NTIA Report 96-330 (revised)

The Natural and Man-made

Noise Environment in Personal

Communications Services Bands

A.D. Spaulding 

U.S. DEPARTMENT OF COMMERCE

William M. Daley, Secretary

Larry Irving, Assistant Secretary 

for Communications and Information

May 1997

CONTENTS

Page

1. INTRODUCTION AND BACKGROUND....................................................................... 1 

2. GENERAL BACKGROUND AND INDIVIDUAL NOISE SOURCES...........................8 

3. SUMMARY AND CONCLUSIONS................................................................................21 

4. REFERENCES..................................................................................................................23 

iii 

THE NATURAL AND MAN-MADE NOISE ENVIRONMENT IN

PERSONAL COMMUNICATIONS SERVICES BANDS

A.D. Spaulding*

This report presents a summary of the available measurement information on the 

level and statistical characteristics of the background noise environment in the 

frequency range of 1-3 GHz. The frequency range covers the proposed frequencies 

for the new personal communications services. Natural and man-made 

unintentional radiations are covered, both the general overall background noise and

noise from individual sources. The urban noise environment in this frequency range 

is due primarily to automotive ignition systems. The noise is non-Gaussian in 

character, but not highly impulsive. 

noise; personal communications services (PCS); non-Gaussian interference; 

background noise levels. 

Key words: 

1. INTRODUCTION AND BACKGROUND

Natural and man-made noise and interference determine the limiting performance of radio 

systems. This has become more and more significant as the radio spectrum becomes increasingly

crowded, and noise-producing devices proliferate. In addition, the nature of the interference being, 

in many cases, highly non-Gaussian, seriously degrades most conventional systems designed for

optimal or near-optimal performance against white-Gaussian noise. Therefore, it is important that

the realworld electromagnetic environment be appropriately modeled so that correct system design 

and analysis can be carried out [1]. Prasad et aI., [2] suggest that Middleton's physical-statistical 

models [3,4,5] are appropriate models for microcellular mobile radio systems and use these models 

in some theoretical digital system performance analyses. 

It is the purpose of this short report to present the natural and man-made background noise levels 

likely in urban locations in the 1- to 3-GHz range and to give some indication as to the noise

environment's statistical character. This environment then must be combined with co-channel

interference (not treated here) to obtain the overall interference process. 

This introduction continues with a background discussion and noise parameter definitions. This is 

followed by an overall look at the natural noise background. The next section then gives the general

* The author was formerly with the U.S. Department of Commerce, National Telecommunications and

Information Administration, Institute for Telecommunication Sciences, Boulder, Colorado 80303. 
man-made background noise level and characteristics in the frequency range of interest and also

looks at the trend of the man-made noise level with time. Individual noise sources, including local

lightning, are also included. 

As noted above, this report addresses the background noise environment from natural and manmade sources, sometimes termed incidental radiation devices, but does not cover interference 

from intentionally radiated signals. A review of the nature of the interference environment due to 

these intentional signals can be obtained from [6,7,8]. 

It has been widely recognized since about 1945 that an effective study of communications systems

and devices cannot be carried out in terms of an individual message or signal alone, nor can the 

inhibiting effects of the background noise or other interference on performance be neglected. Rather, 

one must consider the set, or ensemble, of possible signals for which the system is designed, the

ensemble appropriate to the accompanying noise, and the manner in which they combine in the 

communications process itself. It is these that are ultimately significant in analysis, design, and 

performance. Thus, the methods of probability and random processes provide the required approach. 

Advances in communications technology rest on the foundation of Statistical Communications 

Theory. Indeed, this rigor tells what is required knowledge about noise and signal processes. 

