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Final Project

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Jeremy Ruppert

This document describes an experiment comparing different types of delta modulation techniques: delta modulation, delta-sigma modulation, and adaptive delta modulation. The experiment used TIMS modules to implement analog-to-digital conversion circuits for each technique. Delta modulation showed quantization noise in modulated signals and degraded speech quality after demodulation. Delta-sigma modulation reduced noise through feedback. Adaptive delta modulation further improved quality by varying the step size for different signal slopes. The document presents circuit diagrams and oscilloscope results, finding adaptive delta modulation produced the cleanest signals and most intelligible demodulated speech.

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Abstract—Delta modulation is an analog to digital signal conversion method in which signal quality is not of primary importance. This experiment will replicate delta modulation, delta-sigma modulation, adaptive delta modulation, and delta demodulation. All components used will be TIMS modules, namely an AUDIO OSCILLATOR, DELTA MODULATION UTILITIES, and an ADDER. Index Terms—delta, modulation, analog-to-digital, demodulation I.INTRODUCTION ELTA modulation is an analog-to-digital and digital-to- analog signal conversion technique used for transmission of voice information where quality is not of primary importance. DM is the simplest form of differential pulse-code modulation (DPCM) where the difference between successive samples are encoded into n-bit data streams. In delta modulation, the transmitted data is reduced to a 1-bit data stream. Each segment of the approximated signal is compared to the original analog wave to determine the increase or decrease in relative amplitude. To achieve a high signal-to-noise ratio, delta modulation must use oversampling techniques, that is, the analog signal is sampled at a rate several times higher than the Nyquist rate. D In delta-sigma modulation, the accuracy of the modulation is improved by passing the digital output through a 1-bit DAC and adding (sigma) the resulting analog signal to the input signal, thereby reducing the error introduced by the delta-modulation. Delta-sigma modulation is used in modern electronics such as converters, switched-mode power supplies, and motor controllers. With the delta modulator there is a conflict when determining the step size. A large step size is required when sampling those parts of the input waveform of steep slope. But a large step size worsens the granularity of the sampled signal when the waveform being sampled is changing slowly. A small step size is preferred in regions where the message has a small slope. A controllable step size can be implemented using adaptive delta modulation, also called adaptive delta pulse code modulation, or ADPCM. ADPCM techniques are used in Voice over IP communications. ADPCM was also used by Interactive Multimedia Association for development of legacy audio codec known as ADPCM DVI, IMA ADPCM or DVI4, in the early 1990s. ADPCM encodes the difference between a predicted sample and the speech sample, and provides a more efficient compression and a reduction in the number of bits per sample, yet preserves the overall quality of a speech sample.  Manuscript received November 15th , 2015. This work was supported in part by Auburn University teaching assistant Muralidharan Venkatasubramanian, as part of ELEC 3060 for Wireless Engineers. J. M. Ruppert and E.R. Seay are seniors studying Wireless Engineering at Auburn University, Auburn, AL 36832. II.PROCEDURE A. Delta Encoding We constructed the circuit shown in Figure 1 to implement delta modulation. To decode, we constructed a sample and hold, integrated, and filtered the signal through a low pass filter. A delta modulated signal is shown in Figure 2, and a delta modulated voice message is shown