NTIA Report TR-06-437 

Interference Potential of 

Ultrawideband Signals 

Part 3: Measurement of Ultrawideband Interference to 

 C-band Satellite Digital Television Receivers 

Michael Cotton 

Robert Achatz 

Jeffery Wepman 

Roger Dalke 

NTIA Report TR-06-437 

Interference Potential of 

Ultrawideband Signals 

Part 3: Measurement of Ultrawideband Interference to 

 C-Band Satellite Digital Television Receivers 

Michael Cotton 

Robert Achatz 

Jeffery Wepman 

Roger Dalke 

U.S. DEPARTMENT OF COMMERCE 

Carlos M. Gutierrez, Secretary 

Michael D. Gallagher, Assistant Secretary 

for Communications and Information 

February 2006 

DISCLAIMER 

Certain commercial equipment, software, and materials are identified in this report to specify the 

technical aspects of the reported results. In no case does such identification imply 

recommendation or endorsement by the National Telecommunications and Information 

Administration, nor does it imply that the material or equipment identified is necessarily the best 

available for the purpose. 

ACKNOWLEDGMENTS

The authors recognize John McCorkle of Freescale, Inc. for his leadership, insight, and 

insistence on the highest quality. We learned a great deal from working with John in all relevant 

technical areas. Dr. Paul Runkle of Signal Innovations provided a wealth of expertise in the field 

of digital signal processing. Given that signal processing was the crux of this project, Paul made 

significant contributions by ensuring the integrity and efficient execution of our simulations. 

This investigation required the services of a number of ITS engineers with a broad range of 

expertise, some of whom are not included in the list of authors. The authors recognize Brent 

Bedford for his expertise in test and measurement equipment and techniques; Randy Hoffman, 

Richard Statz, and Steve Engelking for developing much of the low level software routines 

needed to automate the experiment via software control; Stephen Wolf for his expertise in video 

quality assessment; Frank Sanders for sharing knowledge learned in previous interference tests 

on C-band earth station receivers [9]; Andrew Rogers and Michael Mitchell for their attention to 

detail in hardware production and signal characterization measurements; and Dr. William

Kissick for his support and leadership.

iii 

CONTENTS

Page 

FIGURES....................................................................................................................................... vi 

TABLES ......................................................................................................................................xiii 

1. INTRODUCTION ...................................................................................................................... 1 

1.1. Experiment.........................................................................................................................................2

1.2. Organization of Report ......................................................................................................................3

2. DP AND DS INTERFERENCE................................................................................................. 5 

2.1. Pulse Parameters................................................................................................................................5

2.2. DTV Susceptibility to DP and DS Interference.................................................................................7

2.2.1. DTV Signal Quality as a Function of Interference Average Power...........................................7

2.2.2. DTV Susceptibility as a Function of Fractional On-Time .......................................................11

2.3. Characterization of DP and DS Signals...........................................................................................16

2.3.1. Temporal Analysis ...................................................................................................................16

2.3.2. Amplitude Analysis..................................................................................................................17

2.3.3. Spectral Analysis......................................................................................................................19

3. MB INTERFERENCE.............................................................................................................. 21 

3.1. Gating Parameters............................................................................................................................21

3.2. DTV Susceptibility to MB Interference ..........................................................................................22

3.2.1. DTV Signal Quality as a Function of Interference Average Power.........................................22

3.2.2. DTV Susceptibility as a Function of Fractional On-Time .......................................................26

3.3. Characterization of MB Signals.......................................................................................................30

3.3.1. Temporal Analysis ...................................................................................................................30

3.3.2. Amplitude Analysis..................................................................................................................30

3.3.3. Spectral Analysis......................................................................................................................32

4. CONCLUSION......................................................................................................................... 34 

4.1. Signal Sets of Common DTV Susceptibility Behavior ...................................................................34

4.2. Summary of Measured Signal Characteristics.................................................................................35

4.3. Correlations Between DTV Susceptibility and Signal Characteristics............................................36

4.4. UWB Signal Emulation ...................................................................................................................39

5. REFERENCES ......................................................................................................................... 40 

APPENDIX A: THEORETICAL PSD OF DP AND DS SIGNALS........................................... 41 

A.1. DP-UWB.........................................................................................................................................46

A.2. DS-UWB.........................................................................................................................................49

APPENDIX B. CHARACTERIZATION MEASUREMENTS................................................... 51 

B.1. Measurement Setup.........................................................................................................................51

B.2. Temporal Analysis..........................................................................................................................53

B.3. Amplitude Analysis ........................................................................................................................74

B.4. Spectral Analyses..........................................................................................................................114

v 
FIGURES 

Page 

Figure 1. Simulated DP-04 (Tpulse = 10 ns)..............................................................................6 

Figure 2. Simulated (a) DS-03 and (b) DS-04 transmitting random data (Tchip = 0.758 ns)...6 

Figure 3. SNR, SNR′, INR, INR′, BER, and SER reference points...........................................7 

Figure 4. SER versus INR for a DTV channel operating at SNR = 9 dB and exposed to 

DP and DS interference. ..........................................................................................8 

Figure 5. BER versus INR for a DTV channel operating at SNR = 9 dB and exposed to 

DP and DS interference. ..........................................................................................8 

Figure 6. SER versus INR for a DTV channel operating at SNR = 12 dB and exposed to 

DP and DS interference. ..........................................................................................9 

Figure 7. BER versus INR for a DTV channel operating at SNR = 12 dB and exposed to 

DP and DS interference. ..........................................................................................9 

Figure 8. SER versus INR for a DTV channel operating at SNR = 15 dB and exposed to 

DP and DS interference. ........................................................................................10 

Figure 9. BER versus INR for a DTV channel operating at SNR = 15 dB and exposed to 

DP and DS interference. ........................................................................................10 

Figure 10. Illustration of threshold-of-visibility metrics.........................................................11 

Figure 11. INRTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 9 dB and 

exposed to DP and DS interference. ......................................................................13 

Figure 12. BERTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 9 dB and 

exposed to DP and DS interference. ......................................................................13 

Figure 13. INRTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 12 dB and 

exposed to DP and DS interference. ......................................................................14 

Figure 14. BERTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 12 dB and 

exposed to DP and DS interference. ......................................................................14 

Figure 15. INRTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 15 dB and 

exposed to DP and DS interference. ......................................................................15 

vi 
Figure 16. BERTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 15 dB and 

exposed to DP and DS interference. ......................................................................15 

Figure 17. APDs of DP signals band-limited to BDTV...............................................................18 

Figure 18. APDs of DS signals band-limited to BDTV...............................................................18 

Figure 19. PSDs of DP signals. ...............................................................................................20 

Figure 20. PSDs of DS signals. ...............................................................................................20 

Figure 21. Simulated MB-03 transmitting random data (TOFDM = 312.5 ns)............................22 

Figure 22. SER versus INR for a DTV channel operating at SNR = 9 dB and exposed to 

MB interference .....................................................................................................23 

Figure 23. BER versus INR for a DTV channel operating at SNR = 9 dB and exposed to 

MB interference .....................................................................................................23 

Figure 24. SER versus INR for a DTV channel operating at SNR = 12 dB and exposed to 

MB interference .....................................................................................................24 

Figure 25. BER versus INR for a DTV channel operating at SNR = 12 dB and exposed to 

MB interference .....................................................................................................24 

Figure 26. SER versus INR for a DTV channel operating at SNR = 15 dB and exposed to 

MB interference .....................................................................................................25 

Figure 27. BER versus INR for a DTV channel operating at SNR = 15 dB and exposed to 

MB interference .....................................................................................................25 

Figure 28. INRTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 9 dB and 

exposed to MB interference ...................................................................................27 

Figure 29. BERTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 9 dB and 

exposed to MB interference ...................................................................................27 

Figure 30. INRTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 12 dB and 

exposed to MB interference ...................................................................................28 

Figure 31. BERTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 12 dB and 

exposed to MB interference ...................................................................................28 

Figure 32. INRTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 15 dB and 

exposed to MB interference ...................................................................................29 

vii 
Figure 33. BERTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 15 dB and 

exposed to MB interference ...................................................................................29 

Figure 34. APDs of single-dwell MB signals band-limited to BDTV.........................................31 

Figure 35. APDs of multi-dwell MB signals band-limited to BDTV..........................................31 

Figure 36. PSDs of single-dwell MB signals..........................................................................33 

Figure 37. PSDs of multi-dwell MB signals...........................................................................33 

Figure 38. BI versus BD of UWB interference. Contours are drawn around signals within 

the same DTV susceptibility set. ...........................................................................37 

Figure 39. ∆INRTOV versus ζDTV of UWB interference. Contours are drawn around signals 

within the same DTV susceptibility set .................................................................37 

Figure 40. ∆INRTOV versus P/A of UWB interference. Contours are drawn around signals 

within the same DTV susceptibility set .................................................................38 

Figure A-1. Theoretical discrete and continuous spectra of DP-01 ..........................................47 

Figure A-2. Theoretical discrete and continuous spectra of DP-02 ..........................................47 

Figure A-3. Theoretical discrete and continuous spectra of DP-03 ..........................................48 

Figure A-4. Theoretical discrete and continuous spectra of DP-04 ..........................................48 

Figure A-5. |C(f)| of the DS-04 code word ................................................................................50 

Figure A-6. |C(f)| of the DS-06 code word ................................................................................50 

Figure B-1. Setup for RF signal characterization measurements..............................................51 

Figure B-2. Simplified setup for IF signal characterization measurements..............................52 

Figure B-3. Pulse duration statistics of gated noise with 50% duty cycle and 1-μs on-time ....53 

Figure B-4. Pulse interval statistics of gated noise with 50% duty cycle and 1-μs on-time .....54 

Figure B-5 Pulse interval statistics of complex Gaussian noise...............................................54 

Figure B-6. RF temporal analyses of DP-01 (Tpulse = 10,000 ns, w = 0.094 ns, fD = 0.5) ..........55 

Figure B-7. RF temporal analyses of DP-02 (Tpulse = 1000 ns, w = 0.094 ns, fD = 0.5) .............56 

viii 
Figure B-8. RF temporal analyses of DP-03 (Tpulse = 100 ns, w = 0.094 ns, fD = 0.5) ...............57 

Figure B-9. RF temporal analyses of DP-04 (Tpulse = 10 ns, w = 0.094 ns, fD = 0.5) .................58 

Figure B-10. RF temporal analyses of DS-01 (L = 1).................................................................59 

Figure B-11. RF temporal analyses of DS-02 (L = 3, sparse code) ............................................60 

Figure B-12. RF temporal analyses of DS-03 (L = 6, sparse code) ............................................61 

Figure B-13. RF temporal analyses of DS-04 (L = 12, DS code) ...............................................62 

Figure B-14. RF temporal analyses of DS-05 (L = 12, sparse code) ..........................................63 

Figure B-15. RF temporal analyses of DS-06 (L = 24, DS code) ...............................................64 

Figure B-16. RF temporal analyses of MB-01 (b = 1)................................................................65 

Figure B-17. RF temporal analyses of MB-02 (b = 3, d = 1)......................................................66 

Figure B-18. RF temporal analyses of MB-03 (b = 3, d = 2)......................................................67 

Figure B-19. RF temporal analyses of MB-04 (b = 7, d = 1)......................................................68 

Figure B-20. RF temporal analyses of MB-05 (b = 7, d = 2)......................................................69 

Figure B-21. RF temporal analyses of MB-06 (b = 7, d = 6)......................................................70 

Figure B-22. RF temporal analyses of MB-07 (b = 13, d = 1)....................................................71 

Figure B-23. RF temporal analyses of MB-08 (b = 13, d = 2)....................................................72 

Figure B-24. RF temporal analyses of MB-09 (b = 13, d = 12)..................................................73 

Figure B-25. RF amplitude analyses of DP-01 (Tpulse = 10,000 ns, w = 0.094 ns, fD = 0.5).........76 

Figure B-26. IF amplitude analyses of DP-01 at INRTOV .............................................................77 

Figure B-27. RF amplitude analyses of DP-02 (Tpulse = 1000 ns, w = 0.094 ns, fD = 0.5)............78 

Figure B-28. IF amplitude analyses of DP-02 at INRTOV .............................................................79 

Figure B-29. RF amplitude analyses of DP-03 (Tpulse = 100 ns, w = 0.094 ns, fD = 0.5)..............80 

Figure B-30. IF amplitude analyses of DP-03 at INRTOV .............................................................81 

ix 
Figure B-31. RF amplitude analyses of DP-04 (Tpulse = 10 ns, w = 0.094 ns, fD = 0.5)................82 

Figure B-32. IF amplitude analyses of DP-04 at INRTOV .............................................................83 

Figure B-33. RF amplitude analyses of DS-01 (L = 1)...............................................................84 

Figure B-34. IF amplitude analyses of DS-01 at INRTOV .............................................................85 

Figure B-35. RF amplitude analyses of DS-02 (L = 3, sparse code)...........................................86 

Figure B-36. IF amplitude analyses of DS-02 at INRTOV .............................................................87 

Figure B-37. RF amplitude analyses of DS-03 (L = 6, sparse code)...........................................88 

Figure B-38. IF amplitude analyses of DS-03 at INRTOV .............................................................89 

Figure B-39. RF amplitude analyses of DS-04 (L = 12, DS code) .............................................90 

Figure B-40. IF amplitude analyses of DS-04 at INRTOV .............................................................91 

Figure B-41. RF amplitude analyses of DS-05 (L = 12, sparse code).........................................92 

Figure B-42. IF amplitude analyses of DS-05 at INRTOV .............................................................93 

Figure B-43. RF amplitude analyses of DS-06 (L = 24, DS code) .............................................94 

Figure B-44. IF amplitude analyses of DS-06 at INRTOV .............................................................95 

Figure B-45. RF amplitude analyses of MB-01 (b = 1) ..............................................................96 

Figure B-46. IF amplitude analyses of MB-01 at INRTOV ............................................................97 

Figure B-47. RF amplitude analyses of MB-02 (b = 3, d = 1)....................................................98 

Figure B-48. IF amplitude analyses of MB-02 at INRTOV ............................................................99 

Figure B-49. RF amplitude analyses of MB-03 (b = 3, d = 2)..................................................100 

Figure B-50. IF amplitude analyses of MB-03 at INRTOV ..........................................................101 