Environmental noise (man-made noise, atmospheric noise, interfering signals, etc.) is a random 

process. This is true for noise from a single source, like an automobile, as well as the more general 

case in which the interfering noise is f(om a collection of many individual sources. The fact that 

environmental noise is a random process means that the noise can be described only in probabilistic 

or statistical terms and cannot be represented by a deterministic waveform or any collection of

deterministic waveforms. In addition, environmental noise is basically nonstationary and, therefore, 

great care must be exercised in planning, measuring, and interpreting the results. One must measure

long enough to obtain a good estimate of the required parameter, but be certain that the noise 

remains "stationary enough" during this period. This is no small point and is frequently overlooked 

in the design of measurement experiments. It is assumed that the random noise process is stationary 

enough over some required time period to obtain the required statistics. How these statistics change

with time, as from day to day, as well as with location, now becomes important. 

The basic description of any random process is its probability density function (pdf) or

distribution function. The first-order pdf of the received interference process is always required to

determine system performance (but sometimes is not sufficient). 

Although a random process, X(t), is said to be completely described if its hierarchy of distributions

is known, there are other important statistical properties (important to communications systems)

that are not immediately implied by this hierarchy. Moments and distributions of level crossings of

X(t) within a time interval, moments and distributions of the time interval between successive

crossings, distribution of extremes in the interval, and so on, are typical examples. 

2
For analysis or design of a communications system, the noise process of interest is the one seen by 

that part of the receiving system in which information is extracted from the desired signal. In

communications theory terms, the projection of the noise on the "signal space" of the receiver is

required. Narrowband noise processes are almost always those of interest. Here "narrowband" 

means "characterized by an envelope and phase." A narrowband process results whenever the 

bandwidth of the system is a small fraction of the center frequency. The noise process, net), at the 

output of a narrowband filter is given by 

n(t) = v(t) cos [ωct + Φ(t)], (1)

where v(t) is the envelope process and Φ(t) is the phase process. In the absence of discrete signals, 

Φ is generally uniformly distributed; that is 

, . 2

1 ( ) π π

π

p Φ = − ≤ Φ < (2)

Therefore, the statistics of the envelope process, v(t), are of primary interest. In general, for 

system analysis and design, the required statistics that determine performance are either the 

envelope statistics directly or are obtainable from the envelope and phase statistics. For noise from 

some discrete sources, or for general background noise plus interfering signals, Φ(t) may not be 

uniformly distributed, and the statistics of the Φ process must also be known. The envelope 

probability function is normally given as an exceedence distribution. The envelope exceedence 

distribution is defined as follows. 

The amplitude probability distribution (APD) is the fraction of the total measurement time, T, for

which the envelope voltage was above level v; 

D(v) = Prob [Envelope voltage ≥ v] = 1 - P(v), (3)

where P(v) is the cumulative distribution function. The pdf of v is given by the derivative of P(v). 

The appropriate envelope statistics are computed from the APD. (A measurement example at

2.335 GHz is shown in Section 2.) 

The average envelope voltage is termed the expected value of v, E[v];

∫ ∫

∞

= = = −

T

av v t dt vdD v

T

v E v

0 0

( ) ( ) 1 [ ] (4)

3 
where 

-dD (v) = p(v) dv. 

The rms voltage squared, (proportional to energy, or power) E[v

2

], is

( ) ( ). 1 [ ]

0

2

0

2 2 2

v t dt v dD v

T

v E v

T

rms ∫ ∫

∞

= = = − (5)

The rms voltage squared is the main single parameter of importance, giving the mean noise 

power, and with proper calibration determines the mean field strength impinging on the receiver

antenna. It is important to note that most commercial field strength meters specify the field 

strength correctly only for a CW signal (or white Gaussian noise if used in the "noise" mode), 

although true rms measurement devices are available. 