in Figure 3. Adjusting the CLK to higher frequencies increases the number of samples, giving a better waveform. B. Delta-sigma Encoding To improve the quality of the signal, we constructed the circuit shown in Figure 4. This simulates delta-sigma modulation. The delta-sigma modulator places an integrator in between the source and the summer of the basic delta modulator, and Figure 5 shows the resulting waveform, and Figure 6 shows delta-sigma modulation and demodulation of a voice signal. C. Adaptive Delta Encoding We next constructed the circuit shown in Figure 7 to model adaptive delta modulation. The modulated signal is shown in Figure 8, and a demodulated voice signal is shown in Figure 9. D. Figures Figure 1. Delta modulation circuit Figure 2. Delta modulated signal (green) Delta, Delta-sigma, Adaptive delta modulation and demodulation (December 2015) Jeremy M. Ruppert, Edward B. Seay 1
Figure 3. Demodulated delta signal (input speech message in yellow, demodulated output in green) Figure 4. Delta-sigma modulation Figure 5. Delta-sigma modulated signal Figure 6. Delta-sigma demodulated speech signal Figure 7. Adaptive delta modulation Figure 8. Adaptive delta modulated signal Figure 9. Adaptive delta demodulated speech signal III. EXPLANATION OF RESULTS The delta modulation shown in Figure 2 clearly shows the different slopes between each sampled point. These differences are the key to understanding why the quality improves with other delta modulation techniques. The sawtooth waveform contains information at the message frequency, plus unwanted components from quantizing noise, which results in a poor SNR. Figure 3 shows the input voice signal in yellow, and the delta modulated and then demodulated signal in green. The resulting noise can be easily observed, and this noise was noticeable as static when played through a speaker, though speech could be understood. Figure 5 shows a delta-sigma modulated signal, which has a noticeably cleaner curve. The effects of the cleaner curve can be seen in Figure 6 between a voice signal and the demodulated adaptive-delta output. This output contains less quantizing noise, and therefore a cleaner audio output, than the delta modulation we performed prior. Figure 7 shows the adaptive modulated signal, and it has 2
the cleanest waveform of any thus far. Figure 8 shows an input voice signal versus the demodulated output of adaptive delta encoding, and Figure 9 shows adaptive delta modulation applied to a speech signal. Adaptive delta produced the most intelligible output. IV. ERROR / DIFFICULTY The most immediate challenge we came across was that the TIMS modules we had did not include a DELTA DEMODULATION UTILITIES, so we made one from a sample and hold, integrator, and a low pass filter. The rest of the procedure was very straightforward, and we did not have any other significant areas of difficulty. V. CONCLUSION The differences between the various types of delta modulation were visualized on the oscilloscope and successfully applied to voice signals. Each type of modulation shown has its benefits and drawbacks as well as particular uses. The key difference between the three different methods of delta modulation is how they alter the step size. This is most evident when shown on a simple sine wave. By visually comparing the noise generated by each type of modulation and noting the audible improvement in quality, one is able to discern with a reasonably high level of certainty between the three modulation methods. REFERENCES [1] Ni.com, 'Benefits of Delta-Sigma Analog-to-Digital Conversion - National Instruments', 2015. [Online]. Available: http://www.ni.com/white- paper/11342/en/. [Accessed: 01- Dec- 2015]. [2] B. Baker, How delta-sigma ADCs work, Part 1, 1st ed. Texas Instruments Incorporated, 2011. [3] A. Loloee, 'Understanding Delta-Sigma Modulators', Electronicdesign.com, 2013. [Online]. Available: http://electronicdesign.com/analog/understanding-delta-sigma-modulators. [Accessed: 01- Dec- 2015]. 3

