Technical Report Writing
On
Differential Pulse Code
Modulation and Delta
Modulation
Submitted by
Name : ARKA DAS
Department : ECE 1
Semester : 5th
Roll Number : 16900321056
Department of Electronics and Communication Engineering
ACADEMY OF TECHNOLOGY
AEDCONAGAR, HOOGHLY-712121
WEST BENGAL, INDIA
Abstract
This technical report explores the principles, techniques, and
applications of two digital modulation schemes: Differential
Pulse Code Modulation (DPCM) and Delta Modulation. The
report aims to provide a comprehensive understanding of both
modulation methods, their demodulation processes, and to
evaluate their advantages and disadvantages in various
applications.
Introduction
Digital modulation techniques play a pivotal role in the realm
of signal processing, enabling the conversion of analog signals
into digital data for efficient transmission and storage. Among
these techniques, Differential Pulse Code Modulation (DPCM)
and Delta Modulation stand out as crucial tools for achieving
this conversion with distinct methodologies.
DPCM leverages predictive coding to capture and encode the
difference between the present signal sample and a predicted
value extrapolated from previous samples. Conversely, Delta
Modulation focuses on quantizing and encoding the
instantaneous variation between consecutive samples. These
techniques have unique characteristics, rendering them more
suitable for specific applications, and this report aims to
unravel their inner workings, decode their demodulation
processes, and weigh their strengths and limitations in diverse
contexts. Through this analysis, we endeavor to provide a
comprehensive understanding of these modulation techniques,
facilitating informed decisions when choosing the most
suitable method for a given application.
Differential Pulse Code
Modulation
Principles
DPCM is a form of pulse code modulation (PCM) that encodes the
difference between the current signal sample and a predicted value
derived from previous samples. The key components of DPCM include:
Predictor: A mathematical model or filter that estimates the next
sample based on past samples.
Quantizer: A device that quantizes the difference signal into
discrete levels.
Encoder: Converts the quantized difference into binary code for
transmission.
Demodulation
Demodulation in DPCM is the process of reconstructing the original
signal from the transmitted difference signal. It involves the following
steps:
Decoder: Converts the received binary code back into the
quantized difference values.
Inverse Quantizer: Converts the quantized difference values back
to approximate analog values.
Predictor: Uses past decoded samples to predict and reconstruct
the original signal.
Advantages and Disadvantages
Advantages of DPCM:
1. Compression: DPCM exploits temporal redundancy, leading to
efficient compression.
2. Robustness: It is resilient to channel noise and signal distortions
due to the predictive nature.
3. Low Bit Rate: Requires fewer bits compared to PCM for the same
signal quality.
Disadvantages of DPCM:
1. Error Propagation: Errors in prediction can propagate, affecting
the quality of subsequent samples.
2. Complexity: Designing an optimal predictor can be complex.
3. Limited for High-Frequency Signals: Less effective for high-
frequency signals with rapid changes.
Delta Modulation
Principles
Delta Modulation (DM) quantizes and encodes the instantaneous
difference between consecutive samples. Key components of DM include:
Comparator: Compares the input signal with the previous
quantized signal.
Quantizer: Converts the comparison result into a binary code.
Encoder: Transmits the binary code.
Demodulation
Demodulation in Delta Modulation involves:
Decoder: Converts the received binary code into quantized
difference values.
Delta Modulator: Reconstructs the approximate analog signal by
accumulating the quantized differences.
Advantages and Disadvantages
Advantages of Delta Modulation:
1. Simplicity: DM is conceptually simple and requires minimal
hardware.
2. Low Bit Rate: Effective for low-bit-rate communication.
3. Low Complexity: Suitable for real-time applications and low-
power devices.
Disadvantages of Delta Modulation:
1. Granular Noise: The quantization error can introduce granular
noise, particularly in low-bit-rate applications.
2. Limited Accuracy: Delta Modulation may not accurately represent
signals with rapid changes.
3. Sensitivity to Signal Amplitude: DM performance can be
sensitive to signal amplitude variations.
Applications
1. Communication Systems
DPCM: Widely used in digital communication for bandwidth-
efficient voice, image, video, and satellite transmissions.
Delta Modulation: Vital for low-bit-rate communication like
wireless networks and cost-effective VoIP services.
2. Speech and Audio Compression
DPCM: Key in audio codecs for reducing data size without
significant quality loss.
Delta Modulation: Ideal for low-bit-rate audio compression in
scenarios with limited bandwidth.
3. Image and Video Compression
DPCM: Essential in image and video compression standards
for efficient data reduction.
Delta Modulation: Occasional use in extreme bandwidth-
constrained applications like remote sensing.
4. Instrumentation
DPCM: Ensures accurate data transmission in noisy
environments for industrial automation.
Delta Modulation: Simple and cost-effective for real-time
data transmission in environmental monitoring and sensor
networks.
Conclusion
In summary, Differential Pulse Code Modulation (DPCM) and
Delta Modulation are two digital modulation techniques that
aim to encode analog signals into digital formats efficiently.
DPCM focuses on predicting signal values and encoding the
prediction error, while Delta Modulation quantizes the
instantaneous difference between consecutive samples. Both
methods have their advantages and disadvantages, making
them suitable for different applications based on their
characteristics and trade-offs.
References
1. Proakis, John G., and Dimitris G. Manolakis. "Digital Signal
Processing: Principles, Algorithms, and Applications." Pearson
Education India, 2014.
2. Rabiner, Lawrence R., and Ronald W. Schafer. "Introduction
to Digital Speech Processing." Foundations and Trends® in
Signal Processing 1.1-2 (2007): 1-194.
3. Vaidyanathan, P. P. "Multirate Systems and Filter Banks."
Englewood Cliffs, NJ: Prentice Hall, 1993.