The noise power, while needed in determining the signal-to-noise ratio, for example, is seldom 

sufficient by itself to determine system performance. Quite often, the external noise is expressed

as an antenna noise factor, so that it can be combined with the noise generated within the 

receiving system to give an overall operating noise factor. The overall operating noise factor, f, for

a receiving system is composed of a number of noise sources at the receiving terminal of the 

system. Both internal and external noise must be considered. As derived in CCIR Report 413 [9], 

the only appropriate reference point for the overall operating noise factor for a radio-receiving 

system is the input of an equivalent loss-free receiving antenna. (The terminals of this lossless 

antenna do not exist physically.) The rms voltage squared can be referred by calibration to the 

terminals of an equivalent lossless antenna to give the available noise power, Pn. 

For receivers free from spurious responses, the system noise factor is given by: 

= + ( −1) + ( −1) + ( −1) a c c t c t r f f f l f l l f (6)

where

fa = the external noise factor defined as 

kt b

p f

o

n

a = (7)

(Fa is the external noise figure defined as Fa = 10 log10 fa, 

4
Pn = the available noise power from an equivalent lossless antenna, 

k = Boltzmann's constant = 1.38 x 10-23

 J/K, 

to = the reference temperature in K, taken as 290 K, 

b = the noise power bandwidth of the receiving system in Hz, 

lc = the antenna circuit loss 

(power available from lossless antenna/power available from actual antenna), 

lt = the transmission line loss (available input power/available output power), 

fr = the noise factor of the receiver 

(Fr is the receiver noise figure defined as Fr = 10 log10 fr), 

fc = the noise factor associated with the antenna circuit losses, 

1 ( 1) ,

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ = + −

o

c

c c t

t f l and (8)

ft = the noise factor associated with the transmission line losses,

1 ( 1) ,

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ = + −

o

t

t t t

t f l (9)

where 

tc = the actual temperature, in K, of the antenna and nearby ground, and 

tt = the actual temperature, in K, of the transmission line. 

If tc = tt = to, (6) becomes 

1 . a c t r f = f − + f f f (10)

Figure 1 shows the receiving system and how the noise factors can be combined. Equation (6) or 

(10) provides the means to determine an appropriate receiver noise figure, Fr, for an external noise

level, fa. . 

Equation (7) can be written 

Pn = Fa + B − 204dBW (11)

5

where 

Pn = 10 log10 pn , pn = available power in watts, 

B = 10 log10 b, and -204 = 10 log10 kto.

In general, since different antennas have different effective length-to-radiation resistance ratios, 

they can have different fa's for a given field strength [10]. One converts the specified fa data

(particular to the reference antenna) to the corresponding field strength. This field strength is then

applied to the antenna of interest to obtain its fa. Equation (7) or (11) relates available power and fa.

The available power is given, in general, for an antenna by 

, 4

( )

2

rad

eff

n R

e

P ⋅ l = (12)

where ē is the field strength (in a bandwidth b), eff l is the vector effective length of the antenna, 

and Rrad is the radiation resistance of the antenna.

For a short (<<λ), grounded, vertical monopole, from (7) and (12), the vertical component of the 

rms field strength is given by

20log 95.5 ( / ), (13) En = Fa + 10 f MHz + B − dB μV m

where En is the field strength in bandwidth b, and fMHz is the center frequency in MHz. 

Similarly, for a half-wave dipole in free space,

20log 99.0 ( / ), En = Fa + 10 f MHz + B − dB μV m (14)

The external noise factor, especially at higher frequencies, is also commonly expressed as a 

temperature, ta, where, by definition of fa, 

,

o

a

a t

t f = (15)

and ta is the effective antenna temperature due to external noise.

Noise from individual sources such as the sun, atmospheric gases, and the Earth's surface, are 

usually given in terms of a brightness temperature, tb. For the purposes of this report, the brightness

temperature, tb, and the effective antenna temperature, ta, are completely equivalent. 

7
Measurement data are given in terms of Fa (usually as distributions of Fa values for various time

periods). Measurement data are also often given directly in field strength. It often is not known if

this "field strength" is the actual field strength based on proper rms measurements. 

