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Kenneth Rice, Joel Simoneau, and Dr. L. Wilson Pearson The purpose of this research is to implement two baseband communication algorithms: Pulse Position Modulation (PPM) and Pulse Amplitude Modulation (PAM). The two techniques implemented to demodulate PPM and PAM are the Matched Filter and Time Limited Accumulation (TLA) filter. Another purpose of this research is to test several implementations for demodulating PPM for efficiency and productivity. This is done using two noise channel models: Direct/Reflected Path Noise and Random Inversion Noise. The amplitude of the pulses denote the transmitted information. An example is shown in Figure1A. The location of the pulse within the specified transmission frame indicates the transmitted information. Figure1B gives an example of this kind of modulation. Matched Filter: Modulation Techniques Demodulation Techniques Time Limited Accumulation Filter: Introduction Direct/Reflected Path Noise Model: Random Inversion Noise Model: Summer Undergraduate Research Experience Noise Channel Models When the transmitted signal changes path during transmission in such a way that the signal becomes inverted. Figure3A is an example. A more complicated version of the Direct/ Reflected Path Noise Model. This can be seen in Figure3B PAM Implementations: PAM : R EC EIVER xlbalance z -k -1 Sync Scope2 xlrelational z -1 a b a>b en R elational p s PtoS5 fptdbl Out2 z -3 a b (ab) Mult O ut M atched xlconvert cast C onv1 1 C on8 0 C on5 52 C on3 xladdsub z -1 a-b a b a AddSub2 q b rst Accum Out1 Out2 Out3 AD C Receiver (Matched): PPM Implementations: PAM : TR AN SM ITTER O ut D igital Input In O ut DSP In1 In2 Out1 Out2 Out3 D AC 2 0.20313 Cont1 xladdsub z -1 a+b a b a AddSub1 Transmitte r: ONE ZERO In1 Signal F.H alf R eset S.H alf Enable Tim ing C ontroller Scope2 xlrelational z -1 a b a<b en R elate2 fpt dbl Out4 Out1 Out2 Out3 ADC InO ut ABS q b en rst 2A ccum q b en rst 1A ccum PPM : M ATC H ED FILTER R EC EIVER In1 Out1 Out2 Out3 Timing xlbalance z -k -1 Sync Scope2 xlrelational z -1 a b a<b en R elational2 fptdbl Out4 z -3 a b (ab) M ult2 O ut M atched W aveform 0 C on7 q b rst Accum Out1 Out2 Out3 AD C PAM : TR AN SM ITTER ZERO ONE xlp2s ps PtoS6 xlp2s ps PtoS10 xlm ux sel d0 d1 d1 M ux1 O ut D igital Input In O ut DSP In1 In2 Out1 Out2 Out3 DAC 2 3.277e+004 C on8 1024 C on14 Transmitter: Receiver (Matched): Receiver (TLA): Testin g Design 101 bits 1001 bits Matched 44 errors N/A Matched (Altered) 0 errors 0 errors TLA 0 errors 5 errors TLA (Altered) 0 errors 0 errors Direct/Reflected Path Results Design 101 bits 1001 bits Matched 42 errors N/A Matched (Altered) 24 errors 266 errors TLA 0 errors N/A TLA (Altered) 24 errors 266 errors Random Inversion Results Future Work Algorithm Implementation References [1] L.C. Ludeman, Fudamentals of Digital Signal Processing. New York: Harper and Row, 1986. [2] M.B. Pursley, Introduction to Digital Communications. New Jersey: Pearson Prentice Hall, 2005. Figure1 A Figure 1B Figure2 A Figure2 B Pulse Position Modulation: Figure3 A Figure3 B Figure4 A Figure4 B Figure4A shows the Xilinx blocks used in MATLAB’s Simulink to implement PAM. Graph1A shows the transmission of ‘001100’. Pulse Amplitude Modulation: Figure4B shows the PPM implementation and some of the demodulation schemes used for testing. Graph1B shows the transmission of ‘01101’. Graph1A PAM Transmission Graph1B PPM Transmission •bits were randomly transmitted and received with each design •Additive White Gaussian Noise with a 4.8 SNR was added to the transmitted signal along with being manipulated by the noise model. A possible direction that can be taken would be to do further testing with more accurate noise channel models and to quantify the relative complexity of the various algorithms to give a performance versus FPGA memory trade-off. Table1A Table1B In testing the efficiency of the PPM demodulation implementations: Note that N/A in Table1A and Table1B indicate that the design performed above or below average and did not need to be repeated.

