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.