The above discussion shows the relationship between Fa and field strength so that various diverse 

measurements can be interrelated. It also defines a receiving system's overall operating noise factor.

This is especially useful to determine an appropriate receiver noise figure. It makes no sense to use

a receiver with more sensitivity than that dictated by the external noise. It is also desirable to know

the effect of the receiving system's internal noise on the overall interfering noise process. 

For impulsive noise processes at higher frequencies (i.e., > about 1 GHz), Fa values can be quite 

low and only the higher-magnitude pulses appear above the measurement receiver's noise 

threshold. Description here can take the form of peak values for a given time period, exceedence 

probabilities at these higher levels, pulse counts at these higher levels, etc. 

Before proceeding to the section that reviews the noise level (Fa, En, etc.) background 

measurements and the noise levels from particular sources in the frequency range of interest, the 

general overall background noise from natural sources is reviewed. 

Figure 2 shows this background noise in the frequency range of 1 Hz to 1 THz. Notice that in the 

frequency range of interest (1-3 GHz), the natural noise background is extremely low. This is 

especially true for PCS systems since curves LD, LQ, F, H, and M all refer to very narrow beam

antennas pointing directly at the source (e.g., galactic center or the sun) and PCS systems use much 

wider beamwidth antennas. In fact, in this frequency range, the background level can be as low as 

the cosmic background (ta = 2.7 K). Figure 3 ( a corrected figure from CCIR Report 670 [11]) 

shows much of the same information as Figure 2, but over the frequency range of 100 MHz to 100 

GHz. Figure 3 also has curve A which is the man-made noise background in a business (urban)

area. Extending curve A a bit, the background noise at 2 GHz (say) is around Fa = 5 dB. Detailed

measurements in the next section show that this is a reasonable estimate. The next section also 

shows that the background noise (due primarily to automotive ignition systems) is not particularly 

impulsive in this frequency range. 

2. GENERAL BACKGROUND AND INDIVIDUAL NOISE SOURCES 

In this section, the general noise background level in urban areas in the 1- to 3-GHz range is

reviewed in more detail. The interference from nearby individual sources is also presented. Most of

the available information is from measurements prior to about 1975, and generally at frequencies 

below 1 GHz, although there have been reports of serious interference from man-made noise above

1 GHz (usually in special locations or situations only). An example was given by Clarke, et al., [12] 

in 1975. His study of electromagnetic noise on ships in the 1535- to 1660-MHz band concluded that 

a serious interference problem existed in 1975 for the MARSAT system while ships were in port, 

due to impulsive noise from dock equipment and automotive ignition systems. Other examples are 

8


contained in Spaulding [13]. The major sources of radio noise in the frequency band of interest are, 

by rank, 

1. automotive ignitions,

2. transportation and generation facilities, 

3. industrial equipment, 

4. consumer products, 

5. lighting systems, and 

6. medical equipment. 

The effects of some of these sources are reviewed later.

In 1973, Skomal [14] performed a detailed analysis of the available noise measurements up to that

time. This analysis, along with some further analysis, appears in Skomal's noted book on man-made 

noise [15]. Three figures from [15] that summarize the analysis for urban areas are reproduced here. 

The highest measurement frequency was about 1 GHz. Figure 4 [15] shows the results of one group 

of measurement data. If the trend line (slope = -12.3 dB/decade) is extended, the estimated value of

Fa at 1 GHz is 7.7 dB, and at 2 GHz is 4.0 dB. Figure 5 shows the results of the analysis of another 

grouping of data. Here the 1-GHz Fa is 14 dB and the 2-GHz Fa estimate is 10 dB. Figure 6 [15] 

attempts to combine all urban measurements (defined as within 5.0 miles from an urban center). 

This figure gives an Fa estimate of 17 dB at 1 GHz and 13 dB at 2 GHz. Skomal's analysis was

made difficult by the fact that many of the measurements were not of Fa directly, but of other 

parameters, and made with diverse equipment. Interrelating these measurements was a difficult (and

approximate) task. The measurements were also widely separated in time. 

In 1992, Freeman [16] attempted to develop a trend with time for urban man-made noise in the

frequency range of 200-950 MHz using measurements made over the last 40 years. Many of the 

measurements (prior to about 1975) were those used by Skomal. He developed a linear trend with 

time (years) for Pn (power in dBm/kHz) using frequency and population as contributing variables. 

Reproduced results are shown in Figure 7, which uses the measurement data given in Table 1 and 

the references [17-26]. Note, from (11) and Figure 6, that an available power of -130 dBm/kHz 

(say) corresponds to an Fa of 14 dB. The results above from Skomal correspond to Freeman's trend 

for about the year 1970 or so. Since, in this frequency range, the background urban noise is due

primarily to automotive ignition systems which have changed over the years in type and 

suppression, it is reasonable to expect the noise level due to ignition systems to have decreased. 

Freeman's trend analysis indicates that the noise level now (1996) should be given by an Fa of about 

20 dB less than in 1970, on the order of -6 dB. 

Yamanaka and Sugiura [27] presented an extensive set of noise measurements in urban areas 

(general streets and metropolitan expressways in Tokyo) in the 1- to 3-GHz range. Table 2 

summarizes some of their measurements made at 1.48, 2.34, and 2.68 GHz. APD measurements 

were made, and Table 2 shows field strengths in a 100-kHz bandwidth exceeded .01 % and .001 % 

of the time (probabilities of 10-4 and 10-5). Figure 8 shows an APD measurement from [27] at 2.335 

GHz. The measurement system noise is also shown in Figure 8. Note that the background 

11




Table 1. Data Used in Regression Analysis 

(Reprinted from [16], by permission, 

from author and Commsphere '91 conference chairman)

City Source Frequency Year Population Average Noise Difference

(MHz) (Millions) (dBm/kHz) (dB)

Meas. Calc.

New York, NY Young 300 1951 7.891957 -114 -119.3 5.3

New York, NY Young 400 1951 7.891957 -116 -119.6 3.6

New York, NY Young 200 1951 7.891957 -111 -119.0 8.0

New York, NY Young 500 1951 7.891957 -118 -119.9 1.9

New York, NY Young 250 1951 7.891957 -112 -119.2 7.2

Haifa Simpson 250 1952 0.140000 -116 -117.8 1.8

Jerusa]em Simpson 250 1952 0.123000 -119 -117.8 I.2

Tel Aviv Simpson 500 1952 0.335000 -123 -118.6 4.4

Tel Aviv Simpson 250 1952 0.335000 -116 -117.9 1.9

Melbourne Ellis 424 1962 1.956400 -125 -125.7 0.7

Bendigo, Aust. Ellis 424 1962 0.040980 -126 -125.2 0.8

Ascot Vale, Aust. Ellis 424 1962 1.956400 -126 -125.7 0.3

Manhattan, NY RCA 800 1968 7.891957 -130 -132.5 2.5

Phoenix, AZ Anzic 300 1969 0.584303 -127 -129.8 2.8 

Cleveland, OH Anzic 480 1969 0.750879 -116 -130.4 14.4

Cleveland, OH Anzic 950 1969 0.750879 -133 -131.7 1.3

Ottawa, Can Lauber 400 1976 0.693288 -136 -135.0 1.0

Ottawa, Can Lauber 500 1976 0.693288 -138 -135.3 2.7

Ottawa, Can Lauber 300 1976 0.693288 -136 -134.7 1.3

Ottawa, Can Lauber 200 1976 0.693288 -132 -134.4 2.4

Los Angeles, CA Flath 510 1977 2.966850 -140 -136.6 3.4 

Montreal, Can Angers 200 1978 2.818300 -136 -136.4 0.4 

Montreal, Can Angers 500 1978 2.818300 -139.5 -137.2 2.3 

Montreal, Can Angers 300 1978 2.818300 -137 -136.6 0.4 

Montreal, Can Angers 400 1978 2.818300 -138.5 -136.9 1.6 

Ottawa, Can Lauber 700 1983 0.743821 -142.3 -140.7 1.6

Ottawa, Can Lauber 900 1983 0.743821 -143.7 -141.2 2.5

Ottawa, Can Lauber 950 1983 0.743821 -143.6 - 141.4 2.2 

Ottawa, Can Lauber 600 1983 0.743821 -141.9 -140.4 1.5

Ottawa. Can Lauber 800 1983 0.743821 -143.5 -141.0 2.5

Turin, Italy Cost 207 914 1989 1.190688 -127 -145.6 18.6

16
Table 2. Radio Noise Measurements 

(Reprinted from p. 355 of [27], 

by permission, from IEEE @ 1989 IEEE) 

Frequency Average Field Strength Exceeded, Standard Deviation Measurement

(GHz) dB μV/m, 100-kHz Bandwidth Place 

Probability Probability Probability Probability

of 10-4 of 10-5 of 10-4 of 10-5

1.48 39.7 47.0 3.7 3.0 Street

1.48 30.6 36.3 3.4 3.8 Expressway

2.34 32.7 39.4 3.6 3.7 Street

2.34 33.5 37.4 4.5 4.6 Street

2.34 30.3 33.4 3.3 4.5 Expressway

2.68 30.4 36.6 2.6 4.0 Street

2.68 32.8 36.4 1.5 3.5 Expressway

noise showed above the system noise only about 10% of the time. Even so, a reasonably good 

estimate of the rms level can be obtained from this APD using (5) since most of the energy is in the 

portion exceeding the system's noise. In [27], the Erms for this APD is found [using (5)] to be 20 dB

μV/m (l00-kHz bandwidth). This corresponds to an Fa of -1.9 dB, which corresponds reasonably 

well with Freeman's trend analysis. 

In Figure 8, the Rayleigh distribution (envelope of the Gaussian distribution) plots as a straight line 

of slope -1/2, as seen in the system noise measurement. If "peak value" is defined as the value 

exceeded .001% of the time, then the difference between "peak" and rms (which occurs at a 

probability of .36) for Gaussian noise is 11 dB. This difference for the background noise in Figure 8 

is on the order of 23 dB. The difference between "peak" and rms could be used as a measure of

impulsiveness (although the difference between average and rms is normally used). This difference 

is, of course, a function of bandwidth (except for Gaussian noise). The background noise given by 

the measured APD of Figure 8 is not very impulsive. It has a peak-to-rms difference of 23 dB in a

100-kHz bandwidth. 

As noted earlier, using Skomal's results [15] at 1 GHz, the noise level is around Fa = 14 or 17 dB. 

This (17 dB) converts to an rms field strength of 41.5dB μV/m/MHz. Skomal [15] also gives results 

for peak measurements of automotive ignition noise in urban areas (high traffic density). At 1 GHz,

17

these peak measurements are about 65-70 dB μV/m/MHz. These results (65-70 versus 41.5 in a 

1-MHz bandwidth) also indicate that the noise is not particularly impulsive. 

The above discussions have concerned the general urban noise background level. This broadband,

slightly impulsive noise is due primarily to automotive ignition systems. Also of concern are

individual high noise sources that may be close to communication systems. Accordingly, these 

individual sources will be reviewed briefly. For comparison purposes, for the general background,

the 1-GHz results of a peak field strength of 65 dB μV/m/MHz and a corresponding rms field

strength of 41.5 dB μV/m/MHz could be used. It should be noted, however, that these figures are 

for automotive noise around 1975 and now the noise level is approximately 20 dB less. Therefore, 

20 dB μV/m/MHz is chosen for the background rms field strength (Fa = -4.5 dB) and 40 dB 

μV/m/MHz is chosen for the background peak field strength at 1 GHz. This is a somewhat arbitrary

choice but should give a reasonable comparison for various individual sources with the current

background level. The following is a review of individual sources in no particular order. 

