2. What is Data?
• Definition:
• Data refers to raw information that can be processed, stored, or transmitted by computers.
• Can be in the form of text, numbers, images, or sounds.
• Types:
• Analog data (continuous values)
• Digital data (discrete values like 0s and 1s)
• Visual: Examples of data formats (text, numbers, images)
3. What is a Signal?
• Definition: A signal is the physical form in which data is transmitted through a
network (e.g., electrical, optical, or radio signals).Used to encode and carry the
data.
• Types of Signals:
• Analog Signal (continuous waveforms)
• Digital Signal (discrete pulses, typically binary)
• Visual: Waveform examples of analog vs. digital signals
4. Analog vs. Digital Signals
• Analog Signals: Continuous, vary smoothly over time.
• Examples: Audio signals, traditional radio.
Digital Signals: Discrete, made of binary 0s and 1s.
Examples: Computer data, modern communication system
Visual: Graph showing an analog signal and a digital signal side by side
5. Data Transmission and Encoding
•Transmission:
•Data needs to be converted into signals for transmission over a network.
•Encoding Methods:
•Analog Data → Analog Signal: AM/FM modulation
•Digital Data → Digital Signal: Binary encoding
•Analog Data → Digital Signal: Pulse code modulation (PCM)
•Digital Data → Analog Signal: Modulation techniques (like ASK, PSK)
•Visual: Simple encoding diagram
6. Data Transmission and Encoding
• Transmission:
• Data, whether it's text, audio, or video, cannot be directly sent
through a network like copper wires, fiber optics, or radio waves. To
transmit this data, it first needs to be converted into signals that the
transmission medium can carry.
• Data Transmission Process involves two key steps:
• Encoding: Data is transformed into a signal.
• Transmission: The signal is then transmitted through a network medium
(e.g., wired, wireless, fiber).
7. • Encoding Methods: Encoding refers to the process of converting data
into a form (signal) that can be transmitted through a network. There
are different encoding techniques depending on the type of data
(analog or digital) and the type of signal (analog or digital).
• Here are the four primary methods of encoding:
8. . Analog Data → Analog Signal
• When analog data (e.g., voice in a phone call) needs to be sent over a
network, it's converted into an analog signal.
• Modulation is the process used here, and the two common types are:
• Amplitude Modulation (AM): Where the amplitude (strength) of the signal is
varied in proportion to the data.
• Frequency Modulation (FM): Where the frequency of the signal is varied.
• Example: Traditional AM/FM radio transmissions.
9. Digital Data → Digital Signal
• Digital data (like computer files or internet traffic) can be directly
encoded into digital signals.
• This is often done by using binary encoding, where:
• 0 represents a low voltage or off state.
• 1 represents a high voltage or on state.
• Example: Data being transmitted over Ethernet cables uses binary
encoding.
10. Analog Data → Digital Signal
• To transmit analog data in digital form (e.g., voice in a VoIP call or
music), it needs to be digitized. This involves two steps:
• Sampling: Taking periodic samples of the analog signal.
• Quantization: Assigning discrete values to these samples to form a digital
signal.
• The most common technique for this is Pulse Code Modulation
(PCM).
• Example: Audio CDs or digital telephony.
11. Digital Data → Analog Signal
•Sometimes, digital data needs to be converted into an analog signal for
transmission over certain media (e.g., radio waves or telephone lines).
•This conversion process involves modulation techniques, similar to how
analog data is modulated, but it applies to digital data:
•Amplitude Shift Keying (ASK): Varies the amplitude of the analog signal to
represent binary data.
•Frequency Shift Keying (FSK): Varies the frequency to represent 0s and 1s.
•Phase Shift Keying (PSK): Changes the phase of the signal to encode the
data.
•Example: Modems that transmit digital data over telephone lines.
12. Amplitude
• Definition:
• Amplitude refers to the strength or height of the signal wave. It represents the
maximum displacement of the signal from its rest position.
• Importance:
• In both analog and digital signals, amplitude affects the power of the signal. A
higher amplitude generally means a stronger signal, which can travel longer
distances without significant degradation.
• Applications:
• In Amplitude Modulation (AM), the amplitude of the signal is varied to encode
information. This is commonly used in AM radio.
• Visual Example:
• A sine wave with varying heights (amplitudes), where taller waves represent
higher signal strength.
13. Frequency
• Definition:
• Frequency is the number of cycles or oscillations a signal completes in one second, measured in
Hertz (Hz).
• Higher frequencies mean more cycles per second.
• Importance:
• Frequency affects how much data a signal can carry. Higher frequencies can typically carry more
data.
• However, higher-frequency signals tend to lose energy more quickly (attenuation) over long
distances, especially in certain mediums.
• Applications:
• In Frequency Modulation (FM), information is encoded by varying the frequency of the signal,
such as in FM radio.
• Visual Example:
• Two sine waves: one with a higher frequency (more cycles per second) and one with a lower
frequency.
14. Phase
• Definition:
• Phase refers to the position of a point in time on a waveform relative to the start of
a cycle. It's essentially a shift in the waveform's timing.
• Importance:
• Phase shift is used in data encoding techniques such as Phase Shift Keying (PSK),
where the phase of the signal is altered to represent different data values (e.g., 0s
and 1s).
• Phase is crucial in ensuring that signals from different sources don’t interfere
destructively with each other in communications.
• Visual Example:
• Two waves, where one is shifted in time compared to the other (a "delayed" or
"advanced" wave).
15. Factors Affecting Signal Quality
• The quality of a signal during transmission can degrade due to various
factors. If not managed, this can lead to data loss or errors. Here are
the key factors affecting signal quality:
16. Noise
• Definition:
• Noise refers to any unwanted or random disturbances that interfere with the
signal during transmission.
• Types of Noise:
• Thermal noise, electromagnetic interference (EMI), crosstalk, and impulse noise.
• Impact:
• Noise adds random variations to the signal, making it harder to extract the
original data. The more noise, the lower the quality of the signal.
• Solutions:
• Use of error-correction techniques, shielding cables, and digital signal processing
to minimize noise.
17. Attenuation
• Definition:
• Attenuation is the gradual weakening of a signal as it travels through a
medium.
• Impact:
• Over long distances, signals lose energy and may become too weak to be
properly received. This is especially true for analog signals, but digital signals
can also suffer if not amplified or repeated.
• Solutions:
• Use of repeaters (devices that amplify or regenerate the signal) and
amplifiers to boost signal strength in long-distance communication.
18. Distortion
• Definition:
• Distortion occurs when the shape of a signal is altered due to various factors,
such as the medium it is traveling through or interference from other signals.
• Impact:
• It can lead to errors in data interpretation, particularly in analog signals,
where the waveform carries the data.
• Solutions:
• Use of equalizers to reverse the distortion effects, and proper design of
transmission systems to avoid distortion.
19. Signal-to-Noise Ratio (SNR)
• Definition:
• The Signal-to-Noise Ratio (SNR) is a measure of how much of the received
signal is useful data versus how much is noise. It is often expressed in
decibels (dB).
• Importance:
• A higher SNR indicates a clearer and stronger signal, while a low SNR means
the signal is heavily contaminated by noise, making data recovery difficult.
• Solutions:
• Improving SNR can involve reducing noise or increasing signal strength.
Techniques like error correction, signal amplification, and filtering help
maintain a high SNR.
20. Periodic Signals
•Definition: A signal is periodic if it repeats itself at regular intervals over
time.
•Key Properties:
•Period (T): The time interval after which the signal repeats.
•Frequency (f): The number of repetitions (cycles) per second (f = 1/T).
•Examples: Sine waves, cosine waves, clock signals in computers.
•Importance: Used in systems requiring synchronized data transmission
(e.g., radio signals, clock pulses).
21. Nonperiodic Signals
•Definition: A signal is nonperiodic (or aperiodic) if it does not repeat over
time.
•Examples: Real-world signals such as speech, music, and most digital data
streams.
•Importance: Nonperiodic signals are common in data networks like the
Internet, where information
• is transmitted in packets without a fixed pattern.
22. Digital-to-Digital Conversion
•Definition: The process of converting digital data into digital signals for transmission across a
communication medium.
•Relevance: Used in network transmission, where data (binary 0s and 1s) is converted into
signals that can travel over physical media.
•Categories: Includes line coding, block coding, and scrambling.
23. Line Coding
•Definition: The process of converting digital data into a digital signal by mapping binary values
(0s and 1s) into specific voltage levels.
•Types of Line Coding:
•Unipolar: Uses a single voltage level for 1s, 0 voltage for 0s.
•Polar: Uses positive and negative voltages.
•Bipolar: Alternates between positive, negative, and zero voltages.
•Example: Unipolar NRZ (Non-Return-to-Zero), Polar NRZ, Manchester coding.
24. Block Coding
•Definition: Enhances line coding by grouping bits into larger blocks and adding redundant bits for
error detection.
•How It Works: Divides the input data into blocks and adds extra bits (redundancy) for error correction
or synchronization.
•Examples:
•4B/5B: Maps 4 bits of data into 5-bit symbols to maintain synchronization.
•8B/10B: Maps 8-bit data to 10-bit symbols.
•Benefits: Helps with synchronization and error detection.
25. Scrambling
•Definition: Used to avoid long sequences of 0s or 1s in the signal, which can cause loss
of synchronization.
•How It Works: Modifies the data stream in a way that the receiver can correctly interpret, ensuring no
long runs of the same bit.
•Common Methods:
•B8ZS (Bipolar with 8-Zero Substitution): Substitutes eight consecutive zeros with a special pattern
to maintain the signal.
•HDB3 (High-Density Bipolar 3 Zeros): Substitutes patterns in long sequences of zeros with violations
in the signal.
•Use Case: Used in digital telecommunication systems.
26. Importance and Applications
•Error Detection and Synchronization: Techniques like block coding and scrambling are essential
for ensuring data integrity and synchronization in long transmissions.
•Application in Networks: Used in Ethernet, telecommunication systems, and various digital networks to
ensure reliable and efficient data transfer.
•Efficiency: Improves the transmission quality and reduces noise interference in high-speed digital systems.
27. Analog-to-Digital Conversion
•Definition: The process of converting continuous analog signals (e.g., sound, light) into discrete
digital data (binary 0s and 1s).
•Relevance: Essential for digital devices to process real-world signals, such as audio or video.
•Applications: Used in digital audio (e.g., CDs), digital communication, image processing, etc.
28. Steps in Analog-to-Digital Conversion
1. Sampling: Measuring the analog signal at regular intervals (sampling rate).
2. Quantization: Assigning each sampled value to the nearest value in a finite set of levels.
3. Encoding: Converting quantized values into binary code.
•Example: Converting an analog audio signal into a digital stream for playback on a computer.
29. Sampling in Analog-to-Digital Conversion
•Sampling Rate: The number of times per second the analog signal is sampled, measured
in Hertz (Hz).
•Nyquist Theorem: To accurately represent an analog signal, the sampling rate must be at
least twice the highest frequency of the signal.
•Impact of Sampling Rate: Higher sampling rates lead to more accurate digital
representations but require more data.
•Examples: CD audio uses a 44.1 kHz sampling rate.
30. Quantization and Encoding
•Quantization: Converts each sampled value to a nearby fixed level. This process introduces
quantization error, which affects the precision of the signal.
•Bit Depth: The number of bits used to represent each sample, which determines the number of
quantization levels (e.g., 8-bit, 16-bit, etc.).
•Encoding: After quantization, the levels are encoded into binary numbers for storage or
transmission.
•Example: An 8-bit system has 256 possible quantization levels.
31. Importance and Applications of ADC
•Digital Processing: Enables real-world analog signals to be processed, stored, and transmitted by
digital systems (e.g., computers, smartphones).
•Applications:
•Audio: Microphones, digital music, VoIP.
•Video: Digital cameras, streaming services.
