0.63 0.5 0.27 0.21

Average of Busiest Usage by Hour 2.72±0.OSI7 Not applicable

Percent Band Usage (8am-5pm) 1.42±0.0217 0.76 0.6 0.37 0.3

Note: Erlangs can be calculated by multiplying the Percent Band Usage for any threshold by the number of

channels. For example, Mean Erlangs for a threshold of -113 dBm is 10.09 «LOS / 100) * 934).

1799% confidence level - assuming an average message length of no greater than 5 seconds.

A-3
Table A-2. Percent Band Usage and Average ofBusiest Usage by Hour During Weekdays Only

for All 934 Channels in the 162-174 MHz Band (Excluding HOCs)

Weekdays Only Mean Detection Threshold

Threshold (dBm) -100 -90 -80 -70

Threshold·(dBllVIm) 8 21 31 41 51

Timescale Percent Band Usage

Percent Band Usage (24 hours) 1.11±0.0118 0.63 0.52 0.29 0.22

Average of Busiest Usage by Hour 3.l4±0.1018 Not applicable

Percent Band Usage (8am-5pm) 1.53±0.0218 0.79 0.66 0.4 0.32

Note: Erlangs can be calculated by multiplying the Percent Band Usage for any threshold by the number of

channels. For example, Mean Erlangs for a threshold of -113 dBm is 10.37 «1.11 / 100) * 934).

1899% confidence level - assuming an average message length of no greater than 5 seconds.

A-4
Table A-3. Percent Band Usage During Weekend Days for All 934 Channels in the

162-174 MHz Band (Excluding HOCs)

Weekend Days Mean Detection Threshold

Threshold (dEm) -1 -100 -90 -80 -70

Threshold (dB,.(\Tlm) 8 21 31 41 51

Time Scale Percent Band Usage

Percent Band Usage (24 hrs) 1.16±0.02 19 0.59 0.49 0.2 0.16

Percent Band Usage (8am-5pm) 1.62±0.04 19 0.64 0.53 0.24 0.2

Note: Erlangs can be calculated by multiplying the Percent Band Usage for any threshold by the number of

channels. For example, Mean Erlangs for a threshold of -113 dBm is 10.83 ((1.16 / 100) * 934).

Table A-4. Percent Band Usage During Election Day for All 934 Channels in the 162-174 MHz

Band (Excluding HOCs)

IElection Day II Mean Detection Threshold I ~, "1 (dBm) 13

. 1.J dtl/l vim

Percent Band Usage (24 hours) 0.90±0.02 19 0.56 0.45 0.25 0.22

Percent Band Usage(8am-5pm) 1.1 0±0.04 19 0.72 0.62 0.37 0.33

Note: Erlangs can be calculated by multiplying the Percent Band Usage for any threshold by the number of

channels. For example, Mean Erlangs for a threshold of -113 dBm is 8.41 ((0.9 / 100) * 934).

1999% confidence level - assuming an average message length of no greater than 5 seconds.

A-5
A.3 Percent Band Usage for the 406-420 MHz Band

Tables A-5 through A-8 contain the Percent Band Usage data for the 406-420 MHz band for the

entire week, weekdays only, weekends only and Election Day only. As described in greater detail

in Section 5.6, the data is presented in terms of a 24 hour period and a period of 8 AM to 5 PM

for each table for that measurement time. Note that for the entire week and weekdays only tables,

data is included for the Average of Busiest Usage by Hour. That information is not relevant to

the weekend only and Election Day tables and is not included for those measurement times since

the busiest times happen during the weekdays.

Table A-5. Percent Band Usage and Average ofBusiest Usage by Hour During the Entire Week

for All 1113 Channels in the 406-420 MHz Band (Excluding HOCs)

All Days

c c c

~, ".-

, c c / c c

Mean Detection Threshold

~, .'. . .

I .

Timescale

Percent Band Usage (24 hours)

12

2,00±0,0120

29

1.3

39

Percent Usage

1.1

49

0.84

59

0.6

Average of Busiest Usage by Hour 3.79±0.0420 Not applicable

Percent Band Usage (8am-5pm) 2.55±0.0 120 1.6 1.41 1.04 0.75

Note: Erlangs can be calculated by multiplying the Percent Band Usage for any threshold by the number of

channels. For example, Mean Erlangs for a threshold of -113 dBm is 22.26 ((2.0 / 100) * 1113).

2°99% confidence level - assuming an average message length of no greater than 5 seconds.