Nearby Lightning: Figure 9 from [28] shows a summary of lightning peak field strength 

measurements. The lightning is at a distance of 1 mile. At 1 GHz, the peak field strength is (from 

Figure 9) 35 dB μV/m/MHz, 5 dB below the background. 

High-voltage Transmission Lines: An extensive power line noise measurement program was

conducted in 1967 by Pakala et al., [29]. Some of these measurement results are also given in [15]. 

Typical results are given in Table 3. 

Spaulding and Disney [30] also presented power line measurement results. For a 115-kV line directly

under the power line, an Fa of approximately 0 dB is obtained (by extending the trend line since the 

Table 3. High-voltage Transmission Line Noise at 1 GHz 

Line (k V) Lateral Distance Peak Field Strength Type of Noise

from Line (ft) (dB μV/m/MHz) 

4.16 50 30 Gap Discharge

69.00 200 40 Gap Discharge

244.00 200 10 (Fair Weather) Corona 

244.00 200 40 (Sleet) Corona

525.00 50 20 Corona

735.00 50 30 Corona

19

highest frequency of measurement was 250 kHz). Herak and Kirk [31] give results of power line

measurements for a number of transmission lines ranging from 24-230 kV. In all cases, the 

measurements are similar in results to those above and indicate Fa values below zero at 1 GHz. 

Transformer Substations: Pakala [29] shows a peak field strength of 62 dB μV/m/MHz at 1 GHz,

60 ft from a 765-kV substation. 

Welders: Skomal [15] gives results from various references for measurements of radiated spectra

from welders. Typical results are a peak field strength at 1 GHz of 75 μV/m/MHz, 100 ft from an

RF-stabilized arc welder. 

Electromechanical Solenoid-type Relay: Joffe [32] presents measurements of the field emanating

from electromechanical solenoid relays. His general result, for both making contact and breaking

contact, is that the field strength at 1 GHz is approximately 5 μV/m in a 1-kHz bandwidth. This 

converts to an Fa value of 19 dB. 

Diesel Engine Generators: Parker [33] gives measurement results for diesel generator sets for 75-, 

175-, 400-, and 940-kW generators. For all these generator sets, the emitted broadband noise was 

on the order of 80 μV/m/MHz peak at 1 GHz. 

Industrial, Scientific and Medical Equipment (ISM): These equipments operate in the ISM 

bands and apparently do not have any significant harmonics in the frequency range of interest. 

Industrial heating equipment, however, is permitted to function throughout most of the radio 

spectrum. Skomal [15] shows the example of a 7.5-kW preheater that has a harmonic at around 1 

GHz with a field strength of 42 dB μV/m at 25 ft. 

Additional information on noise levels is given by Blackard et al., [34] at 918 MHz, 2.44 GHz, and 

4.0 GHz to develop models for indoor wireless communications. They report "Fa values" between 

24 and 50 dB at 918 MHz for various sites and around 30 dB at 2.44 GHz for a "typical case." The

various sites represent "common workplace environments." These measurements primarily are in 

terms of "dB above mean thermal noise." It is not clear that proper Fa measurements (i.e., rms with 

correct antenna calibration) were made, however. 

3. SUMMARY AND CONCLUSIONS

This report began by taking an overall look at the natural noise background and noted that in the 1-

to 3-GHz range, the .natural background noise is quite low; for systems using wide beamwidth 

antennas such as PCS, on the order of Fa = -10 dB or less. The man-made noise background in 

urban areas is due primarily to automotive ignition systems (in the 1- to 3-GHz range) and now 

(1996) is probably also quite low. (An approximate value of Fa = -4.5 dB, or rms field strength of

20 dB μV/m/MHz was obtained). This background noise is impulsive in nature but not with a wide 

dynamic range, that is, not "very" impulsive. A peak field strength of about 40 dB μV/m/MHz was 

21
obtained. Other possible sources of noise, nearby lightning (1-mile distant) and nearby highvoltage transmission lines, produce noise at levels at or below the background. 

