search

Chapter 3 Data and Signals

Chapter 3 of Data Communications and Networking by Behrouz A. Forouzan, titled "Data and Signals", covers the relationship between data and the electromagnetic signals used in data transmission. Below are detailed notes:

hashtag
1. Analog and Digital Data

  • Analog Data: Continuous values (e.g., sounds, human speech). Example: Sound waves captured by a microphone.

  • Digital Data: Discrete values (e.g., text stored as 0s and 1s). Example: Binary data in computer memory.

hashtag
2. Analog and Digital Signals

  • Analog Signals: Infinite number of values over a continuous range. Example: A sine wave representing voltage changes.

  • Digital Signals: Finite number of distinct values (e.g., 0 or 1). Represented as square waves.

hashtag
3. Periodic and Nonperiodic Signals

  • Periodic Signals: Repeat a pattern over time. Example: A sine wave completing a cycle at regular intervals.

  • Nonperiodic Signals: Do not exhibit a repetitive pattern. Common in data communication for transmitting irregular data streams.

hashtag
4. Periodic Analog Signals

  • Sine Wave: A fundamental concept in signal theory, described by three characteristics:

    • Amplitude: The height of the wave, representing the signal's strength.

    • Frequency: The number of cycles a wave completes in a second (measured in Hertz, Hz). Inversely related to the period.

    • Phase: The position of the wave relative to time zero.

  • Composite Signals: Signals formed by combining multiple sine waves, each with different frequencies, amplitudes, and phases. Fourier analysis breaks down these complex signals into simpler sine waves.

  • Bandwidth: The difference between the highest and lowest frequencies in a composite signal. Wider bandwidth allows more data transmission.

hashtag
5. Digital Signals

  • Bit Rate: The number of bits transmitted per second (bps).

  • Bit Length: The distance one bit occupies on the transmission medium.

  • Digital Signal as Composite Analog Signal: A digital signal is essentially a combination of multiple sine waves, each with different frequencies.

hashtag
6. Transmission Impairments

  • Attenuation: Loss of signal strength over distance.

  • Distortion: Occurs when different parts of the signal travel at different speeds, causing a change in shape.

  • Noise: Unwanted interference, including:

    • Thermal Noise: Random motion of electrons.

    • Induced Noise: External interference from sources like electrical devices.

    • Crosstalk: Overlapping signals from adjacent wires.

    • Impulse Noise: Sudden spikes in energy, such as lightning.

hashtag
7. Data Rate Limits

  • Nyquist Bit Rate: The theoretical maximum bit rate for a noiseless channel is calculated as 2 * Bandwidth * log2(L) where L is the number of signal levels.

  • Shannon Capacity: For a noisy channel, the maximum bit rate is determined by the signal-to-noise ratio (SNR) and bandwidth: Capacity = Bandwidth * log2(1 + SNR).

hashtag
8. Performance Metrics

  • Throughput: Actual rate of successful data transmission.

  • Latency: Total time taken for data to travel from source to destination, including processing and transmission delays.

  • Bandwidth-Delay Product: The number of bits that can fill the transmission path, calculated as Bandwidth * Delay.

  • Jitter: Variation in packet arrival times, which can affect real-time applications like video or voice communication.

This chapter provides foundational concepts necessary for understanding how data is transmitted across a network【7:2†source】【7:3†source】【7:4†source】【7:11†source】.

PreviousChapter 2 Network ModelsNextChapter 4 Digital Transmission

Last updated