A-6
Table A-6. Percent Band Usage and Average ofBusiest Usage by Hour During Weekdays for

All 1113 Channels in the 406--420 MHz Band (Excluding HOCs)

,

Weekdays Only Mean Detection Threshold

Threshold (dBII1) -100 -90 -80 "70 ,

Threshold,.,(dB#VItn.) 12 29 39 .49 59

Timescale Percent Usage

Percent Band Usage (24 hours) 2.08±0.01 21 1.3 1.14 0.89 0.63

Average of Busiest Usage by Hour 4.29±0.05 21 Not applicable

Percent Band Usage (8arn-5prn) 2.67±0.0 1

21 1.7 1.49 1.1 0.79

Note: Erlangs can be calculated by multiplying the Percent Band Usage for any threshold by the number of

channels. For example, Mean Erlangs for a threshold of -113 dBm is 23.15 ((2.08 / 100) * 1113).

21 99% confidence level - assuming an average message length of no greater than 5 seconds.

A-7
Table A-7. Percent Band Usage During Weekend Days for All 1113 Channels in the

406-420 MHz Band (Excluding HOCs)

Weekend Days Mean Detection Threshold

Threshold (dBm)

Threshold (dBIlV/m)

-117

12

-100

29

-90

39

-80

49

-70

59

Time Scale Percent Band Usage

Percent Band Usage (24 hours)

Percent Band Usage (8am-Spm)

1.76±0.0122

2.l9±0.0222

1.11

1.37

0.96

1.18

0.72

0.87

0.52

0.63

Note: Erlangs can be calculated by multiplying the Percent Band Usage for any threshold by the number of

channels. For example, Mean Erlangs for a threshold of -113 dBm is 19.59 «1.76 / 100) * 1113).

Table A-8. Percent Band Usage During Election Day for All 1113 Channels in the

406-420 MHz Band (Excluding HOCs)

Election Day Mean Detection Threshold

~,

, .1..1 (dBm) -90

~,

, .1..1 (dBIlV/m) 12 29 39 59

Time Scale Percent Band Usage

Percent Band Usage (24 hours) 2.l7±0.0222 1.3 1.15 0.88 0.59

Percent Band Usage (8am-Spm) 2.92±0.03 22 1.79 1.59 1.21 0.79

Note: Erlangs can be calculated by multiplying the Percent Band Usage for any threshold by the number of

channels. For example, Mean Erlangs for a threshold of -113 dBm is 24.15 «2.17/100) * 1113).

2299% confidence level - assuming an average message length of no greater than 5 seconds.

A-8
APPENDIX B: CONFIDENCE INTERVALS FOR OCCUPANCY MEASUREMENTS

B.I Introduction

This appendix describes a method for calculating confidence intervals for channel occupancy

measurements. Typically, a channel occupancy measurement involves random samples of the

signal strength. The channel is deemed occupied if a predetermined threshold is exceeded and

hence each measurement is a realization of a binary random variable. The probability of

exceeding the threshold gives the fraction of time the channel is occupied.

B.2 Statistical Character of Channel Occupancy Measurements

We wish to estimate the probability p that given a random observation, the signal strength

exceeds our predetermined threshold. Let the binary random variable ¢"i represent the

ith observation, then

{

I with prob, p

~.=

I 0 with prob, q =1 - p .

To estimate channel occupancy, we make n observations and obtain a realization of the random

variable

(1)

and estimate of channel occupancy p =u/n. Note that this estimate has the desirable property of

being unbiased (i.e. e{fJ} =p).

To further understand the statistical nature of our estimate it is useful to determine its probability

distribution. Some simplifying assumptions are needed to make this exercise tractable as

described below.

B.2.1 Characterization of the Process

The sequence of observations is a realization of a discrete random process. We assume that in

general the samples are not independent and are reasonably characterized as a regular

first-order Markov chain as discussed in [1].

B-1
For our purposes, the regular Markov chain is characterized by a 2 x 2 transition matrix P and

the relation

(q ,p)P =(q ,p).

In terms of p, q and the transition probability '11 =P {~i =0 I~i-l = 1} we have

P = ( 1 - 'I1P/q 'I1p/q ).

'11 1 - '11

(2)

When n is large, we can use the Central Limit Theorem for Markov Chains [2], which gives the

limiting normal distribution for v

s

P{r< v -np <s} ---+ _1_ Je-X2/2 dx

jnp .fi1t r

where nfJ is the limiting variance for the number of times that ~i = 1 and

fJ =pqL

where

L~(~) 1 -A,

The limiting distribution of the channel occupancy estimate is

r

B.2.2 Confidence Intervals

(3)

(4)

(5)

Since our measurement is an estimate, we would like to make some intelligent remarks about its

accuracy. A commonly used methodology is to calculate the endpoints of an interval that with

probability 1 - E contains the actual value of the population statistic. Thus, given a small

quantity E we need to calculate rand s so that

B-2
P{p+rvPln~p~p+svPln} =l-E, (6)

where it is customary to set s = -r =YE' By writing p =.P ± YEVpqLln and solving for p, it can

be shown that the probability that plies between the limits p±yEvpqLln is equivalent to the

probability that p lies between the limits

(7)

as described in [3]. For large n, we can use the normal distribution given in Equation 5 to

calculate YE

(8)

Note that the determination of L in Equation 7 requires that we know the transition probability A.