This report showed that nearby individual "devices" can produce noise at levels well above the

overall background and gave results for transformer substations, welders, and electromechanical 

solenoid-type relays. Industrial, scientific and medical equipment generally does not affect the 

frequency range of interest. 

Finally, some recent measurements were cited that indicate the background noise in "common

workplace environments" (inside, around office equipment) can also be well above that specified

earlier. The exact nature of these measurements is not particularly clear, however. As noted, the

background noise must be combined with interfering cochannel signals to obtain the overall

interference environment. As given in [2], Middleton's Class A model should be a good model to

use to model the overall environment. This short survey makes it clear that additional proper

measurements are required to adequately characterize the background noise environment for PCS 

communications. 

22
4. REFERENCES

A.D. Spaulding and D. Middleton, "Optimum reception in an impulsive interference 

environment - part I: coherent detection," IEEE Trans. Comm. COM-25, pp. 910-923, Sep. 

1977. 

[1] 

R. Prasad, A. Kegel and A. deVos, "Performance of microcellular mobile radio in a

cochannel interference, natural, and man-made noise environment," IEEE Trans. Vehic. 

Tech., Vol. 42, No.1, pp. 33-40, Feb. 1993. 

[2] 

D. Middleton, "Statistical-physical models for urban radio noise environments -part I: 

foundations," IEEE Trans. Electromagn. Compat. EMC-14, pp. 38-56, May 1972. . 

[3] 

D. Middleton, "Canonical non-Gaussian noise models: their implications for measurement

and for prediction of receiver performance," IEEE Trans. Electromagn. Compat. EMC-21,

pp. 209-220, Aug. 1979. 

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25
FORM NTIA-29 U.S. DEPARTMENT OF COMMERCE 

(4-80) NAT’L. TELECOMMUNICATIONS AND INFORMATION ADMINISTRATION 

BIBLIOGRAPHIC DATA SHEET 

1. PUBLICATION NO. 

96-330 revised 

2. Government Accession No. 3. Recipient’s Accession No. 

5. Publication Date 

May 1997 

4. TITLE AND SUBTITLE 

The Natural and Man-Made Noise Environment in 

Personal Communications Services Bands 6. Performing Organization Code 

7. AUTHOR(S) 

A.D. Spaulding 

9. Project/Task/Work Unit No. 

8. PERFORMING ORGANIZATION NAME AND ADDRESS 

National Telecommunications & Information Admin. 

Institute for Telecommunication Sciences 

325 Broadway 

Boulder, CO 80303

10. Contract/Grant No. 

11. Sponsoring Organization Name and Address 

NTIA 

HCHB, 14th & Constitution Ave, NW 

Washington, DC 20230 

12. Type of Report and Period Covered 

14. SUPPLEMENTARY NOTES 

15. 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 presents a summary of the available measurement 

information on the level and statistical characteristics of the 

background noise environment in the frequency range of 1-3 GHz. The 

frequency range covers the proposed frequencies for the new personal 

communications services. Natural and man-made unintentional 

radiations are covered, both the general overall background noise and 

noise from individual sources. The urban noise environment in this 

frequency range is due primarily to automotive ignition systems. The 

noise is non-Gaussian in character, but not highly impulsive. 

16. Key Words (Alphabetical order, separated by semicolons) 

Key Words: Noise, personal communication services (PCS), non-Gaussian 

interference, background noise levels 

18. Security Class. (This report) 20. Number of pages 

 

 32 

17. AVAILABILITY STATEMENT 

UNLIMITED. 

19. Security Class. (This page) 21. Price: