Lecture_2

Physical Layer and Media

  • Date: 06/03/2025

Transmission of Data

  • Data transmission requires transforming data into electromagnetic signals.

Analog and Digital Data

  • Data Types:

    • Analog Data:

      • Represents information that is continuous and can take any value within a specified range.

      • Example: Temperature measuring from 0°C to 100°C can be any number within this range.

    • Digital Data:

      • Represents information with discrete states. It can only take specific, finite values.

      • Example: Values can be binary (0s and 1s) or any defined set of discrete values.

    • Understanding these concepts will involve knowledge about:

      • Analog and Digital Signals

      • Periodic and Nonperiodic Signals

      • Sine Wave Characteristics

      • Wavelength as a Signal Characteristic

      • Time and Frequency Domains

      • Composite Signals

      • Bandwidth

Signal Classification

  • Analog Signals:

    • Can possess an infinite number of values within a range.

  • Digital Signals:

    • Limited to a fixed number of values.

  • In data communications, we generally utilize:

    • Periodic analog signals

    • Nonperiodic digital signals

Periodic Analog Signals

  • Defined by continuous variations, repeating at regular intervals, suitable for audio/video transmissions.

  • Simple Periodic Signals:

    • Example: Sine wave, un-decomposable into simpler signals.

  • Composite Periodic Signals:

    • Composed of multiple sine waves.

Sine Wave Characteristics

  • Amplitude: Maximum value of a signal's strength measured from its baseline.

  • Frequency (f): Rate of signal variation.

    • Two signals can have the same phase and frequency but different amplitudes.

  • Period (T): Time taken to complete one cycle.

Frequency-Period Relationship

  • Frequency and period are inversely related:

    • Formula: T = 1/f

Signal Phase

  • Phase describes the position of the waveform concerning time 0.

    • Example: Different phases will yield different starting amplitudes at time 0.

Composite Signals and Fourier Analysis

  • Composite Signals:

    • Can be made of multiple sine waves.

    • Periodic and nonperiodic signal types each provide specific frequency characteristics:

      • Periodic signals yield discrete frequencies upon decomposition.

      • Nonperiodic signals yield continuous frequencies.

    • Fourier analysis explains the decomposition of complex signals into their fundamental components.

Bandwidth

  • Defined as the difference between highest and lowest frequencies within a signal.

  • Practical examples include bandwidths assigned to radio stations and how they impact transmission capabilities.

Digital Signals

  • Represent data using discrete states (e.g., binary signals, encoded voltage levels).

    • Digital signals can have multiple levels, increasing bits per level (log2L).

  • Various applications where digital signals are utilized include digitized voice channels which require specific sampling rates and compression techniques.

Transmission Techniques

  • Baseband Transmission:

    • Digital signals are sent without converting to analog; requires dedicated channels.

  • Broadband Transmission:

    • Involves using modulation to transmit over wider channels, allowing multiple signals.

Channel Characteristics

  • Low-Pass Channels:

    • Wide bandwidth channels preserve vertical and horizontal integrity of digital signals.

  • Bandwidth Requirements:

    • Bit rate is proportional to bandwidth used; higher bit rates require more bandwidth.

Conclusion

  • Analog vs Digital Signals:

    • Understanding signal types and their properties is crucial for effective data communication.

  • Chapter 5 will go further into the rationale of bandwidth allocations per signal type.

  • The complexity of digital signals and their transmission techniques are essential components of telecommunications.