Figure B-51. RF amplitude analyses of MB-04 (b = 7, d = 1)..................................................102 

Figure B-52. IF amplitude analyses of MB-04 at INRTOV ..........................................................103 

Figure B-53. RF amplitude analyses of MB-05 (b = 7, d = 2)..................................................104 

x 
Figure B-54. IF amplitude analyses of MB-05 at INRTOV ..........................................................105 

Figure B-55. RF amplitude analyses of MB-06 (b = 7, d = 6)..................................................106 

Figure B-56. IF amplitude analyses of MB-06 at INRTOV ..........................................................107 

Figure B-57. RF amplitude analyses of MB-07 (b = 13, d = 1)................................................108 

Figure B-58. IF amplitude analyses of MB-07 at INRTOV ..........................................................109 

Figure B-59. RF amplitude analyses of MB-08 (b = 13, d = 2)................................................110 

Figure B-60. IF amplitude analyses of MB-08 at INRTOV ..........................................................111 

Figure B-61. RF amplitude analyses of MB-09 (b = 13, d = 12)..............................................112 

Figure B-62. IF amplitude analyses of MB-09 at INRTOV ..........................................................113 

Figure B-63. RF spectral analyses of DP-01 (Tpulse = 10,000 ns, w = 0.094 ns, fD = 0.5) ..........115 

Figure B-64. RF spectral analyses of DP-02 (Tpulse = 1000 ns, w = 0.094 ns, fD = 0.5) .............116 

Figure B-65. RF spectral analyses of DP-03 (Tpulse = 100 ns, w = 0.094 ns, fD = 0.5)...............117 

Figure B-66. RF spectral analyses of DP-04 (Tpulse = 10 ns, w = 0.094 ns, fD = 0.5) .................118 

Figure B-67. RF spectral analyses of DS-01 (L = 1).................................................................119 

Figure B-68. RF spectral analyses of DS-02 (L = 3, sparse code)............................................120 

Figure B-69. RF spectral analyses of DS-03 (L = 6, sparse code)............................................121 

Figure B-70. RF spectral analyses of DS-04 (L = 12, DS code)...............................................122 

Figure B-71. RF spectral analyses of DS-05 (L = 12, sparse code)..........................................123 

Figure B-72. RF spectral analyses of DS-06 (L = 24, DS code)...............................................124 

Figure B-73. RF spectral analyses of MB-01 (b = 1)................................................................125 

Figure B-74. RF spectral analyses of MB-02 (b = 3, d = 1)......................................................126 

Figure B-75. RF spectral analyses of MB-03 (b = 3, d = 2)......................................................127 

Figure B-76. RF spectral analyses of MB-04 (b = 7, d = 1)......................................................128 

xi 
Figure B-77. RF spectral analyses of MB-05 (b = 7, d = 2)......................................................129 

Figure B-78. RF spectral analyses of MB-06 (b = 7, d = 6)......................................................130 

Figure B-79. RF spectral analyses of MB-07 (b = 13, d = 1)....................................................131 

Figure B-80. RF spectral analyses of MB-08 (b = 13, d = 2)....................................................132 

Figure B-81. RF spectral analyses of MB-09 (b = 13, d = 12)..................................................133 

xii 
TABLES 

Page 

Table 1. DP Pulse Parameters................................................................................................5 

Table 2. DS Pulse Parameters................................................................................................5 

Table 3. Measured DTV Susceptibility and FEC Performance for DP and DS 

Interference ............................................................................................................12 

Table 4. Measured Temporal Characteristics of DP and DS Signals Band-Limited 

to BDTV .....................................................................................................................16 

Table 5. Measured Amplitude Characteristics of DP and DS Signals Band-Limited 

to BDTV .....................................................................................................................17 

Table 6. MB Gating Parameters...........................................................................................21 

Table 7. Measured DTV Susceptibility and FEC Performance for MB Interference..........26 

Table 8. Measured Temporal Characteristics of MB Signals Band-Limited to BDTV ...........30 

Table 9. Measured Amplitude Characteristics of MB Signals Band-Limited to BDTV .........32 

Table 10. Ranked DTV Susceptibility Relative to Gaussian Noise Degradation..................34 

Table B-1. Maximum Waveform Values and VSG Amplitudes for RF VSA 

Measurements........................................................................................................52 

Table B-2. RF VSA Measurement Settings.............................................................................52 

Table B-3. Measured RF P/A (dB) of UWB Signals Band-Limited to Different 

Bandwidths ............................................................................................................74 

Table B-4. Measured IF P/A (dB) of UWB Signals at INRTOV and Band-Limited to BDTV .......75 

Table B-5. Spectrum Analyzer Settings for Characterizing UWB Signals ...........................114 

xiii 
xiv 
INTERFERENCE POTENTIAL OF ULTRAWIDEBAND SIGNALS

PART 3: MEASUREMENTS OF ULTRAWIDEBAND INTERFERENCE TO C-BAND 

SATELLITE DIGITAL TELEVISION RECEIVERS 

Michael Cotton, Robert Achatz, Jeffery Wepman, and Roger Dalke*

This report provides results from tests that measured digital television (DTV) 

susceptibility to ultrawideband (UWB) interference. A test system was developed 

to inject interference with known characteristics into a victim receiver and 

quantitatively measure susceptibility. In this experiment, a C-band satellite DTV 

victim receiver was injected with Dithered-Pulse (DP), Direct-Sequence (DS), 

and Multi-Band OFDM (MB) UWB interference. Results showed that the UWB 

signals could be categorized into three signal sets of common DTV susceptibility 

behavior. Interestingly, the categorized signals, band-limited by the DTV receiver 

filter, also had common characteristics. Set 1 consists of signals whose DTV 

susceptibility and band-limited signal characteristics resemble Gaussian noise. 

Set 2 consists of signals more deleterious than Gaussian noise interference. 

Notably, these signals had a wide range of band-limited signal characteristics and 

susceptibilities. Set 3 consists of a signal that is relatively benign. Results also 

showed that measurable band-limited characteristics, e.g., burst duration (BD), 

burst interval (BI), fractional on-time (ζDTV), and peak-to-average ratio (P/A), of 

the interfering signal are useful for predicting susceptibility. Finally, it was 

determined that continuous and gated noise signals can be used to emulate the 

interference effects of DS and MB signals for the DTV victim receiver and 

operational scenarios tested in this study. This might not be true, however, for 

testing the susceptibility of other victim receivers operating in narrower 

bandwidths as indicated by amplitude probability distributions as a function of 

frequency for MB signals band-limited to relatively narrow bandwidths. 

Key words: digital television; interference; satellite communications; ultrawideband 

1. INTRODUCTION 

In April 2002, the Federal Communications Commission (FCC) released FCC 02-48 [1] 

legalizing intentional, low-power ultrawideband (UWB) emissions between 3.1 GHz and 

10.6 GHz for communications devices operated indoors. UWB emissions were limited to 

-41 dBm average power in 1-MHz bandwidth and 0 dBm peak power in 50-MHz bandwidth, 

where average power is measured over a 1-millisecond integration time and peak power 

measurement duration is unspecified. The rules define a UWB device as one that emits signals 

with 10-dB bandwidth greater than 500 MHz or greater than 20% of the center frequency. 

 

*

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

Administration, U.S. Department of Commerce, Boulder, Colorado 80305. 
The FCC rules do not specify how the bandwidth requirement is achieved, consequently 

allowing industry considerable breadth in choosing a modulation. This breadth is exemplified by 

the development of Direct-Sequence (DS) and Multi-band Orthogonal Frequency-Division 

Multiplexing (MB) ultrawideband technologies. Proponents of DS and MB technologies have 

both sought standardization from IEEE (Institute of Electrical and Electronics Engineers) 802.15 

working group 3a on high-rate (greater than 20 million bits per second) Wireless Personal Area 

Networks (WPAN). As the name implies, WPAN is intended for short-distance (nominally less 

than 10 meters) wireless networking of devices such as PCs, personal digital assistants, and 

mobile phones. 

Both DS and MB transmitters are based on state-of-the-art integrated circuitry. DS modulation 

controls pulse polarity and hence supports phase shifting modulations. It achieves its ultra-wide 

bandwidth by transmitting sufficiently narrow pulses. An MB device simultaneously modulates 

122 carriers spaced 4.125 MHz apart to achieve the ultra-wide bandwidth and frequency hops the 

modulated carriers between non-overlapping bands. 

Since previous work performed at the Institute for Telecommunication Sciences (ITS) [2 – 5] did 

not specifically look at susceptibility of receivers to interference from DS or MB signals, and 

since there is little published information on this subject, ITS entered into a Cooperative 

Research and Development Agreement (CRADA) with the Freescale subsidiary of Motorola, 

Inc. to study how UWB interference might be predicted. 

1.1. Experiment 

Interference potential is a general concept where performance degradation of a victim receiver is 

predicted from interference signal characteristics. Interference potential is derived from

numerous susceptibility tests on receivers with a variety of bandwidths and signal demodulation 

techniques. This 3-part report series describes one such susceptibility test on a C-band satellite 

DTV receiver. This victim receiver was chosen because it demodulates signals transmitted in the 

3.7 to 4.2 GHz frequency range, which lies within the band allocated for UWB operation. It also 

uses a variety of bandwidths and signal demodulation techniques, which makes it an ideal victim

receiver for the study of interference potential. Additionally, instruments capable of providing 

quantitative DTV signal quality data from various receiver subsystems are readily available. 

Part 1 [6] of this report series describes procedures to characterize UWB signal emissions and 

measure DTV susceptibility. These procedures were executed on a test bed consisting of a 

satellite signal generator, a vector signal generator (VSG) emitting software-simulated UWB 

waveforms, a DTV signal monitor, and a vector signal analyzer (VSA). Specifically, the 

procedures describe how signal quality metrics from various receiver subsystems within the 

DTV signal monitor can be used to quantify susceptibility and how signal characterization 

metrics can be obtained from the VSA. 

The complexity of the UWB signals made experimental verification difficult. Part 2 [7] of this 

report series describes how continuous and gated noise signals were used in their place for 

verification purposes. These signals eliminated the complexities of the UWB signals and 

2 
provided a simple parameterized theoretical basis for understanding DTV susceptibility results. 

These tests verified the pre-Viterbi bit error rate (BER) and post-Reed-Solomon segment error 

rate (SER) DTV signal quality metrics. 

Beyond verification, insight into DTV susceptibility to UWB signals was gained from the gatednoise experiment. Results clearly showed that DTV susceptibility was dependent on the 

interfering signal gating parameters, such as on-time (τon) and off-time (τoff), and the bandwidth of 

the DTV receiver in addition to the more commonly used average and peak power metrics. This 

dependence on τon and τoff motivated an investigation into the effects of band-limiting on the 

temporal parameters and their subsequent correlation to DTV susceptibility. These band-limited 

metrics include burst duration (BD) and burst interval (BI), corresponding to τon and τoff, 

respectively. 

In this report, Part 3 of the report series, the experiment is extended to actual UWB signals. The 

primary objective of this report is to evaluate the susceptibility of the DTV receiver to the UWB 

signals. The secondary objective is to determine if DTV susceptibility can be predicted from

UWB signal parameters and the bandwidth of the victim receiver as well as band-limited metrics 

such as BD and BI. The final objective is to determine if continuous and gated Gaussian noise 

can be used in place of DS and MB signals, respectively, in susceptibility tests. 

1.2. Organization of Report 

UWB signals addressed in this report can be divided into two categories: Dithered-Pulse (DP) 

and DS signals that are specified with pulse parameters, i.e., pulse width (w), pulse repetition 

period (Tpulse), and fractional dither (fD), and MB signals that are specified with gating parameters, 

i.e., τon and τoff. Accordingly, DTV susceptibility and signal characterization results for DP and 

DS signals are given in Section 2, while results for MB signals are given in Section 3. 

DTV susceptibility results are plotted in two different ways. First, post-Reed-Solomon SER and 

pre-Viterbi BER of the DTV victim receiver are plotted as a function of interference-to-noise 

ratio (INR) to demonstrate how DTV performance depends on average power of the interfering 

signals. Second, INR and BER at the threshold of visibility (TOV), i.e., INRTOV and BERTOV, are 

plotted as a function of the reciprocal fractional on-time (1/ζ) in dB. These plots demonstrate 

how DTV susceptibility and forward error correction (FEC) performance depend on pulse and 

gating parameters of the interfering signals. Signal characterization includes temporal and 

amplitude analyses of measured UWB signals, which demonstrate the effects of band-limiting by 

the victim receiver. The temporal analyses are based on crossing statistics. Measured BD and BI

of the band-limited signals are compared to w and Tpulse of the DP and DS signals and to τon and 

τoff of the MB signals. Amplitude analyses are based on the amplitude probability distribution 

(APD). Measured peak-to-average ratios (P/As) of the band-limited DP and DS signals are 

compared to P/A of band-limited Gaussian noise, measured P/As of the band-limited MB signals 

are compared to P/As of corresponding band-limited gated Gaussian noise signals. Also provided 

are spectral analyses based on the power spectral density (PSD). 

 

3 
Section 4 summarizes DTV susceptibility test results, identifies signals with common DTV 

susceptibility behavior, plots DTV susceptibility results as a function of band-limited metrics, i.e, 

BD, BI, ζDTV, and P/A, to illustrate correlations, and evaluates the significance and scope of the 

findings. Finally, the validity of using continuous and gated noise signals to replicate DS and 

MB signals in this and other susceptibility tests is discussed. 

Appendices to this report contain information supporting the main body. Appendix A develops 

theoretical expressions for the PSD of the DP and DS signals. Appendix B provides measured 

crossing statistics of the UWB signals measured at the satellite radio frequency (RF) and bandlimited to the bandwidth of the victim receiver (BDTV), APDs of the UWB signals measured at the 

satellite RF in a variety of bandwidths, APDs of the UWB signals measured at the first 

intermediate frequency (IF) of the victim receiver in the presence of low-noise block 

downconverter (LNB) noise for interference powers corresponding to INRTOV, and APD statistics 

as a function of frequency and bandwidth of the UWB signals measured at the satellite RF. 

4 
2. DP AND DS INTERFERENCE

This section provides DTV susceptibility test results and characterization measurements for DP 

and DS interference. 

2.1. Pulse Parameters 

DP and DS signals achieve their ultra-wide bandwidth by transmitting pulses of short duration. 