Baseband PPM and PAM Algorithm Implementation

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Page 1: Baseband PPM and PAM Algorithm Implementation

Kenneth Rice, Joel Simoneau, and Dr. L. Wilson Pearson

The purpose of this research is to implement two baseband communication algorithms: Pulse Position Modulation (PPM) and Pulse Amplitude Modulation (PAM). The two techniques implemented to demodulate PPM and PAM are the Matched Filter and Time Limited Accumulation (TLA) filter.

Another purpose of this research is to test several implementations for demodulating PPM for efficiency and productivity. This is done using two noise channel models: Direct/Reflected Path Noise and Random Inversion Noise.

The amplitude of the pulses denote the transmitted information. An example is shown in Figure1A.

The location of the pulse within the specified transmission frame indicates the transmitted information. Figure1B gives an example of this kind of modulation.

Matched Filter:

Modulation Techniques

Demodulation TechniquesTime Limited Accumulation Filter:

Introduction

Direct/Reflected Path Noise Model:

Random Inversion Noise Model:

Summer Undergraduate Research Experience

Noise Channel Models

When the transmitted signal changes path during transmission in such a way that the signal becomes inverted. Figure3A is an example.

A more complicated version of the Direct/ Reflected Path Noise Model. This can be seen in Figure3B

PAM Implementations:

PAM: RECEIVER

xlbalancez-k -1

SyncScope2

xlrelationalz-1

a

b a>b

en

Relational

xlp2sp sPtoS5

fpt dblOut2

xlmultz-3

ab (ab)

MultOut

Matched xlconvertcast

Conv1

1

Con8

0

Con5

52Con3

xladdsubz-1a-b

aba

AddSub2q

brst

Accum

Out1

Out2

Out3

ADC

Receiver (Matched):

PPM Implementations:

PAM: TRANSMITTER

Out

Digital Input

In Out

DSP

In1

In2

Out1Out2Out3

DAC 20.20313

Cont1

xladdsubz-1a+b

aba

AddSub1

Transmitter:

ONE

ZERO

In1

Signal

F.Half

Reset

S.Half

Enable

Timing Controller

Scope2

xlrelational

z-1

a

b a<b

en

Relate2

fpt dbl

Out4

Out1

Out2

Out3

ADC

InOut

ABS

q

b

en

rst

2Accum

q

b

en

rst

1Accum

PPM: MATCHED FILTER RECEIVER

In1Out1Out2Out3

Timing

xlbalancez-k -1

Sync

Scope2

xlrelationalz-1

ab a<ben

Relational2

fpt dblOut4

xlmultz-3

ab (ab)

Mult2

Out

Matched Waveform 0Con7

qbrst

Accum

Out1

Out2

Out3

ADC

PAM: TRANSMITTER

ZERO

ONE xlp2sp sPtoS6

xlp2sp sPtoS10

xlmux

sel

d0

d1d1

Mux1

Out

Digital Input

In Out

DSP

In1

In2

Out1Out2Out3

DAC 2

3.277e+004

Con81024

Con14

Transmitter:

Receiver (Matched):

Receiver (TLA):

TestingDesign 101 bits 1001 bits

Matched 44 errors N/A

Matched (Altered) 0 errors 0 errors

TLA 0 errors 5 errors

TLA (Altered) 0 errors 0 errors

Direct/Reflected Path Results

Design 101 bits 1001 bitsMatched 42 errors N/A

Matched (Altered) 24 errors 266 errors

TLA 0 errors N/A

TLA (Altered) 24 errors 266 errors

Random Inversion Results

Future Work

Algorithm Implementation

References[1] L.C. Ludeman, Fudamentals of Digital Signal Processing. New York: Harper and Row, 1986.

[2] M.B. Pursley, Introduction to Digital Communications. New Jersey: Pearson Prentice Hall, 2005.

Figure1A Figure1B

Figure2A Figure2B

Pulse Position Modulation:

Figure3A

Figure3B

Figure4A Figure4B

Figure4A shows the Xilinx blocks used in MATLAB’s Simulink to implement PAM. Graph1A shows the transmission of ‘001100’.

Pulse Amplitude Modulation:

Figure4B shows the PPM implementation and some of the demodulation schemes used for testing. Graph1B shows the transmission of ‘01101’.

Graph1A

PAM Transmission

Graph1B

PPM Transmission

•bits were randomly transmitted and received with each design

•Additive White Gaussian Noise with a 4.8 SNR was added to the transmitted signal along with being manipulated by the noise model.

A possible direction that can be taken would be to do further testing with more accurate noise channel models and to quantify the relative complexity of the various algorithms to give a performance versus FPGA memory trade-off.

Table1A

Table1B

In testing the efficiency of the PPM demodulation implementations:

Note that N/A in Table1A and Table1B indicate that the design performed above or below average and did not need to be repeated.