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Final Project

  • 1. Abstract—Delta modulation is an analog to digital signal conversion method in which signal quality is not of primary importance. This experiment will replicate delta modulation, delta-sigma modulation, adaptive delta modulation, and delta demodulation. All components used will be TIMS modules, namely an AUDIO OSCILLATOR, DELTA MODULATION UTILITIES, and an ADDER. Index Terms—delta, modulation, analog-to-digital, demodulation I.INTRODUCTION ELTA modulation is an analog-to-digital and digital-to- analog signal conversion technique used for transmission of voice information where quality is not of primary importance. DM is the simplest form of differential pulse-code modulation (DPCM) where the difference between successive samples are encoded into n-bit data streams. In delta modulation, the transmitted data is reduced to a 1-bit data stream. Each segment of the approximated signal is compared to the original analog wave to determine the increase or decrease in relative amplitude. To achieve a high signal-to-noise ratio, delta modulation must use oversampling techniques, that is, the analog signal is sampled at a rate several times higher than the Nyquist rate. D In delta-sigma modulation, the accuracy of the modulation is improved by passing the digital output through a 1-bit DAC and adding (sigma) the resulting analog signal to the input signal, thereby reducing the error introduced by the delta-modulation. Delta-sigma modulation is used in modern electronics such as converters, switched-mode power supplies, and motor controllers. With the delta modulator there is a conflict when determining the step size. A large step size is required when sampling those parts of the input waveform of steep slope. But a large step size worsens the granularity of the sampled signal when the waveform being sampled is changing slowly. A small step size is preferred in regions where the message has a small slope. A controllable step size can be implemented using adaptive delta modulation, also called adaptive delta pulse code modulation, or ADPCM. ADPCM techniques are used in Voice over IP communications. ADPCM was also used by Interactive Multimedia Association for development of legacy audio codec known as ADPCM DVI, IMA ADPCM or DVI4, in the early 1990s. ADPCM encodes the difference between a predicted sample and the speech sample, and provides a more efficient compression and a reduction in the number of bits per sample, yet preserves the overall quality of a speech sample.  Manuscript received November 15th , 2015. This work was supported in part by Auburn University teaching assistant Muralidharan Venkatasubramanian, as part of ELEC 3060 for Wireless Engineers. J. M. Ruppert and E.R. Seay are seniors studying Wireless Engineering at Auburn University, Auburn, AL 36832. II.PROCEDURE A. Delta Encoding We constructed the circuit shown in Figure 1 to implement delta modulation. To decode, we constructed a sample and hold, integrated, and filtered the signal through a low pass filter. A delta modulated signal is shown in Figure 2, and a delta modulated voice message is shown in Figure 3. Adjusting the CLK to higher frequencies increases the number of samples, giving a better waveform. B. Delta-sigma Encoding To improve the quality of the signal, we constructed the circuit shown in Figure 4. This simulates delta-sigma modulation. The delta-sigma modulator places an integrator in between the source and the summer of the basic delta modulator, and Figure 5 shows the resulting waveform, and Figure 6 shows delta-sigma modulation and demodulation of a voice signal. C. Adaptive Delta Encoding We next constructed the circuit shown in Figure 7 to model adaptive delta modulation. The modulated signal is shown in Figure 8, and a demodulated voice signal is shown in Figure 9. D. Figures Figure 1. Delta modulation circuit Figure 2. Delta modulated signal (green) Delta, Delta-sigma, Adaptive delta modulation and demodulation (December 2015) Jeremy M. Ruppert, Edward B. Seay 1
  • 2. Figure 3. Demodulated delta signal (input speech message in yellow, demodulated output in green) Figure 4. Delta-sigma modulation Figure 5. Delta-sigma modulated signal Figure 6. Delta-sigma demodulated speech signal Figure 7. Adaptive delta modulation Figure 8. Adaptive delta modulated signal Figure 9. Adaptive delta demodulated speech signal III. EXPLANATION OF RESULTS The delta modulation shown in Figure 2 clearly shows the different slopes between each sampled point. These differences are the key to understanding why the quality improves with other delta modulation techniques. The sawtooth waveform contains information at the message frequency, plus unwanted components from quantizing noise, which results in a poor SNR. Figure 3 shows the input voice signal in yellow, and the delta modulated and then demodulated signal in green. The resulting noise can be easily observed, and this noise was noticeable as static when played through a speaker, though speech could be understood. Figure 5 shows a delta-sigma modulated signal, which has a noticeably cleaner curve. The effects of the cleaner curve can be seen in Figure 6 between a voice signal and the demodulated adaptive-delta output. This output contains less quantizing noise, and therefore a cleaner audio output, than the delta modulation we performed prior. Figure 7 shows the adaptive modulated signal, and it has 2
  • 3. the cleanest waveform of any thus far. Figure 8 shows an input voice signal versus the demodulated output of adaptive delta encoding, and Figure 9 shows adaptive delta modulation applied to a speech signal. Adaptive delta produced the most intelligible output. IV. ERROR / DIFFICULTY The most immediate challenge we came across was that the TIMS modules we had did not include a DELTA DEMODULATION UTILITIES, so we made one from a sample and hold, integrator, and a low pass filter. The rest of the procedure was very straightforward, and we did not have any other significant areas of difficulty. V. CONCLUSION The differences between the various types of delta modulation were visualized on the oscilloscope and successfully applied to voice signals. Each type of modulation shown has its benefits and drawbacks as well as particular uses. The key difference between the three different methods of delta modulation is how they alter the step size. This is most evident when shown on a simple sine wave. By visually comparing the noise generated by each type of modulation and noting the audible improvement in quality, one is able to discern with a reasonably high level of certainty between the three modulation methods. REFERENCES [1] Ni.com, 'Benefits of Delta-Sigma Analog-to-Digital Conversion - National Instruments', 2015. [Online]. Available: http://www.ni.com/white- paper/11342/en/. [Accessed: 01- Dec- 2015]. [2] B. Baker, How delta-sigma ADCs work, Part 1, 1st ed. Texas Instruments Incorporated, 2011. [3] A. Loloee, 'Understanding Delta-Sigma Modulators', Electronicdesign.com, 2013. [Online]. Available: http://electronicdesign.com/analog/understanding-delta-sigma-modulators. [Accessed: 01- Dec- 2015]. 3