•Communication Systems: Converting voice signals to digital data in telecommunication systems.
•Accuracy: The combination of high sampling rate and high bit depth improves the accuracy and
quality of the digital signal.
32. Digital-to-Analog Conversion
•Definition: The process of converting digital data (binary 0s and 1s) into continuous analog signals.
•Relevance: Essential in communication systems where digital data needs to be transmitted over
analog media (e.g., telephone lines, radio waves).
•Applications: Modems, broadcasting systems, telecommunications, etc.
33. Basic Techniques in Digital-to-Analog
Conversion
•1. Amplitude Shift Keying (ASK): The amplitude of the carrier signal is varied to represent digital
data (0s and 1s).
•2. Frequency Shift Keying (FSK): The frequency of the carrier signal is varied to encode data.
•3. Phase Shift Keying (PSK): The phase of the carrier signal is shifted to represent binary data.
•Use Case: Modulation techniques used in modems for digital communication.
34. Amplitude Shift Keying (ASK)
•Definition: Modulation technique where the amplitude of a carrier wave is modified to represent
digital data.
•How It Works: Binary 1s and 0s are represented by different signal amplitudes. A higher amplitude
represents a binary 1, while a lower (or zero) amplitude represents a binary 0.
•Applications: Low-speed communication systems like RFID tags and optical fiber.
35. Frequency Shift Keying (FSK)
•Definition: Modulation technique where the frequency of the carrier signal is changed to represent
digital data.
•How It Works: A higher frequency represents a binary 1, and a lower frequency represents a binary
0.
•Applications: Used in radio transmission, early modems, and RFID.
•Example: Telephone modems that used different frequencies to transmit data over analog phone
lines.
36. Phase Shift Keying (PSK)
•Definition: Modulation technique where the phase of the carrier wave is shifted to encode digital data.
•How It Works: Binary values are represented by changes in the phase of the signal. A shift in phase
represents a change from 0 to 1 or vice versa.
•Types:
•BPSK (Binary PSK): Uses two phases (0° and 180°) to represent binary data.
•QPSK (Quadrature PSK): Uses four phases (0°, 90°, 180°, 270°) for more efficient data transmission.
•Applications: Used in Wi-Fi, satellite communication, and cellular networks.
37. Analog-to-Analog Conversion
•Definition: The process of converting one analog signal into another analog signal with
modified characteristics for transmission.
•Relevance: Used in communication systems to modulate signals for transmission over different
media.
•Applications: Radio broadcasting, TV broadcasting, cellular communication
38. Types of Analog Modulation
•1. Amplitude Modulation (AM): Modifies the amplitude of the carrier signal based on the amplitude
of the input signal.
•2. Frequency Modulation (FM): Modifies the frequency of the carrier signal according to the input
signal.
•3. Phase Modulation (PM): Alters the phase of the carrier signal in response to the input signal.
•Use Case: All three methods are widely used in various communication systems, like radio and TV.
39. Amplitude Modulation (AM)
•Definition: The amplitude of the carrier wave changes in proportion to the amplitude of the input
(message) signal.
•How It Works: The strength (amplitude) of the carrier signal varies according to the input analog
signal (e.g., voice or music).
•Applications: Used in AM radio broadcasting, aircraft communication.
•Advantages/Disadvantages: Simple but more susceptible to noise.
40. Frequency Modulation (FM)
•Definition: The frequency of the carrier wave is varied in accordance with the amplitude of the input
signal.
•How It Works: A higher input signal causes a higher frequency deviation, while a lower input signal
causes a lower frequency deviation.
•Applications: Used in FM radio, TV sound signals, two-way radios.
•Advantages/Disadvantages: Less prone to noise interference compared to AM.
41. Phase Modulation (PM)
•Definition: The phase of the carrier signal is modulated to represent the input analog signal.
•How It Works: The phase of the carrier signal shifts in proportion to the input signal's amplitude.
•Applications: Used in some communication systems, often combined with FM.
•Advantages/Disadvantages: More complex but can carry more data.