These signals are specified by pulse width (w), the nominal pulse period (Tpulse = 1/PRF, where 

PRF is the pulse repetition frequency), and fractional dither (fD) to quantify pulse offset from

Tpulse. Table 1 specifies parameters that define the DP signals considered in this report. Fractional 

on-time is approximated as ζ ≈ w/Tpulse. Figure 1 illustrates pulse parameters for DP-04. 

Table 1. DP Pulse Parameters 

Type Index w (ns) Tpulse (ns) ζ fD

01 10,000 9.4×10-6

02 1000 9.4×10-5

03 100 9.4×10 DP -4

04 

0.094 

10 9.4×10-3

0.5 

Table 2 specifies parameters that define the DS signals considered in this report. Recall that DS 

devices multiply each data bit by a code word consisting of L chips. The chips have values of 

{-1, 0, 1} and are transmitted every Tchip = 1/fchip, where fchip = 1320 million chips per second. The 

coded data phase modulates pulses that are approximately 0.58 ns wide. Sparse codes used for 

DS-02, DS-03, and DS-05 are all zeros except for a single one, which results in distinct pulses 

every Tpulse = LTchip. DS codes used for DS-04 and DS-06 have relatively few zeros, which results 

in tightly-packed pulses every Tpulse = Tchip. Figure 2 illustrates pulse parameters for DS-03 and 

DS-04. 

Table 2. DS Pulse Parameters†

DS Parameters Pulse Parameters Type Index L Code Type w (ns) Tpulse (ns) ζ fD

01 1 N/A 0.758 0.77

02 3 Sparse 2.27 0.26

03 6 Sparse 4.55 0.13

04 12 DS 0.758 0.77

05 12 Sparse 9.09 0.064

DS 

06 24 DS

0.58 

0.758 0.77

0.0 

 

† The specific codes are [1] for DS-01, [0 1 0] for DS-02, [0 0 1 0 0 0] for DS-03, [0 -1 -1 -1 1 1 1 -1 1 1 -1 1] for

DS-04, [0 0 0 0 0 0 0 0 1 0 0 0] for DS-05, and [-1 1 -1 -1 1 -1 -1 1 -1 0 -1 0 -1 -1 1 1 1 -1 1 1 1 -1 -1 -1] for DS-06. 

5 
Figure 1. Simulated DP-04 (Tpulse = 10 ns). 

Figure 2. Simulated (a) DS-03 and (b) DS-04 transmitting random data (Tchip = 0.758 ns). 

6 
2.2. DTV Susceptibility to DP and DS Interference 

Results of the DTV susceptibility tests for DP and DS interference are described in this section. 

Post-Reed-Solomon segment error rate and pre-Viterbi bit error rate are plotted versus the ratio 

of average interference power to average noise power. Additionally, DTV susceptibility and FEC 

performance metrics, i.e., INRTOV and BERTOV, are plotted versus 1/ζ in dB. Figure 3 illustrates 

reference points for signal powers and DTV signal quality metrics acquired during the DTV 

susceptibility tests. 

Figure 3. SNR, SNR′, INR, INR′, BER, and SER reference points. 

2.2.1. DTV Signal Quality as a Function of Interference Average Power 

Figures 4 – 9 provide composite plots of measured SER and BER as a function of INR for 

measured SNR = {9, 12, 15} dB corresponding to SNR′ = {8.2, 10.5, 12.5} dB at the output of 

the demodulator. Each page is dedicated to a single SNR, each plot is dedicated to a specific 

signal type, and each curve represents a single Tpulse. Figures 4, 6, and 8 provide composite plots 

of SER, while Figures 5, 7, and 9 provide composite plots of BER. For each plot, Gaussian noise 

(GN-01) results are provided as a reference. 

The following are general comments regarding the shift, separation, and slope of these SER and 

BER curves. Both BER and SER shifted toward greater INR with increasing SNR. This occurred 

because more interference was needed to degrade stronger satellite signals. The shift of DP-01 

BER and SER was significantly greater than the other interference signals. SER due to DS signals 

was similar to SER due to GN-01. SER due to DP signals showed separation from GN-01 only 

when Tpulse was greater than 100 ns. Relative to Gaussian-noise degradation, the DTV receiver 

was more susceptible to DP-02 and less susceptible to DP-01. With the exception of DP-01 and 

DP-02, all DP and DS SER curves were steeper than corresponding BER curves, which indicates 

that SER was more sensitive than BER to changes in average interference power as expected with 

forward error correction. When Tpulse > 100 ns, the SER slope flattened with increasing Tpulse. In 

fact, the slope of DP-01 SER was so low that oscillations indicative of the systematic error 

mentioned in Appendix B of Part 2 of this report series were revealed. 

7 
Figure 4. SER versus INR for a DTV channel operating at SNR = 9 dB and exposed to DP 

and DS interference. 

Figure 5. BER versus INR for a DTV channel operating at SNR = 9 dB and exposed to DP 

and DS interference. 

8 
Figure 6. SER versus INR for a DTV channel operating at SNR = 12 dB and exposed to DP 

and DS interference. 

Figure 7. BER versus INR for a DTV channel operating at SNR = 12 dB and exposed to DP 

and DS interference. 

9 
Figure 8. SER versus INR for a DTV channel operating at SNR = 15 dB and exposed to DP 

and DS interference. 

Figure 9. BER versus INR for a DTV channel operating at SNR = 15 dB and exposed to DP 

and DS interference. 

10 
2.2.2. DTV Susceptibility as a Function of Fractional On-Time 

Figure 10 displays measured SER and BER curves for a DTV victim receiver operating at 

SNR = 15 dB and exposed to increasing levels of Gaussian noise interference. This figure also 

identifies important DTV susceptibility and FEC performance metrics. Importantly, 

SERTOV = 10-4 is a level identified by video quality studies [8] as the threshold of visibility (TOV) 

where video quality degradation is first evident. 

The INR that corresponds to SERTOV, INRTOV, is our primary DTV susceptibility metric. That is, 

receiver susceptibility increases as INRTOV decreases. The BER that corresponds to SERTOV, 

BERTOV, is our FEC performance metric. This metric quantifies the ability of the FEC to 

overcome bit errors caused by interference to achieve SERTOV. In other words, larger BERTOV

indicates more corrected bits and better FEC performance at the threshold of visibility. 

Figure 10. Illustration of threshold-of-visibility metrics. 

11 
Table 3 gives INRTOV and BERTOV results for DP and DS interference; GN-01 results from Part 2 

of this report series are also included for comparison purposes. Differences between INRTOV of 

DS, DP-03, DP-04, and GN-01 results were less than 0.5 dB. 

Table 3. Measured DTV Susceptibility and FEC Performance for DP and DS Interference 

SNR ≈ 9 dB SNR ≈ 12 dB SNR ≈ 15 dB

Type Index INRTOV

(dB) BERTOV

INRTOV

(dB) BERTOV

INRTOV

(dB) BERTOV

01 10.2 0.012 20.4 0.007 25.2 0.006

02 -0.7 0.025 4.2 0.021 8.0 0.022

03 1.0 0.041 5.8 0.045 9.6 0.049 DP 

04 0.9 0.038 5.6 0.039 9.0 0.040

01 0.6 0.038 5.4 0.038 9.1 0.038

02 0.5 0.038 5.5 0.038 9.1 0.039

03 0.9 0.038 5.7 0.039 9.0 0.040

04 0.6 0.039 5.7 0.041 9.2 0.042

05 0.6 0.039 5.7 0.041 9.2 0.042

DS 

06 0.2 0.037 5.2 0.038 8.8 0.039

GN 01 0.7 0.038 5.4 0.038 9.2 0.038

Recall from Part 2 of this report series that high DTV susceptibility, i.e., low INRTOV, correlated 

with poor FEC performance, i.e., low BERTOV. This demonstrated that DTV susceptibility was 

related to how effective the FEC was at overcoming bit errors caused by the interference at TOV. 

DP-01 demonstrates a distinct contrast with this trend, i.e., high DTV susceptibility did not 

correspond to poor FEC performance based on the chosen metric BERTOV. 

Figures 11 – 16 provide plots of INRTOV and BERTOV as a function of 10log(1/ζ), where DP pulse 

parameters w = 0.094 ns and Tpulse = {104

, 103, 102, 10} ns correspond to 

ζ = {9.4×10-6, 9.4×10-5, 9.4×10-4, 9.4×10-3} and 10log(1/ζ) = {50, 40, 30, 20} dB, and DS pulse 

parameters w = 0.58 ns and Tpulse = {0.758, 2.27, 4.55, 9.09} ns correspond to 

ζ = {0.77, 0.26, 0.13, 0.064} and 10log(1/ζ) = {1.6, 5.9, 8.9, 12} dB. The independent variable 

10log(1/ζ) was chosen because average power is proportional to ζ. Data points for DS-04 and 

DS-06 were excluded from the plots because they have the same ζ as DS-01. The horizontal 

dashed reference line in each INRTOV plot corresponds to DTV susceptibility to Gaussian noise

interference. Results demonstrate that DTV susceptibility can be related to particular pulse 

parameters. Generally speaking, DTV susceptibility to DS interference and DP interference with 

10log(1/ζ) ≤ 30 dB was comparable to that of Gaussian noise interference. At larger 10log(1/ζ), 

however, the DTV receiver was relatively more susceptible to DP-02 and less susceptible to 

DP-01. 

12 
Figure 11. INRTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 9 dB and exposed 

to DP and DS interference. 

Figure 12. BERTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 9 dB and 

exposed to DP and DS interference. 

13 
Figure 13. INRTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 12 dB and 

exposed to DP and DS interference. 

Figure 14. BERTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 12 dB and 

exposed to DP and DS interference. 

14 
Figure 15. INRTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 15 dB and 

exposed to DP and DS interference. 

Figure 16. BERTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 15 dB and 

exposed to DP and DS interference. 

15 
2.3. Characterization of DP and DS Signals 

Characterization of the DP and DS signals was accomplished via temporal, amplitude, and 

spectral analyses. The UWB signals were measured with the vector signal analyzer under 

optimal measurement conditions at the RF output of the vector signal generator. Appendix B 

discusses the measurement setup and provides an extensive set of results. This section provides 

band-limited signal characterization results for the BDTV = 19.51-MHz DTV receiver root-raisedcosine (RRC) filter. 

2.3.1. Temporal Analysis 

Temporal characteristics of the DP and DS signals were evaluated with crossing statistics, i.e., 

probabilities of the time duration that commences when a signal crosses an amplitude threshold 

and stays either above or below that threshold. Measured cumulative distribution functions for 

pulse duration (PD) and pulse interval (PI) statistics are given in Section B.2. Burst duration 

(BD) and burst interval (BI) are defined as the 10th percentile of PD and PI, respectively, using a 

crossing threshold equal to -70 dBm. This crossing threshold was useful for quantifying the 

effects of band-limiting on temporal characteristics of UWB signals, because it is high enough to 

avoid significant contribution from the measurement system noise floor and low enough to 

discern pulses and gated signals given the described measurement conditions. 

Table 4 summarizes the effects of band-limiting on the temporal characteristics of the DP and 

DS signals. DP-01 and DP-02 pulses were resolved because Tpulse was significantly greater than 

1/BDTV. As expected for these signals, band-limiting lengthened pulse widths, BD > w, and 

increased fractional on-times, ζDTV = BD/(BD + BI) > ζ. Notice that BI for DP-01 was greater 

than Tpulse due to dithering. BD and BI are less meaningful estimates when pulses are not resolved 

in the limiting bandwidth BDTV, because there are no on- and off-times to distinguish. This was 

the case for DS signals, DP-03, and DP-04, whose crossing statistics resembled those of GN-01, 

i.e., BI was invariably 0.02 μs, and the variability in BD had little effect on ζDTV ≈ 1. 

Table 4. Measured Temporal Characteristics of DP and DS Signals Band-Limited to BDTV

Pulse Parameters Band-Limited Metrics Type Index

w (μs) Tpulse (μs) ζ BD (μs) BI (μs) ζDTV

01 10.0 9.4×10-6 0.22 11.24 0.02

02 1.0 9.4×10-5 0.20 0.91 0.18

03 0.1 9.4×10-4 2.26 0.02 0.99 DP 

04 

0.000094 

0.01 9.4×10-3 8.46 0.02 1.00

01 0.000758 0.77 7.40 0.02 1.00

02 0.00227 0.26 8.36 0.02 1.00

03 0.00455 0.13 8.10 0.02 1.00

04 0.000758 0.77 9.03 0.02 1.00

05 0.00909 0.064 11.22 0.02 1.00

DS 

06 

0.00058 

0.000758 0.77 3.71 0.02 0.99

GN 01 N/A N/A 1.00 6.92 0.02 1.00

16 
2.3.2. Amplitude Analysis 

Amplitudes of the DP and DS signals were characterized with amplitude probability 

distributions, which give the probability that the signal amplitude exceeds a certain value. In this 

report, APDs are plotted on Rayleigh graphs where Rayleigh-distributed amplitudes of complexGaussian noise appear as a negatively-sloped, straight line. The sorting method, documented in 

Appendix D of Part 1 of this report series, was used to estimate and plot APDs of 131,072 

samples that are free of correlation introduced by the measurement system bandwidth and bandlimiting in post-measurement processing. 

Figures 17 and 18 provide composite APD plots of measured DP and DS signals, respectively. 

The upper bound of the shaded region is the average power of the VSA noise, approximately 

-79.7 dBm in BDTV. Notice that measured average powers, indicated in the legends, were 

proportional to ζ. Band-limiting had profound effects on the APDs of the DP and DS signals. For 

signals with Tpulse > 1/BDTV, a step-like APD occurred, where higher amplitudes corresponded to 

elongated pulses and lower amplitudes corresponded to system noise observable during the 

shortened off-times between pulses. DP-01 and DP-02 band-limited to BDTV have step-like APDs. 

For signals with Tpulse ≤ 1/BDTV a negatively-sloped, straight APD can occur, corresponding to 

Rayleigh-distributed amplitudes due to elongated pulses overlapping each other. DS-01 and DS02 band-limited to BDTV have Rayleigh-distributed APDs. 

Table 5 summarizes measured peak-to-average ratio and APD characteristics for the bandlimited DS and DP signals. APD characteristics are labeled RAYL for Rayleigh-distributed 

amplitudes or RP for resolved pulses. More specifically, RP designates a step-like APD whose 

amplitude falls below the average power of the VSA noise at least 10% of the time. Notice that 

measured P/As of the DS signals were 0 – 3 dB less than P/A of GN-01. 

Table 5. Measured Amplitude Characteristics of DP and DS Signals Band-Limited to BDTV

Type Index P/A (dB) APD 

01 23.5 RP

02 13.8 RP

03 5.4 DP 

04 8.1

01 9.5 RAYL

02 9.0 RAYL

03 8.1

04 6.6

05 6.6

DS 

06 6.8

GN 01 9.6 RAYL

17 
Figure 17. APDs of DP signals band-limited to BDTV. 

Figure 18. APDs of DS signals band-limited to BDTV. 

18 
2.3.3. Spectral Analysis 

Spectral characteristics of the DP and DS signals were characterized with the power spectral 

density, which represents the average power present per unit bandwidth as a function of 

frequency. Appendix A provides theoretical analyses of the PSD for DP and DS signals. In short, 

PSDs of the DP signals have discrete and continuous components that depend on the pulse 

spectrum and the dither function, while PSDs of the DS signals have only a continuous 

component that depends on the pulse spectrum and the code word spectrum. 

PSDs were calculated from VSA measurements by averaging squared spectrum magnitudes of 

500 rectangular-windowed, non-overlapping blocks of signal data. The periodic nature of the 

signals required that the block size be an integer multiple of the pulse period. To have the same

∆f, the block size must also be a common integer multiple of all pulse periods. For the DP 

signals, these requirements were satisfied with a block size equal to 100 μs, which corresponds to 

∆f = 10.0 kHz. For the DS signals, these requirements were satisfied with a block size equal to 

90.9 μs, which corresponds to ∆f = 11.0 kHz. 

Figures 19 – 20 provide PSDs of the DP and DS signals, respectively, in the frequency band of 

the DTV victim receiver, i.e., 0 Hz on the plots corresponds to 3820 MHz. The victim receiver 

RRC filter was not applied to the data in post-measurement processing. The measured PSDs of 

DP signals, DS-01, DS-02, DS-03, DS-04, and DS-05 were flat over the DTV frequency band. In 

contrast and in agreement with Figure A-6, the PSD of DS-06 was not flat due to the code word 

spectrum. Notice that the measured power densities of the DP and DS signals were proportional 

to ζ. Also, the spectral line at 0 Hz, most prevalent in DP-01, was due to VSG local-oscillator 

feed-through. The influence of the VSG local-oscillator feed-through on test results was 

discussed in Appendix C of Part 1 of this report series. 

19 
Figure 19. PSDs of DP signals. 

Figure 20. PSDs of DS signals. 

20 
3. MB INTERFERENCE

This section provides DTV susceptibility test results and characterization measurements for MB 

interference.

3.1. Gating Parameters 

MB-OFDM achieves its ultra-wide bandwidth by simultaneously modulating 122 tones spaced 

4.125 MHz apart. MB signals frequency-hop between bands according to a specified timefrequency code, which defines the number of bands (b) and the number of dwells (d) the signal 

stays in each band. From the perspective of a victim receiver operating within a single band, MB 

signals have two gating processes associated with (1) hopping and (2) insertion of zero-prefix 

and guard-intervals in each MB symbol. Each MB symbol is comprised of a zero-prefix (ZP), 

data block, and guard interval (GI); the MB symbol period is the sum of its constituents, i.e., 

TOFDM = TZP + TDATA + TGI , where TZP = 60.6 ns, TDATA = 242.4 ns, and TGI = 9.5 ns. 

Table 6 provides the MB parameters and corresponding gating parameters, i.e., on-time (τon), offtime (τoff), and fractional on-time (ζ), considered in this report; these parameters also apply to 

GN(MB) gated-noise signals. Fractional on-time is calculated exactly as ζ = TDATA / bTOFDM . Onand off-times are calculated as τon = dTOFDM - TZP - TGI and τoff = (b – 1)dTOFDM + TZP + TGI , 

respectively. These expressions ignore TZP + TGI between consecutive MB symbols and therefore 

are approximate in the multiple-dwell, i.e., d > 1, cases. This is necessary for later comparisons 

to BD and BI metrics and is justified for this experiment because TZP + TGI = 70.1 ns is 

comparable to the reciprocal bandwidth of the victim receiver, i.e., 1/BDTV = 51.3 ns. Figure 21 

illustrates gating parameters for MB-03. 

Table 6. MB Gating Parameters 

MB Parameters Gating Parameters Type Index b d τon (μs) τoff (μs) ζ

01 1 N/A 0.24 0.07 0.776

02 3 1 0.24 0.70 0.259

03 3 2 0.55 1.32 0.259

04 7 1 0.24 1.95 0.111

05 7 2 0.55 3.82 0.111

06 7 6 1.80 11.32 0.111

07 13 1 0.24 3.82 0.060

08 13 2 0.55 7.57 0.060

MB, 

GN(MB) 

09 13 12 3.68 45.07 0.060

21 
Figure 21. Simulated MB-03 transmitting random data (TOFDM = 312.5 ns). 

3.2. DTV Susceptibility to MB Interference 

Results of the DTV susceptibility tests for MB interference are described in this section. PostReed-Solomon segment error rate and pre-Viterbi bit error rate are plotted versus the ratio of 

average interference power to average noise power. Additionally, DTV susceptibility and FEC 

performance metrics, i.e., INRTOV and BERTOV, are plotted versus 1/ζ in dB. 

3.2.1. DTV Signal Quality as a Function of Interference Average Power 

In this subsection, SER and BER are plotted versus INR for DTV susceptibility to MB

interference. Figures 22 – 27 provide composite plots of measured SER and BER as a function of 

INR. Each page is dedicated to a single SNR, each plot is dedicated to a specific range of d, and 

each curve represents a specific value of b. Figures 22, 24, and 26 provide composite plots of 

SER, while Figures 23, 25, and 27 provide composite plots of BER. For each plot, GN-01 and 

MB-01 results are provided as a reference. 

The following are general comments regarding the shift, separation, and slope of SER and BER

curves. Both SER and BER shifted toward greater INR with increasing SNR. SER curves with 

fixed SNR and τon show increased separation (from GN-01) with decreasing ζ. Likewise, all SER

curves with fixed SNR and ζ exhibit increased separation with increasing τon. SER curves were 

generally steeper than corresponding BER curves. For sufficiently small ζ, slopes of the SER

curves were not as steep as higher-ζ cases. These observations are similar to those discussed in 

Appendix A of Part 2 of this report series for GN(MB) gated-noise interference. 

22 
Figure 22. SER versus INR for a DTV channel operating at SNR = 9 dB and exposed to 

MB interference. 

Figure 23. BER versus INR for a DTV channel operating at SNR = 9 dB and exposed to 

MB interference. 

23 
Figure 24. SER versus INR for a DTV channel operating at SNR = 12 dB and exposed to 

MB interference. 

Figure 25. BER versus INR for a DTV channel operating at SNR = 12 dB and exposed to 

MB interference. 

24 
Figure 26. SER versus INR for a DTV channel operating at SNR = 15 dB and exposed to MB 

interference.

Figure 27. BER versus INR for a DTV channel operating at SNR = 15 dB and exposed to MB 

interference.

25 
3.2.2. DTV Susceptibility as a Function of Fractional On-Time 

Table 7 summarizes INRTOV and BERTOV results for MB interference; GN(MB) results from Part 2 

of this report series are included for comparison purposes. Differences between INRTOV of 

corresponding MB and GN(MB) results were less than 1 dB. 

Table 7. Measured DTV Susceptibility and FEC Performance for MB Interference

SNR = 9 dB SNR = 12 dB SNR = 15 dB

Type Index INRTOV

(dB) BERTOV

INRTOV

(dB) BERTOV

INRTOV

(dB) BERTOV

01 0.6 0.039 5.6 0.041 9.5 0.043

02 -0.3 0.032 4.4 0.032 8.0 0.034

03 -0.7 0.030 3.6 0.028 7.1 0.029

04 -1.4 0.024 3.0 0.021 6.1 0.021

05 -3.0 0.019 1.2 0.015 4.2 0.014

06 -4.9 0.015 -0.9 0.010 2.6 0.010

07 -3.1 0.018 0.9 0.013 4.1 0.021

08 -4.9 0.015 -1.1 0.009 2.1 0.009

MB 

09 -7.7 0.011 -3.4 0.006 -0.3 0.005

01 0.5 0.037 5.2 0.036 8.5 0.036

02 -0.7 0.030 3.7 0.027 7.0 0.028

03 -0.9 0.028 3.5 0.025 6.5 0.025

04 -1.9 0.022 2.3 0.018 5.8 0.019

05 -3.2 0.018 0.8 0.013 4.2 0.013

06 -5.0 0.015 -1.2 0.009 2.3 0.009

07 -3.3 0.016 0.7 0.012 4.3 0.011

08 -5.1 0.014 -1.1 0.009 2.3 0.008

GN(MB) 

09 -7.4 0.011 -3.3 0.005 -0.3 0.005

GN 01 0.7 0.038 5.4 0.038 9.2 0.038

Figures 28 – 33 plot INRTOV and BERTOV versus 1/ζ in dB, where b = {1, 3, 7, 13} correspond to 

ζ = {0.776, 0.259, 0.111, 0.060} and 10log(1/ ζ) = {1.10, 5.87, 9.55, 12.2} dB. The horizontal 

dashed reference line in each INRTOV plot corresponds to DTV susceptibility to Gaussian noise

interference. In terms of average interference power, the DTV receiver was generally more 

susceptible to MB signals than Gaussian noise. This is observed in Figures 28, 30, and 32 where 

INRTOV was lower for MB-02 – MB-09 than for GN-01. Additionally, the MB results 

demonstrated that DTV susceptibility was dependent on temporal parameters of the interfering 

signal. For MB-01, τoff was comparable to 1/BDTV = 51.3 ns, and DTV susceptibility was similar 

to that of Gaussian noise and independent of τon and ζ. For MB-02 – MB-09, however, τoff was 

significantly greater than 1/BDTV, and DTV susceptibility was clearly dependent on τon and ζ. 

More specifically, for fixed SNR and τon, DTV susceptibility increased with decreasing ζ. 

Likewise, for fixed SNR and ζ, DTV susceptibility increased with increasing τon. 

26 
Figure 28. INRTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 9 dB and exposed 

to MB interference. 

Figure 29. BERTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 9 dB and 

exposed to MB interference. 

27 
Figure 30. INRTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 12 dB and 

exposed to MB interference. 

Figure 31. BERTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 12 dB and 

exposed to MB interference. 

28 
Figure 32. INRTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 15 dB and 

exposed to MB interference. 

Figure 33. BERTOV versus 10log(1/ζ) for a DTV channel operating at SNR = 15 dB and 

exposed to MB interference. 

29 
3.3. Characterization of MB Signals 

Characterization of MB signals was accomplished via temporal, amplitude, and spectral 

analyses. This section provides band-limited signal characterization results for the 

BDTV = 19.51-MHz DTV receiver RRC filter. 

3.3.1. Temporal Analysis 

Table 8 summarizes the effects of band-limiting on the temporal characteristics of MB signals. 

As expected, band-limiting lengthened on-times, BD > τon, shortened off-times, BI < τoff, and 

increased fractional on-times, ζDTV > ζ. BD and BI approached the respective gating parameters 

only when τon and τoff were significantly larger than 1/BDTV. Notice that measured MB temporal 

characteristics are identical to those of the GN(MB) signals. 

 

Table 8. Measured Temporal Characteristics of MB Signals Band-Limited to BDTV

Gating Parameters MB GN(MB) 

Index τon 

(μs)

τoff

(μs) ζ BD (μs)

BI 

(μs) ζDTV

BD 

(μs)

BI 

(μs) ζDTV

01 0.24 0.07 0.776 3.7 0.0 1.00 3.7 0.0 1.00

02 0.24 0.70 0.259 0.4 0.6 0.40 0.4 0.6 0.40

03 0.55 1.32 0.259 0.7 1.2 0.37 0.7 1.2 0.37

04 0.24 1.95 0.111 0.4 1.8 0.18 0.4 1.8 0.18

05 0.55 3.82 0.111 0.7 3.7 0.16 0.7 3.7 0.16

06 1.80 11.32 0.111 1.9 11.2 0.15 1.9 11.2 0.15

07 0.24 3.82 0.060 0.4 3.7 0.10 0.4 3.7 0.10

08 0.55 7.57 0.060 0.7 7.4 0.09 0.7 7.4 0.09

09 3.68 45.07 0.060 2.5 44.9 0.05 2.5 44.9 0.05

3.3.2. Amplitude Analysis 

Figures 34 and 35 provide composite APD plots of measured single- and multi-dwell MB 

signals, respectively. Notice that measured average powers, indicated in the legends, were 

proportional to ζ. Band-limiting had profound effects on the APDs of the MB signals. For 

MB-01, τoff was less than or comparable to 1/BDTV and a negatively-sloped, relatively straight 

APD occurred. For MB-02 – MB-09, τoff exceeded 1/BDTV and a step-like APD occurred where 

higher amplitudes corresponded to MB interference during elongated on-times and lower 

amplitudes corresponded to system noise observable during shortened off-times. This was most 

pronounced for MB-08 and MB-09. 

30 
Figure 34. APDs of single-dwell MB signals band-limited to BDTV. 

Figure 35. APDs of multi-dwell MB signals band-limited to BDTV. 

31 
Table 9 summarizes measured P/A and APD characteristics for the MB signals band-limited to 

BDTV. APD characteristics are labeled RG for resolved gating, i.e., step-like APD whose 

amplitude falls below the average power of the VSA noise at least 10% of the time. Notice that 

measured P/As of the MB signals were 1 – 2 dB less than the P/A of corresponding GN(MB) 

signals. 

Table 9. Measured Amplitude Characteristics of MB Signals Band-Limited to BDTV

MB GN(MB) Index P/A (dB) APD P/A (dB) APD

01 8.3 10.5

02 12.8 RG 14.7 RG

03 12.8 RG 14.6 RG

04 16.2 RG 18.0 RG

05 16.4 RG 17.9 RG

06 16.3 RG 17.8 RG

07 18.7 RG 20.2 RG

08 18.9 RG 20.1 RG

09 18.8 RG 19.9 RG

3.3.3. Spectral Analysis 

Figures 36 and 37 provide measured PSDs of the single- and multi-dwell MB signals, 

respectively, over the VSA bandwidth. In Figure 37, the PSD of MB-05 is directly beneath 

MB-06. To compute the PSD, 500 blocks of length = 170.6 μs (∆f = 5.9 kHz) were averaged. 

Measured MB PSDs were flat across the band of interest, and measured power density was 

proportional to ζ. Differences between measured MB and GN(MB) PSDs were negligible. Also, 

the spectral line at 0 Hz was due to VSG local-oscillator feed-through. The influence of the VSG 

local-oscillator feed-through on test results was discussed in Appendix C of Part 1 of this report 

series. 

32 
Figure 36. PSDs of single-dwell MB signals. 

Figure 37. PSDs of multi-dwell MB signals. 

33 
4. CONCLUSION

The primary objective of this experiment was to measure and evaluate the susceptibility of a 

C-band satellite DTV receiver to UWB interference. The secondary objective was to determine if 

DTV susceptibility could be predicted from measured signal characteristics. A final objective 

was to determine if continuous and gated Gaussian noise could be used to emulate DS and MB 

signals, respectively, in susceptibility tests. Each of these objectives are addressed in these 

concluding remarks. 

4.1. Signal Sets of Common DTV Susceptibility Behavior 

The primary objective of this experiment was to measure and evaluate the susceptibility of a 

DTV victim receiver to UWB interference. INRTOV is our primary DTV susceptibility metric, i.e., 

DTV susceptibility increases as INRTOV decreases and conversely decreases as INRTOV increases. 

Table 10 provides ∆INRTOV for the UWB signals ranked from least to most susceptible, where 

∆INRTOV is normalized to the INRTOV of Gaussian noise. Notice that variation with SNR does not 

affect ranking, and for all signals except DP-01 SNR variation is minimal. Superimposed upon 

this ranking is categorization into three signal sets distinguished by their distance from the 

INRTOV of Gaussian noise, i.e., Set 1 is defined as -0.5 dB ≤ ∆INRTOV ≤ 0.5 dB, Set 2 is defined 

as ∆INRTOV < -0.5 dB, and Set 3 is defined as ∆INRTOV > 0.5 dB. 

Table 10. Ranked DTV Susceptibility relative to Gaussian Noise Degradation 

∆INRTOV (dB) Rank Signal SNR = 9 dB SNR = 12 dB SNR = 15 dB Set 

1 DP-01 9.5 15.0 16.1 3

2 DP-03 0.3 0.4 0.5

3 MB-01 -0.1 0.2 0.3

4 DS-03 0.2 0.3 -0.1

5 DS-04 -0.1 0.3 0.1

6 DS-05 -0.1 0.3 0.1

7 DP-04 0.2 0.2 -0.2

8 GN-01 0.0 0.0 0.0

9 DS-01 -0.1 0.1 0.0

10 DS-02 -0.2 0.2 -0.1

11 DS-06 -0.5 -0.2 -0.3

1 

12 MB-02 -1.0 -1.0 -1.2

13 DP-02 -1.5 -1.2 -1.1

14 MB-03 -1.4 -1.8 -2.0

15 MB-04 -2.1 -2.4 -3.0

16 MB-05 -3.7 -4.2 -5.0

17 MB-07 -3.8 -4.5 -5.1

18 MB-06 -5.6 -6.3 -6.6

19 MB-08 -5.6 -6.5 -7.0

20 MB-09 -8.4 -8.8 -9.4

2 

34 
Signals in Set 1 are for all practical purposes equivalent to Gaussian noise in terms of DTV 

susceptibility. Signals in Set 2 have INRTOV measurably below that of Gaussian noise and 

consequently are more deleterious to DTV reception. DP-01 is the only signal in Set 3; its INRTOV

is considerably greater than that of Gaussian noise and therefore is the most benign to DTV 

reception. Demarcation of Sets 1 and 3 is relatively straightforward as they are separated by a 

wide margin. Demarcation of Sets 1 and 2, however, is slightly more subjective. For example, 

INRTOV of MB-02 is merely 1.0 – 1.2 dB below that of Gaussian noise. 

During this experiment, there was interest in understanding the effects of UWB interference on 

the DTV forward error correction, consisting of a Viterbi decoder, convolutional byte deinterleaver, and Reed-Solomon decoder. Having access only to pre-Viterbi BER and post-ReedSolomon SER, the FEC was regarded as a black box whose performance was evaluated by the 

average number of bit errors it corrected. In particular, FEC performance was deemed good 

when it achieved SERTOV = 10-4 from a relatively high BERTOV. Interestingly in Sets 1 and 2, poor 

FEC performance, i.e., low BERTOV, was correlated with high DTV susceptibility, i.e., low 

INRTOV. Inspection of MB-01 and MB-09 in Table 7 (SNR = 12 dB), for example, shows that 

BERTOV decreased from 0.041 to 0.006 as INRTOV decreased from 5.6 dB to -3.4 dB. As was 

pointed out in Section 2.2.2, DP-01 in Set 3 did not correlate in the same way. Disregarding this 

exception, the correlation between BERTOV and INRTOV indicates that FEC plays a strong role in 

susceptibility. The effects of UWB interference on FEC performance is a topic for further study. 

4.2. Summary of Measured Signal Characteristics 

UWB signal characterization measurements were performed in the DTV victim signal 

bandwidth. Measured UWB signals were subjected to temporal, amplitude, and spectral 

analyses. Temporal analyses used BD and BI statistics and corresponding ζDTV estimates. 

Amplitude analyses used the APD and P/A. Finally, spectral analyses focused on the PSD. 

Temporal analyses of DP and DS signals showed that band-limiting elongated pulse width, w. 

This was evident in Table 4, which demonstrates that BD > w and ζDTV > ζ. For signals with Tpulse

less than or comparable to 1/BDTV, elongated pulses overlapped and the subsequent APD and P/A

approached Rayleigh amplitude statistics. For signals with Tpulse significantly greater than 1/BDTV, 

elongated pulses remained distinct and a step-like APD occurred with correspondingly high P/A. 

Similar results were observed with the MB signals; in these cases, however, band-limiting 

elongated on-time, τon, and shortened off-time, τoff. These changes were evident in Table 8, which 

demonstrated BD > τon, BI < τoff, and ζDTV > ζ. For signals with τoff less than or comparable to 

1/BDTV, elongated on-times overlapped and the subsequent APD and P/A approached Rayleigh 

amplitude statistics. For signals with τoff significantly greater than 1/BDTV, elongated on-times 

remained distinct and a step-like APD occurred with correspondingly high P/A. 

35 
Spectral analyses of DP, DS, and MB signals revealed flat power spectral densities like white 

Gaussian noise. A notable exception to this was DS-06 whose PSD sloped several dB over the 

DTV signal bandwidth. Theoretical analysis demonstrated that this was due to the DS code word 

spectral characteristics. Further comments on spectral analyses for bandwidths other than BDTV

can be found in Section 4.4. 

4.3. Correlations Between DTV Susceptibility and Signal Characteristics 

The second objective of this experiment was to determine if DTV susceptibility could be 

predicted from measured signal characteristics. Indeed, in Part 2 of this report series it was found 

that DTV susceptibility to gated noise interference could not be predicted by interference power 

alone. It was demonstrated that DTV susceptibility was also dependent on the temporal 

parameters of the gated noise signals, i.e., τon, τoff, and ζ. In this section, the analysis is taken one 

step further by plotting DTV susceptibility versus the band-limited metrics BD, BI, ζDTV, and P/A. 

Figures 38 and 39 summarize the temporal metrics of the UWB signals and illustrate how DTV 

susceptibility, i.e., ∆INRTOV, depends on these metrics. Figure 38 provides BI versus BD of the 

UWB signals, and Figure 39 provides ∆INRTOV as a function of ζDTV. In both plots, contours are 

drawn around the DTV susceptibility sets identified in Section 4.1. Signals within Set 1 have 

short BI < 1/BDTV and a wide range of longer BD. For these signals, the pulse period or gating offtime is less than 1/BDTV, and band-limiting caused overlapping. This either preserved or created 

signal characteristics that resembled continuous noise as evidenced by ζDTV near unity. Hence, 

INRTOV for signals within Set 1 resembles that of Gaussian noise. Signals within Set 2 have a 

wide range of BI > 1/BDTV and BD. For these signals, the pulse period or gating off-time is greater 

than or comparable to 1/BDTV, and band-limiting did not create a continuous interference signal as 

evidenced by ζDTV ranging from 0.05 to 0.4. The wide range of BD and BI for signals within Set 2 

caused a correspondingly wide range of ∆INRTOV below that of Gaussian noise, where the DTV 

receiver was most susceptible to signals with long BD and BI, e.g., MB-09, and least susceptible 

to signals with short BD and BI, e.g., MB-02 and DP-02. DP-01 in Set 3 has long BI >> 1/BDTV. 

For this signal, BD is much less than BI making ζDTV small. Hence, the victim receiver was 

exposed to interference the least amount of time, and ∆INRTOV is significantly greater than that of 

Gaussian noise. 

Contours drawn around signals within the DTV susceptibility sets, defined by ∆INRTOV alone, 

persist as regions when plotted against the temporal metrics BD, BI, and ζDTV. These findings 

suggest that DTV susceptibility categorization can be predicted from a priori knowledge of these 

band-limited metrics. Results suggest that UWB signals with ζDTV close to unity will generate 

interference much like Gaussian noise. Further, results suggest that UWB signals with ζDTV

approaching zero will generate benign interference. Finally, results suggest that UWB signals 

with 0.05 ≤ ζDTV ≤ 0.4 are likely to generate a range of interference effects more deleterious than 

Gaussian noise interference, which requires more knowledge to determine the specific impact on 

the victim receiver. For example, Figure 39 shows the signals clustering horizontally with those 

having the same number of bands. Within these clusters, signals are differentiated vertically by 

their dwell. Understanding this dependence on dwell required the in-depth study of the effects of 

gated noise on-time given in Part 2 of this report series. 

36 
Figure 38. BI versus BD of UWB interference. Contours are drawn around signals within the 

same DTV susceptibility set. 

Figure 39. ∆INRTOV versus ζDTV of UWB interference. Contours are drawn around signals 

within the same DTV susceptibility set. 

37 
Figure 40 provides ∆INRTOV versus P/A with contours drawn around the DTV susceptibility sets. 

Signals within Set 1 are in a horizontal line in the range 5.4 dB ≤ P/A ≤ 9.6 dB, which indicates 

that the peaks of these signals have negligible effect on ∆INRTOV. Signals within Set 2 follow a 

downward trend in the range 12.8 dB ≤ P/A ≤ 18.9 dB, which indicates that DTV susceptibility 

increases with increasing P/A. Exact determination of the P/A transitions between Sets 1 and 2 

and Sets 2 and 3 requires further investigation. 

Contours drawn around the signals within the DTV susceptibility signal sets, defined by ∆INRTOV

alone, persist as regions when plotted against P/A. This suggests that DTV susceptibility 

categorization can be predicted from a priori knowledge of the P/A metric. Results suggest that 

UWB signals with 5.4 dB ≤ P/A ≤ 9.6 dB will generate interference much like Gaussian noise. 

Further, results suggest that UWB signals with exceedingly high P/A will generate benign 

interference. Finally, results suggest that UWB signals with 12.8 dB ≤ P/A ≤ 18.9 dB are likely 

to generate a range of interference effects more deleterious than Gaussian noise interference, 

which requires more knowledge to determine the specific impact on the victim receiver. 

Figure 40. ∆INRTOV versus P/A of UWB interference. Contours are drawn around signals 

within the same DTV susceptibility set. 

In Section 4.1, it was mentioned that ∆INRTOV varied slightly with SNR in Sets 1 and 2. This 

variation manifests itself as vertical displacement of ∆INRTOV with SNR in Figures 39 and 40. 

Displacement of BD, BI, ζDTV, and P/A with SNR are not applicable since these metrics were 

derived from RF measurements. Hence, horizontal displacement of BD and vertical displacement 

of BI in Figure 38, horizontal displacement of ζDTV in Figure 39, and horizontal displacement of 

P/A in Figure 40 do not exist. 

38 
4.4. UWB Signal Emulation 

As stated previously, the last obje ine whether continuous and 

ated noise could be used to emulate DS and MB signals, respectively, in these and other 

vided temporal, amplitude, and spectral analyses for each of the 

ignals band-limited to BDTV. With two exceptions, these analyses demonstrated that DS signals 

,

gnals

were nearly identical 

r comparative signals. Hence, it appears reasonable to substitute continuous and gated noise 

N(MB) signals

annot be used in place of MB signals for susceptibility tests on victim receivers with narrower 

e

ctive of this study was to determ

g

susceptibility tests. This objective is important since gated noise is easier to implement and 

analyze than the UWB signals. 

The main body of this report pro

s

are similar to Gaussian noise. First, P/As of the DS signals were 0 – 3 dB less than P/A of 

Gaussian noise. Consequently, APDs of the DS signals deviated slightly from Rayleigh. Second

the PSD of DS-06 sloped several dB over the DTV signal bandwidth in contrast to the flat

spectrum of white Gaussian noise. This slope was attributed to the spectrum of the direct 

sequence codeword. Similarly, these analyses showed that gated noise was similar to MB si

with the exception that the P/A was 1 – 2 dB less than those of GN(MB). 

The similarities were also present in the DTV susceptibility results, which

fo

signals for DS and MB signals, respectively, when replicating this experiment. 

APD statistics as a function of frequency in Section B.4, however, suggest that G

c

bandwidths. These statistics show significant variation as a function of frequency when the 

signal is band-limited to 1.0 and 0.1 MHz. APD statistics versus frequency in the 1-MHz 

bandwidth case have a distinct periodic lobing pattern. APD statistics versus frequency in th

0.1-MHz bandwidth case have a distinct periodic spiking pattern centered at the pilot tone

frequency. These features are not present in the GN(MB) signals and require further analysis. 

39 
5. REFERENCES 

[1] “First Report and Order in the matter of ET Docket 98-153 (Revision of Part 15 of the 

Commission’s Rules Regarding Ultra-Wideband Transmission Systems),” FCC 02-48, 

adopted Feb. 14, 2002, released Apr. 22, 2002. 

[2] W.A. Kissick, Ed., “The temporal and spectral characteristics of ultrawideband signals,” 

NTIA Report 01-383, Jan. 2001. 

[3] J.R. Hoffman, M.G. Cotton, R.J. Achatz, R.N. Statz, and R.A. Dalke, “Measurements to 

determine potential interference to GPS receivers from ultrawideband transmission 

systems,” NTIA Report 01-384, Feb. 2001. 

[4] J.R. Hoffman, M.G. Cotton, R.J. Achatz, and R.N. Statz, “Addendum to NTIA Report 01-

384: Measurements to determine potential interference to GPS receivers from

ultrawideband transmission systems,” NTIA Report 01-389, Sep. 2001. 

[5] J.R. Hoffman, E.J. Haakinson, and Y. Lo, “Measurements to determine potential 

interference to public safety radio receivers from ultrawideband transmission systems,” 

NTIA Report 03-402, Apr. 2003. 

[6] M. Cotton, R. Achatz, J. Wepman, and B. Bedford, “Interference potential of 

ultrawideband signals: Part 1 – Procedures to characterize ultrawideband emissions and 

measure interference susceptibility of C-band satellite digital television receivers,” NTIA 

Report TR-05-419, Feb. 2005. 

[7] M. Cotton, R. Achatz, J. Wepman, and P. Runkle, “Interference potential of ultrawideband 

signals: Part 2 – Measurement of gated-noise interference to C-band satellite digital 

television receivers,” NTIA Report TR-05-429, Aug. 2005. 

[8] J.C. Whitaker, “Digital television transmission systems,” Ch. 13 in Standard Handbook of 

Video and Television Engineering, J.C. Whitaker, Ed., New York, NY: McGraw-Hill, 

2000. 

[9] F. Sanders, “Measurements of pulsed co-channel interference in a 4-GHz digital Earth 

station receiver,” NTIA Report 02-393, May 2002. 

40 
APPENDIX A: THEORETICAL PSD OF DP AND DS SIGNALS 

A general expression for the power spectral density (PSD) of ultrawideband (UWB) signals 

using a fixed time-base dither was provided in Section 3 of [2]. This section provides the 

derivation of the expression and uses it to evaluate the PSD of DP and DS signals. 

UWB signals that modulate pulses to convey binary data can be expressed as 

( ) ( ) ( ) ( ) ,

1

0

∑ 0 0 1 1 ∑ ∑

∞

= = −∞

∞

=−∞

= − − + − − = − − n k

kn k n

n

u t α n y t nT β n α n y t nT β n α y t nT β (A-1) 

where yk is the channel symbol, e.g., y0 represents a zero and y1 represents a one, T is the nominal 

symbol period, n is the symbol period index, and βn is a random variable that defines the 

dithering as described by the dither function q(β). αkn chooses the appropriate symbol for each 

information bit according to 

 

1 (with probability 1 ) .

0 (with probability ) and

( 1)

1 ( 0)

1 0

0

⎩

⎨

⎧

= − =

⎩

⎨

⎧

=

− = = ξ ξ

ξ

α n

n

n

kn a

a k

a k

This formulation can be altered to map any two distinct information bit values, e.g., {1, -1}, with 

no change in the final PSD expressions. Note that an and βn are independent and identically 

distributed (iid). 

The PSD is the Fourier transform of the autocorrelation function, i.e., , 

where the expectation operator, defined as 

( , ) { ( ) ( )} 2

*

1 2 1 R t t u t u t uu = Ε

{ } ∫ Ε X = xq(x)dx , is distributive and for independent 

random variables the expectation of the product is equal to the product of the individual 

expectations. The complex conjugate *

 can be dropped because u(t) is a real function, and the 

autocorrelation function is expressed as 

( , ) { } ( ) ( ) ( ) ( ) . , ,

1 2 1 2 1 2

⎭

⎬

⎫

⎩

⎨

⎧ = Ε = Ε ∑∑ − − − − n l m k

uu kn lm k n l mT m R t t u t u t α α y t nT β y t β

Note that summations involving n and/or m imply a range ±∞ , summations involving k and/or l

imply a range from 0 to 1, and integrals with unspecified limits imply the limits ±∞ . 

Evaluation of Ruu(t1, t2) involves summation of the function 

( , ) { } { ( ) ( )} , ,

1 2 = ∑Ε Ε 1 − − 2 − − k lnm kn lm k n l mT m γ t t α α y t nT β y t β

where the expectation was moved inside the summation operators and split into the product of 

expectations of the independent random variables. The expectation of the product of the channel 

41 
symbols is difficult to simplify in a meaningful way. To avoid this difficulty, the following 

variable is introduced 

ˆ ( , ) { } { } { ( )} { ( )} . ,

1 2 = ∑Ε Ε Ε 1 − − Ε 2 − − k l

nm kn lm k n l mT m γ t t α α y t nT β y t β

∑ ∑ ≠ ≠

=

n m

nm

n m

nm (t ,t ) ˆ (t ,t ) 1 2 1 2 γ γ because the symbols are independent in different symbol periods. 

However, because the symbols are not independent in the same

symbol period. Since both quantities are easily evaluated along the diagonal, is 

subtracted and is added to formulate the expression in a way that can be evaluated 

analytically, i.e., 

∑ ≠ ∑n

nn

n

nn (t ,t ) ˆ (t ,t ) 1 2 1 2 γ γ

∑n

nn ˆ (t ,t ) 1 2 γ

∑n

nn (t ,t ) 1 2 γ

( , ) ( , ) ˆ ( , ) [ ( , ) ˆ ( , )] . 1 2 1 2

,

1 2

,

1 2 = ∑ 1 2 =∑ + ∑ − n

nn nn

n m

nm

n m

uu nm R t t γ t t γ t t γ t t γ t t (A-2) 

As will be demonstrated, this approach has the added benefit of distinguishing between the 

discrete and continuous spectra of the resulting PSD. 

Consider the first term of equation (A-2), ∑n m

nm t t ,1 2 γˆ ( , ). Ε{αkn} is evaluated as 

{ } { }

{ } {1 } {1} { } .

(0) (1)

0 0

1 0 1 1

α ξ

α ξ ξ ξ

Ε = Ε − = Ε − Ε =

Ε = Ε = + =

n n n

n n

a a

a

Hence, Ε{αkn} = ξk is independent of n and can be moved outside ∑n, yielding 

Expanding the expectation into integral form and introducing = ∑ − n

φk (t) yk (t nT) gives 

ˆ ( , ) { } ( ) { ( ) . 1 2

,

1 2 ⎥

⎦

⎤ ⎢

⎣

⎡ Ε − − ⎥

⎦

⎤ ⎢

⎣

⎡ ∑ = ∑ ∑Ε − − ∑ ∑

l m

l l m

n

k n

k

k

n m

γ nm t t ξ y t nT β ξ y t mT β }

{ } ∑ ( ) ∑ ∫ ∫ Ε − − = − − = − = ∗ n

k k k

n

k n y (t nT β ) y (t nT β )q(β )dβ φ (t β )q(β )dβ φ q (t) ,

where ∗ is the convolutional operator. Defining the function = ∑

k

k k ψ (t) ξ φ (t) gives 

ˆ ( , ) [( )( )][( )( )] , 1 2

,

1 2 t t q t q t n m

∑γ nm = ψ ∗ ψ ∗

(A-3) 

42 
where the periodic function ψ(t) can be expressed as a Fourier series 

( ) . 1 ( ) ,

/ 2

/ 2

2 / 2 /

∑ ∫

−

− = Ψ Ψ =

T

T

j mt T

m

m

j mt T

m t e dt

T

t e π π ψ ψ

This allows for the convolution in equation (A-3) to be expressed as 

( )

,

( ) ( ) ( )

2 /

2 ( ) / 2 / 2 /

∑

∫∑ ∑ ∫

⎟

⎠

⎞ ⎜

⎝

⎛ = Ψ

∗ = Ψ = Ψ − −

m

j mt T

m

m

j mt T j m T

m

m

j m t T

m

e

T

m Q

q t e q d e q e d

π

π β π π β ψ β β β β

where Q is the Fourier transform of q. The Fourier coefficients in terms of ξk and yk are 

, 1 ( ) 1 2 /

∑ ∫ ∑ ⎟

⎠

⎞ ⎜

⎝

⎛ Ψ = ′ ′ = − ′

k

k k

j mt T

k

k

m k T

m Y

T y t e dtT ξ ξ π

where change of variable, t' = t – nT, was used to simplify and Yk is the Fourier transform of yk. 

Substitution into equation (A-3) and changing the independent variables to τ = t2 – t1 and t = t2

yields 

(A-4) [ ] . 1 ˆ ( , ) , ,

2 ( ) /

∑ ∑2 ∑ ∑ + − ⎟

⎠

⎞ ⎜

⎝

⎛ ⎟

⎠

⎞ ⎜

⎝

⎛ ⎥

⎦

⎤ ⎢

⎣

⎡ ⎟

⎠

⎞ ⎜

⎝

⎛ ⎥

⎦

⎤ ⎢

⎣

⎡ ⎟

⎠

⎞ ⎜

⎝

⎛ = n m m n

j m n t m T

k

k k

k

nm k k e

T

m Q T

n Q T

m Y

T

n Y

T

t π τ γ τ ξ ξ

The next term in equation (A-2) to be considered is 

( )( )

( ) ( ) ( ) ( ) ,

ˆ( , ) ( ) ( ) ( ) ( )

,

1 2

2 ( ) 2 ( )

1 2 1 2

,

1 2 1 2

1 2 1 1 2 2

∑ ∫∫ ∑

∑ ∑ ∑ ∫ ∫

− + +

⎥

⎦

⎤ ⎢

⎣

⎡ =

= − − − −

k l

j f t f t

n

j f f nT

k l k l

n l k n

k l k l

Y f Y f Q f Q f e e df df

t t y t nT q d y t nT q d

π π ξ ξ

γ ξ ξ β β β β β β

where ∫ ∫ − y t − nT − q d = Y f Q f e e df j fnT j f t

k k

π π β β β 2 2 ( . ) ( ) ( ) ( )

The term in square brackets may be expressed as the sum of delta functions using the identity 

. 2 1 ∑ ∑ ⎟

⎠

⎞ ⎜

⎝

⎛ = − −

n n

j fnT

T

n f T

e δ π (A-5) 

43 
Simple evaluation of the f2 integral, changing the independent variables to τ = t2 – t1 and t = t2, 

and consolidating the k and l terms yields 

( ) ( ) [ ] ( ) ( ) ( ) , 1

( ) ( ) 1 ˆ ( , )

2 / 2 / 2 /

2 / 2

1 2

∑ ∑ ∑

∑ ∑ ∫ ∑ ∑

⎥ ∗ ∗ −

⎦

⎤ ⎢

⎣

⎡ ⎟

⎠

⎞ ⎜

⎝

⎛ ⎟ ∗ − ⎠

⎞ ⎜

⎝

⎛ =

⎟

⎠

⎞ ⎜

⎝

⎛ − ⎥

⎦

⎤ ⎢

⎣

⎡ ⎟

⎠

⎞ ⎜

⎝

⎛ − ⎥

⎦

⎤ ⎢

⎣

⎡ = −

n

j n T j n T

l

l l

k

k k

j nt T

j f

l

l l

k

k k

n

j nt T

n

nn

e y y e q q e

T

f e df T

n f Q f Q Tn

e Y f Y

T

t t

π π τ π τ

π π τ

ξ τ ξ τ τ τ

γ ξ ξ

(A-6) 

where j n T

k

j f

k f e df y e

T

n Y 2 2 / ( ) π τ π τ ⎟ = −τ ⎠

⎞ ⎜

⎝

⎛ − ∫ . 

The last term to be evaluated in equation (A-2) is 

{αknαln} is independent of n, that is 

ence, Ε{αknαln } = ξk δkl, where δkl is the Kronecker delta function. Expanding the expectation 

tilizing equation (A-5) to evaluate the f2 integral, changing independent variables to τ = t2 – t1

(A-7)

( , ) { } { ( ) ( )} . ,

∑ 1 2 =∑ ∑Ε Ε 1 − − 2 − − n l k

kn kn k n l n

n

γ nn t t α α y t nT β y t nT β

Ε

{ } { }

H

into integral form, taking the double Fourier transform, and consolidating n and β terms yields

U

and t = t2, rearranging terms, and recognizing the Fourier transform with respect to τ yields

{ } { } { } { } { }

{ } { } {(1 ) } { } { } 0 .

(1 ) 1 2

2

0 1 1 0

0

2 2

0 0

(0) (1) 1 1

2

0

2

1 1

Ε = Ε = Ε − = Ε − Ε =

Ε = Ε − = Ε − Ε + Ε =

Ε = Ε = + =

n n n n n n n n

n n n n n

n n n

a a a a

a a a

a

α α ν ν

α α ξ

α α ξ ξ ξ

( ) ( ) [ ] ( ) .

( , ) ( ) ( ) ( )

1 2

2 ( ) 2 ( ) 2 ( )

1 2

1 2 1 2

1 2 1 2 1 1 2 2

∑ ∫∫ ∑ ∫

∑ ∑∫

− + − + +

⎥

⎦

⎤ ⎢

⎣

⎡ =

= − − − −

k

j f f j f t f t

n

j f f nT

k k k

k n

k k k

n

nn

Y f Y f e q e d e df df

t t y t nT y t nT q d

π π β π ξ β β

γ ξ β β β β

2

∑

( ) ( ) ( ) . 1 2 / 2 /

∑ ∑

∫

⎟ ∗ − ⎠

⎞ ⎜

⎝

⎛ =

⎟

⎠ ⎜⎝ ⎟⎠ ⎜⎝

n k

j n T

k k k

j nt T

n

k k

k

k

n

nn

y y e

T

n

e Q T

T T T

π π τ ξ τ τ

( ) 1 ( , ) 2 / 2

∑ ∑ ∑ ⎛ ⎞ − ⎛ ⎞ = j nt T − j f f e df n Y f Y n

t e Q π π τ γ τ ξ

44 
Equations (A-2), (A-4), (A-6), and (A-7) combine to give an expression for the autocorrelation 

is

valuating this integral involves the integral identity

here k is an integer. Hence, the time average of equation (A-4) is non-zero only for n = -m, and 

inally, taking the Fourier transform of

function in terms of τ and t. The statistics for Ruu(τ, t) are periodic with period T. Such processes

are commonly referred to as cyclostationary. For these processes, it is useful to calculate the 

average over all possible observation times within a period. The time average over one period

denoted as follows 

( ) ( , ) .

0

∫ uu = Ruu t dt

T

R τ τ

1 T

E

0 (otherwise) , 0

2 /

⎩ ∫ e dt = ⎨ T

j π kt T

w

the time average of equations (A-6) and (A-7) are non-zero only for n = 0. The time-average 

autocorrelation function reduces to 

1 ⎧1 (k = 0) T

( ) ( ) ( ) ( ) [ ] ( ) ( ) , 1

1 ( ) 2 /

2

2

⎪⎭

⎪

⎬

⎫

⎪⎩

⎪

⎨

⎧

⎥ ∗ ∗ −

⎦

⎤ ⎢

⎣

⎡ ⎟

⎠

⎞ ⎜

⎝

⎛ ⎟ ∗ − ⎠

⎞ ⎜

⎝

⎛

+ ∗ − −

⎟

⎠

⎞ ⎜

⎝

⎛ ⎟

⎠

⎞ ⎜

⎝

⎛ =

∑ ∑ ∑

∑ ∑

ξ τ τ ξ τ ξ τ τ τ

τ ξ π τ

y y y y q q T

e

T

n Q T

n Y

T

R

k

k k

k

k k

k

k k k

n

j n T

k

uu k k

2

where Q(0) is the integrated probability density function q(β) equal to 1. 

(τ ) Ruu yields 

(A-8) 

ol spectrum

F

{ } ( )

( ) ( ) ( ) , 1

( ) 1 ( ) FT ( )

2

2

2

2

2

⎪⎭

⎪

⎬

⎫

⎪⎩

⎪

⎨

⎧

+ −

⎟

⎠

⎞ ⎜

⎝

⎛ = = −

∑ ∑

∑ ∑

Y f Y f Q f T

T

n Y f Q f f T

S f R

k

k k

k

k k

k n

uu uu k k

ξ ξ

τ ξ δ

2

which is comprised of discrete and continuous components that depend on the symb

and the Fourier transform of the density function used to randomize the signal. 

45 
A.1. DP-UWB 

For DP signals, q(β) is uniformly distributed (and more importantly symmetric); hence, the 

signal can be expressed according to the general expression (A-1). The DP channel symbol y1 is 

a time advanced version of y0 defined as 

( ) ( ) , 2 1 0 y t p t

T

y t DP

max ⎟ = ≡ ⎠

⎞ ⎜

⎝

⎛ + β

where βmax is the dither fraction and pDP(t) is the pulse shape. Assuming equiprobable DP 

information bits, i.e., ξk = 1⁄2, and knowing that time shift translates to a phase shift in the 

frequency domain results in 

( ) [ ] 1 cos( ) . 2

1 ( ) 1

4

1 ( )

( ) ( ) ( ) 2

1 ( )

2 2 2

2

2 2 2 2 2 2 max

Y f P f e P f f T

Y f p t e dt e p t e dt P f

DP max

j f T

DP

k

k k

DP

j f t

DP

j f t j f T

k DP

k

k

max ξ π β

ξ

π β

π π β π

= + = +

=⎥⎦

⎤ ⎢⎣

⎡ = +

∑

∑ ∫ ∫ − −

Substitution in equation (A-8) yields 

[ ] ( )

[ ] ( ) . 2

( ) 1 cos

( ) 1 1

( ) ( ) 1 cos

2

1 ( )

2

2

2

2

⎪⎭

⎪

⎬

⎫

⎪⎩

⎪

⎨

⎧ +

+ −

⎟

⎠

⎞ ⎜

⎝

⎛ = + ∑ −

Q f f T

P f T

T

n P f Q f f T f T

S f

max

DP

n

uu DP max

π β

π β δ

Figures A-1 – A-4 illustrate the power spectral densities of DP-01 – DP-04, respectively. The 

magnitudes of the spectra were normalized to the peak of the continuous spectrum. For DP-01 – 

DP-04, q(β) is uniformly distributed over half of the pulse period. Consequently, βmax = 0.5 and 

Q(f ) = sinc(πβmaxTf ). This sinc function has nulls at frequencies equal to 2k/T (k = ±1, ±2, ...), 

which zeros out every other spectral line and causes the spacing between discrete spectral lines 

to be 2/T. In these plots, the vertical shaded regions in the top plots correspond to the DTV 

channel displayed in the bottom plots. Notice that in all cases the spectral lines were either below 

the continuous spectrum or outside the DTV channel. 

46 
Figure A-1. Theoretical discrete and continuous spectra of DP-01. 

Figure A-2. Theoretical discrete and continuous spectra of DP-02.

47 
Figure A-3. Theoretical discrete and continuous spectra of DP-03. 

Figure A-4. Theoretical discrete and continuous spectra of DP-04. 

48 
A.2. DS-UWB

DS channel symbols are not dithered, i.e., Q(f ) = FT{q(β)} = FT{δ(0)} = 1. They are defined as 

the convolution of a codeword and the DS pulse shape (pDS), i.e., 

( ) ( ) ( ) ,

1

0

1 0 ∑

−

=

− = ≡ −

L

l

l DS chip y t y t c p t lT

where L is the codeword length with values of {1, 3, 6, 12, or 24}, cl is the l

th codeword chip 

with values {-1, 0, 1}, and Tchip is the chip period. Assuming DS information bit values are 

equiprobable, the negative relation between y1 and y0 makes 

[ ] ( ) ( ( )) 0 , 2

1 ( ) 2

0 0

2

= + − = ∑ ∫ − Y f y t y t e dt j f t

k

k k

π ξ

and causes the discrete component of the DS-UWB PSD to be zero. The other sum in equation 

(A-7) evaluates to 

( ) ( ) ,

( )

( ) ( )

2 2

2 1

0

2 2

2 1

0

2 2

P f C f

P f c e

Y f c p t lT e dt

DS

L

l

j f lT

DS l

k

L

l

j f t

k k l DS chip

chip

=

=

= −

∑

∑ ∑ ∫

−

=

−

−

=

−

π

π ξ

and substitution into equation (A-8) yields 

( ) ( ) . 1 ( ) 2 2P f C f TS f uu = DS

Figures A-5 and A-6 illustrate |C(f)| for DS-04 and DS-06, respectively. In these plots, the 

magnitudes of the spectra were normalized to their peak, and the vertical shaded regions in the 

top plots correspond to the DTV channel displayed in the bottom plots. Notice the resemblance 

between the |C(f)| and the measured PSD of DS-06 illustrated in Section 2.3.3. This agreement is 

because |PDS(f)| is flat over the frequency range 3.7 – 4.2 GHz as illustrated in Figure 3 of Part 1 

[6]. Not shown in this appendix are frequency flat sparse codes for DS-01, DS-02, DS-03, and 

DS-05, which produce the flat measured PSDs shown in Section 2.3.3. 

49 
Figure A-5. |C(f)| of the DS-04 code word. 

Figure A-6. |C(f)| of the DS-06 code word. 

50 
APPENDIX B. CHARACTERIZATION MEASUREMENTS 

This appendix provides a thorough description of the measurement procedures and processing 

used to characterize the ultrawideband (UWB) signals. It provides an extensive set of temporal, 

amplitude, and spectral analysis results that support Sections 2.3 and 3.3.

B.1. Measurement Setup 

The UWB signals were measured under optimal conditions at the radio frequency (RF) output of 

the vector signal generator (VSG) as described in Figure B-1. Measurements at RF were made 

with the vector signal analyzer (VSA) and digital oscilloscope (DO). 

Figure B-1. Setup for RF signal characterization measurements. 

Prototype DS and MB devices were made available for these tests; however, we chose to 

generate simulated signals with a VSG to have more control over modulation parameters and test 

conditions. Prototype DS and MB signals were characterized to verify corresponding VSG 

signals. Characteristics of the prototype DS signals matched those of the VSG DS signals. 

General characteristics of the prototype MB signals resembled those of the VSG MB signals. 

However, differences attributed to local-oscillator (LO) feed-through in the prototype MB 

signals were observed. Prototype-generated signal characterization measurements are not 

included in this report. 

The VSG was set up with the procedures described in Appendix B of Part 1 [6]. UWB 

waveforms were created via software simulation, down-conversion to baseband, and decimation 

to the sampling frequency of the VSG. In order to ensure optimal use of the analog-to-digital 

converters in the VSG, DP and DS signals were normalized according to their maximum values 

shown in Table B-1. In contrast, MB-02 – MB-09 were normalized by the maximum value of 

MB-01 from which they were derived. In the composite plots of Section 2.3, discrepancies due to 

different normalization factors were removed so the relative average powers are proportional to 

Tpulse. Plots in this appendix, however, were not adjusted according to the individual 

normalization factors. 

VSA instrument settings are summarized in Table B-2. As discussed in Appendix E of Part 1, 

VSG amplitudes were adjusted to ensure that the dynamic range of the VSA was optimally 

utilized. Table B-1 provides the VSG amplitudes used for RF signal characterization of DP and 

DS signals. The VSG amplitude for MB signals was -28.62 dBm.

51 
Table B-1. Maximum Waveform Values and VSG Amplitudes for RF VSA Measurements 

Type Index Maximum VSG Amplitude (dBm)

01 0.014

02 0.014

03 0.018 DP 

04 0.053

-31.61 

01 0.048 -29.86

02 0.025 -30.71

03 0.016 -31.62

04 0.032 -33.31

05 0.009 -33.61

DS 

06 0.029 -33.23

Table B-2. RF VSA Measurement Settings 

Post-Processing 

Bandwidths 

(MHz) 

Span 

(MHz) 

Number of 

Samples 

Center 

Frequency 

(MHz) 

Input Range 

(dBm) 

36, 19.51, 10 36 > 360,000 

1 4.5 > 450,000

0.1 0.5625 > 562,500

3820 -30

DO measurements at the maximum sample rate, i.e., 20 GSps, provided real, time-domain 

representations of RF signals. DO measurements were made with the VSG output level set to a 

higher value, i.e., 0 dBm, to compensate for low DO sensitivity at the maximum sample rate. 

UWB interference signals were also measured at the IF output of the low-noise block 

downconverter (LNB) with the setup described in Figure 20 of Part 1 with the VSG output level 

corresponding to INRTOV. The simplified block diagram of the hardware components that affect 

the IF signal characterization measurements is shown in Figure B-2. Bandpass filter BPF1 has a 

1-dB bandwidth equal to 40 MHz. 

Figure B-2. Simplified setup for IF signal characterization measurements. 

Measurements at IF were made with the VSA only. VSA settings for IF measurements were the 

same as those used for RF measurements described in Table B-2, except the center frequency 

was set to 1330 MHz. 

52 
B.2. Temporal Analysis

Time or crossing statistics are provided via the pulse duration distribution (PDD) and the pulse 

interval distribution (PID). PDD is presented in terms of the percentage of pulses that exceed 

various time durations in seconds. It provides statistics on how long a signal crosses and stays 

above a specified threshold. PID gives the probability distribution for the times a signal falls and 

stays below a threshold. PDD and PID are plotted on Rayleigh graph where the ordinate is 

plotted on a log scale. Poisson-distributed crossings with exponentially-distributed PD and PI

values would plot as a straight line on this graph. 

Figure B-3 is an illustration of PD statistics from VSA measurements of the gated-noise signal, 

GN-10, i.e., τon = 1 μs and 50% duty cycle, when the crossing threshold is set to -70 dBm. There 

are three PD categories: non-interrupted on-times in black, interrupted on-times in green, and 

anomalous spikes in red. Non-interrupted pulse durations are identified by the horizontal portion 

at low percentiles. Nearly 40% of PDs are approximately 1.13 μs corresponding to a τon slightly 

broadened by band-limiting. 

Figure B-3. Pulse duration statistics of gated noise with 50% duty cycle and 1-μs on-time. 

Figure B-4 is an illustration of PI estimates from VSA measurements of GN-10 when the 

crossing threshold is set to -70 dBm. Interestingly, the interrupted off-time category is absent 

because there are negligible disruptions from higher amplitudes. The resulting PID is nearly a 

step function. Similar to the PD analysis, non-interrupted PI estimates are identified by the 

horizontal portion at low percentiles.

53 
Figure B-4. Pulse interval statistics of gated noise with 50% duty cycle and 1-μs on-time. 

Figure B-5 is an illustration of PI estimates from VSA measurements of complex Gaussian 

noise, GN-01, when the crossing threshold is set to -70 dBm. For the given measurement 

procedure, this choice for the crossing threshold is too low to quantify meaningful time statistics 

of continuous signals. As illustrated, GN-01 only triggered time statistic estimates at anomalous 

noise spikes. Therefore, it is useful to provide curves for a range of crossing thresholds. 

Figure B-5. Pulse interval statistics of complex Gaussian noise. 

Figures B-6 – B-24 provide PDD and PID for the UWB signals when the crossing threshold was 

set to mean amplitude, -50 dBm, -60 dBm, and -70 dBm. Tenth percentile PD and PI estimates 

when the crossing threshold was set to -70 dBm were chosen as meaningful metrics to quantify 

the on- and off-times of band-limited signals and were specified in the main text as burst 

duration (BD) and burst interval (BI), respectively. 

54 
Figure B-6. RF temporal analyses of DP-01 (Tpulse = 10,000 ns, w = 0.094 ns, fD = 0.5).

55 
Figure B-7. RF temporal analyses of DP-02 (Tpulse = 1000 ns, w = 0.094 ns, fD = 0.5).

56 
Figure B-8. RF temporal analyses of DP-03 (Tpulse = 100 ns, w = 0.094 ns, fD = 0.5).

57 
Figure B-9. RF temporal analyses of DP-04 (Tpulse = 10 ns, w = 0.094 ns, fD = 0.5).

58 
Figure B-10. RF temporal analyses of DS-01 (L = 1).

59 
Figure B-11. RF temporal analyses of DS-02 (L = 3, sparse code).

60 
Figure B-12. RF temporal analyses of DS-03 (L = 6, sparse code).

61 
Figure B-13. RF temporal analyses of DS-04 (L = 12, DS code).

62 
Figure B-14. RF temporal analyses of DS-05 (L = 12, sparse code).

63 
Figure B-15. RF temporal analyses of DS-06 (L = 24, DS code).

64 
Figure B-16. RF temporal analyses of MB-01 (b = 1).

65 
Figure B-17. RF temporal analyses of MB-02 (b = 3, d = 1).

66 
Figure B-18. RF temporal analyses of MB-03 (b = 3, d = 2).

67 
Figure B-19. RF temporal analyses of MB-04 (b = 7, d = 1).

68 
Figure B-20. RF temporal analyses of MB-05 (b = 7, d = 2).

69 
Figure B-21. RF temporal analyses of MB-06 (b = 7, d = 6).

70 
Figure B-22. RF temporal analyses of MB-07 (b = 13, d = 1).

71 
Figure B-23. RF temporal analyses of MB-08 (b = 13, d = 2).

72 
Figure B-24. RF temporal analyses of MB-09 (b = 13, d = 12). 

73 
B.3. Amplitude Analysis 

This subsection provides measured time series and amplitude probability distributions (APDs) of 

the UWB signals. Odd numbered plots in Figures B-25 – B-62 provide RF measurement results 

organized as: 

(a) Real time series measured with the DO and amplitude time series measured with the 

VSA and band-limited to BDTV = 19.51 MHz. 

(b) APDs measured with the VSA and band-limited to 36, BDTV, 10, 1, and 0.1 MHz. 

Even numbered plots in Figures B-25 – B-62 provide IF measurement results organized as: 

(a) Amplitude time series measured with the VSA and band-limited to BDTV. 

(b) APDs measured with the VSA and band-limited to BDTV. 

Table B-3 provides peak-to-average (P/A) values for the UWB signals measured at RF and bandlimited to various bandwidths in post-measurement processing. Table B-4 provides P/A values 

for the UWB signals measured at IF under TOV operational conditions and band-limited to BDTV

in post-measurement processing. 

Table B-3. Measured RF P/A (dB) of UWB Signals Band-Limited to Different Bandwidths‡

Type Index 36.0 MHz BDTV 10.0 MHz 1.0 MHz 0.1 MHz 

01 25.4 23.5 20.6 11.5 6.8

02 15.7 13.8 11.0 6.1 9.4 

03 7.8 5.4 6.0 9.0 10.1 DP 

04 7.7 8.1 9.0 9.4 9.4 

01 9.3 9.5 9.5 9.5 9.5 

02 8.8 9.0 9.5 9.8 9.6 

03 7.8 8.1 8.8 9.9 9.7 

04 6.8 6.6 8.0 9.6 9.6 

05 6.8 6.6 8.0 9.8 9.8 

DS 

06 6.6 6.8 8.3 9.5 9.8 

01 9.6 8.3 6.9 7.5 9.2 

02 13.5 12.8 11.1 5.6 8.6

03 13.8 12.8 11.3 7.4 8.7

04 16.9 16.2 14.7 6.4 8.1

05 17.1 16.4 14.8 10.8 8.2

06 17.2 16.3 15.0 14.8 10.0 

07 19.4 18.7 17.3 8.6 7.4

08 19.4 18.9 17.3 13.3 7.6

MB 

09 19.4 18.8 17.4 17.7 14.9

 

‡

 Shaded cells highlight Rayleigh-amplitude statistics. 

74 
Table B-4. Measured IF P/A (dB) of UWB Signals at INRTOV and Band-Limited to BDTV

§

Type Index SNR = 9 dB SNR = 12 dB SNR = 15 dB 

01 23.4 ? ?

02 13.2 14.0 14.1

03 8.9 7.9 7.2 DP 

04 9.3 8.9 8.7

01 9.6 9.4 9.4 

02 9.5 9.0 9.1 

03 9.1 8.8 8.6

04 9.1 8.1 7.8

05 8.9 8.4 7.7

DS 

06 9.4 8.9 8.4

01 9.6 9.3 9.0 

02 11.7 12.7 12.8

03 11.9 12.4 12.5

04 13.6 15.1 15.6

05 12.8 14.5 15.2

06 12.4 14.0 15.2

07 15.0 16.6 17.8

08 14.0 16.0 17.2

MB 

09 12.7 14.6 16.2

 

§

 Shaded cells highlight Rayleigh-amplitude statistics. Question marks indicate uncertainty in the measurement due

to exceedingly high signal voltages overdriving the VSA. 

75 
Figure B-25. RF amplitude analyses of DP-01 (Tpulse = 10,000 ns, w = 0.094 ns, fD = 0.5). 

76 
Figure B-26. IF amplitude analyses of DP-01 at INRTOV. 

77 
Figure B-27. RF amplitude analyses of DP-02 (Tpulse = 1000 ns, w = 0.094 ns, fD = 0.5). 

78 
Figure B-28. IF amplitude analyses of DP-02 at INRTOV. 

79 
Figure B-29. RF amplitude analyses of DP-03 (Tpulse = 100 ns, w = 0.094 ns, fD = 0.5). 

80 
Figure B-30. IF amplitude analyses of DP-03 at INRTOV. 

81 
Figure B-31. RF amplitude analyses of DP-04 (Tpulse = 10 ns, w = 0.094 ns, fD = 0.5). 

82 
Figure B-32. IF amplitude analyses of DP-04 at INRTOV. 

83 
Figure B-33. RF amplitude analyses of DS-01 (L = 1).

84 
Figure B-34. IF amplitude analyses of DS-01 at INRTOV. 

85 
Figure B-35. RF amplitude analyses of DS-02 (L = 3, sparse code).

86 
Figure B-36. IF amplitude analyses of DS-02 at INRTOV.

87 
Figure B-37. RF amplitude analyses of DS-03 (L = 6, sparse code).

88 
Figure B-38. IF amplitude analyses of DS-03 at INRTOV.

89 
Figure B-39. RF amplitude analyses of DS-04 (L = 12, DS code).

90 
Figure B-40. IF amplitude analyses of DS-04 at INRTOV.

91 
Figure B-41. RF amplitude analyses of DS-05 (L = 12, sparse code).

92 
Figure B-42. IF amplitude analyses of DS-05 at INRTOV.

93 
Figure B-43. RF amplitude analyses of DS-06 (L = 24, DS code).

94 
Figure B-44. IF amplitude analyses of DS-06 at INRTOV.

95 
Figure B-45. RF amplitude analyses of MB-01 (b = 1).

96 
Figure B-46. IF amplitude analyses of MB-01 at INRTOV.

97 
Figure B-47. RF amplitude analyses of MB-02 (b = 3, d = 1).

98 
Figure B-48. IF amplitude analyses of MB-02 at INRTOV.

99 
Figure B-49. RF amplitude analyses of MB-03 (b = 3, d = 2).

100 
Figure B-50. IF amplitude analyses of MB-03 at INRTOV.

101 
Figure B-51. RF amplitude analyses of MB-04 (b = 7, d = 1).

102 
Figure B-52. IF amplitude analyses of MB-04 at INRTOV.

103 
Figure B-53. RF amplitude analyses of MB-05 (b = 7, d = 2).

104 
Figure B-54. IF amplitude analyses of MB-05 at INRTOV.

105 
Figure B-55. RF amplitude analyses of MB-06 (b = 7, d = 6). 

106 
Figure B-56. IF amplitude analyses of MB-06 at INRTOV.

107 
Figure B-57. RF amplitude analyses of MB-07 (b = 13, d = 1). 

108 
Figure B-58. IF amplitude analyses of MB-07 at INRTOV.

109 
Figure B-59. RF amplitude analyses of MB-08 (b = 13, d = 2). 

110 
Figure B-60. IF amplitude analyses of MB-08 at INRTOV.

111 
Figure B-61. RF amplitude analyses of MB-09 (b = 13, d = 12). 

112 
Figure B-62. IF amplitude analyses of MB-09 at INRTOV. 

113 
B.4. Spectral Analyses

The spectral analyses provided in this subsection were derived from VSA measurements and 

intended to emulate the swept spectrum analyzer (SA) measurements described in Table B-5. 

Complex samples measured in a 36-MHz VSA span were frequency shifted so that the frequency 

of interest was centered at 0 Hz. Next, the signal was band-limited to a resolution bandwidth 

(RBW) of 1 MHz or 0.1 MHz using a root-raised cosine filter with α = 0.35. Mean, median, and 

peak statistics were computed for the resulting band-limited complex-baseband data. 

Table B-5. Spectrum Analyzer Settings for Characterizing UWB Signals 

Center 

Frequency 

(MHz) 

Span (MHz) 

Resolution 

Bandwidth 

(MHz) 

Video 

Bandwidth 

(MHz) 

Number of 

Frequency 

Steps 

Sweep Time

(seconds) Detector

3950 600 1 3600 10.8

3820 40 0.1 50 2400 72.0 Rms, peak 

These RBWs are smaller than that of the victim digital television channel; however, results 

provide mean and peak estimates relevant to possible narrowband circuitry within the receiver. 

Frequencies of interest spanned the bandwidth of the satellite channel with a frequency step size 

set to one tenth of RBW to ensure that spectrum details were not missed. 

Figures B-63 – B-81 provide spectral statistics for the UWB signals: Figures B-63 – B-66 

correspond to DP-01 – DP-04, Figures B-67 – B-72 correspond to DS-01 – DS-06, and Figures 

B-73 – B-81 correspond to MB-01 – MB-09. SA measurements were made and show agreement 

with the VSA measurement results; SA measurements are not included in this report. 

The most notable trend was frequency-dependent variation in the MB peak amplitude statistics. 

This behavior is related to the location and modulation of the data and pilot tones of the MB 

signals, and is the primary difference between MB and GN(MB) signals. GN(MB) peak statistics 

are flat versus frequency as demonstrated theoretically in Section C.2 in Part 2 [7]. 

A notable example of this trend is MB-02 in a 0.1-MHz RBW. The pilot tone in the band of 

interest, located at -4.375 MHz, caused spikes in the peak spectra at intervals of 1⁄2 the reciprocal 

gating repetition rate, i.e., 0.533 MHz. Although this feature is evident in the 1-MHz RBW, the 

more prominent feature is the cyclic variation of all peak statistics. Interestingly, the nulls in the 

cyclic variation correspond to center frequencies of the data and pilot tones.

114 
Figure B-63. RF spectral analyses of DP-01 (Tpulse = 10,000 ns, w = 0.094 ns, fD = 0.5).

115 
Figure B-64. RF spectral analyses of DP-02 (Tpulse = 1000 ns, w = 0.094 ns, fD = 0.5).

116 
Figure B-65. RF spectral analyses of DP-03 (Tpulse = 100 ns, w = 0.094 ns, fD = 0.5). 

117 
Figure B-66. RF spectral analyses of DP-04 (Tpulse = 10 ns, w = 0.094 ns, fD = 0.5).

118 
Figure B-67. RF spectral analyses of DS-01 (L = 1).

119 
Figure B-68. RF spectral analyses of DS-02 (L = 3, sparse code).

120 
Figure B-69. RF spectral analyses of DS-03 (L = 6, sparse code).

121 
Figure B-70. RF spectral analyses of DS-04 (L = 12, DS code).

122 
Figure B-71. RF spectral analyses of DS-05 (L = 12, sparse code).

123 
Figure B-72. RF spectral analyses of DS-06 (L = 24, DS code).

124 
Figure B-73. RF spectral analyses of MB-01 (b = 1).

125 
Figure B-74. RF spectral analyses of MB-02 (b = 3, d = 1).

126 
Figure B-75. RF spectral analyses of MB-03 (b = 3, d = 2).

127 
Figure B-76. RF spectral analyses of MB-04 (b = 7, d = 1).

128 
Figure B-77. RF spectral analyses of MB-05 (b = 7, d = 2).

129 
Figure B-78. RF spectral analyses of MB-06 (b = 7, d = 6).

130 
Figure B-79. RF spectral analyses of MB-07 (b = 13, d = 1).

131 
Figure B-80. RF spectral analyses of MB-08 (b = 13, d = 2).

132 
Figure B-81. RF spectral analyses of MB-09 (b = 13, d = 12). 

133 
FORM NTIA-29 U.S. DEPARTMENT OF COMMERCE 

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

BIBLIOGRAPHIC DATA SHEET 

1. PUBLICATION NO. 

TR-06-437 

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

5. Publication Date 

February 2006 

4. TITLE AND SUBTITLE 

Interference Potential of Ultrawideband Signals --- Part 3: Measurements of 

Ultrawideband Interference to C-Band Satellite Digital Television Receivers 6. Performing Organization Code 

511-6592000-300

7. AUTHOR(S) 

Michael Cotton, Robert Achatz, Jeffery Wepman, and Roger Dalke 

9. Project/Task/Work Unit No.

8. PERFORMING ORGANIZATION NAME AND ADDRESS 

NTIA/ITS

U.S. Department of Commerce 

325 Broadway

Boulder, CO 80305

10. Contract/Grant No.

11. Sponsoring Organization Name and Address 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 provides results from tests that measured digital television (DTV) susceptibility to ultrawideband (UWB) 

interference. A test system was developed to inject interference with known characteristics into a victim receiver and 

quantitatively measure susceptibility. In this experiment, a C-band satellite DTV victim receiver was injected with 

Dithered-Pulse (DP), Direct-Sequence (DS), and Multi-Band OFDM (MB) UWB interference. Results showed that 

the UWB signals could be categorized into three signal sets of common DTV susceptibility behavior. Interestingly, 

the categorized signals, band-limited by the DTV receiver filter, also had common characteristics. Set 1 consists of 

signals whose DTV susceptibility and band-limited signal characteristics resemble Gaussian noise. Set 2 consists of

signals more deleterious than Gaussian noise interference. Notably, these signals had a wide range of band-limited 

signal characteristics and susceptibilities. Set 3 consists of a signal that is relatively benign. Results also showed that 

measurable band-limited characteristics, e.g., burst duration (BD), burst interval (BI), fractional on-time (ζDTV), and 

peak-to-average ratio (P/A), of the interfering signal are useful for predicting susceptibility. Finally, it was 

determined that continuous and gated noise signals can be used to emulate the interference effects of DS and MB 

signals for the DTV victim receiver and operational scenarios tested in this study. This might not be true, however, 

for testing the susceptibility of other victim receivers operating in narrower bandwidths as indicated by amplitude 

probability distributions as a function of frequency for MB signals band-limited to relatively narrow bandwidths. 

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

Digital television; interference; satellite communications; ultrawideband

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