A method for estimating A is given in [1]. This method assumes that the time duration T of a

transmitted signal is random with an exponential distribution. Denoting the mean duration as to

and the time between samples as T, the following expression is used to estimate the transition

probability:

(9)

T:

B.2.3 Example

Assume we obtain n =4000 samples and observe that p =0.02 using a sample rate that is twice

the average time duration of the transmitted signal ('t = t

o/2). For the 90% confidence level we

have E =0.1 and using Equation 8, YE =1.64. From Equation 9, A =0.6 and L =4. Substituting

into Equation 7 gives an upper limit of 0.0286 and a lower limit of 0.0139.

B-3
B.3 Average Occupancy for a Band of Channels

Previous sections have addressed calculating the occupancy of a single channeL We now turn our

attention to calculating the average occupancy of a group or band of N channels, the calculation

of which is described as follows

N

P=.lL Pi (10)

N i=l

where Pi is the probability of occupancy of each channel as described above. When the number

of measurements for the i

th channel nj is large, Pi is approximately normal with variance pjqjL/nj.

Assuming the individual channels are independent, p is approximately normal with variance

(11)

Since we have sampled from several different populations, it is difficult to obtain exact

confidence intervals. However, for large nj the observed values of the i

th channel statistics

A

(p i'qi =1 -Pi' andL i from estimates ofAt ) can be used to approximate the variance

(12)

We can then say with (1 - E) 100% confidence that the mean probability of occupancy over a

band is between the following limits

(13)

where y€ is calculated as before and (J is calculated using Equation 12.

B.4 References

[1] A.D. Spaulding, and G.H. Hagn, "On the definition and estimation of spectrum occupancy,"

IEEE Trans. on EMC, voL 19, no. 3, pp. 269-280, Aug. 1977.

[2] J.G. Kemeny, and J.L. Snell (1960), Finite Markov Chains, Princeton, New Jersey: D. Van

Nostrand Company, Inc., 1960, p. 89.

B-4
[3] H. Cramer, Mathematical Methods of Statistics, Princeton, New Jersy: Princeton University

Press, 1946, pp. 514-515.

B-5
FORM NTIA-29 U.S. DEPARTMENT OF COMMERCE

(4-80) NAT'L. TELECOMMUNICATIONS AND INFORMATION ADMINISTRATION

BIBLIOGRAPHIC DATA SHEET

I. PUBLICATION NO. 2. Government Accession No. 3. Recipient's Accession No.

TR-07-448

4. TITLE AND SUBTITLE 5. Publication Date

Measurements to Characterize Land Mobile Channel Occupancy for Federal July 2007

Bands 162-174 MHz and 406-420 MHz in the Washington, D.C., Area 6. Performing Organization Code

NTIA/ITS

7. AUTHOR(S) 9. Project/Task/Work Unit No.

J. Randy Hoffman, Robert J. Matheson, and Roger A. Dalke

8. PERFORMING ORGANIZATION NAME AND ADDRESS

10. Contract/Grant No.

NTIA/ITS.M

U.S. Department ofCommerce

325 Broadway

Boulder, CO 80305

II. Sponsoring Organization Name and Address 12. Type ofReport and Period Covered

14. SUPPLEMENTARY NOTES

IS. ABSTRACT (A 200-word or less factual summary of most significant information. If document includes a significant bibliography or literature survey, mention it

here.)

This report describes field measurements to characterize Land Mobile Radio (LMR) channel occupancy ofFederal bands

162-174 MHz and 406--420 MHz at a single central location in the Washington, D.C., area. This is part ofthe National

Telecommunications and Information Administration effort to evaluate the spectrum efficiency in the Federal frequency

bands. Measurements ofthe received signal levels in LMR frequency bands 162-174 MHz and 406--420 MHz were

performed over an eight day period for the purpose of determining channel usage within the measurement system's

coverage area of approximately 100-km radius for base stations, 50-km radius for mobile units, and 25-km radius for

portable units. The measurements were made using new equipment and techniques that digitize as much as a 5-MHz

segment ofspectrum and process it to obtain simultaneous signal levels ofup to 400 individual LMR channels. These

techniques provided faster measurements, but also allowed enhanced post-processing ofthe data to remove effects of

impulsive noise.

16. Key Words (Alphabetical order, separated by semicolons)

channel occupancy; channel usage; Federal radio usage; Land Mobile Radio (LMR); measurements; spectrum efficiency

17. AVAILABILITY STATEMENT 18. Security Class. (This report) 20. Number of pages

UNLIMITED. 81

19. Security Class. (This page) 21. Price: