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CS 313 Introduction to Computer Networking & Telecommunication

CS 313 Introduction to Computer Networking & Telecommunication. Theoretical Basis of Data Communication. Topics. Data Communication Performance Measurements Analog/Digital Signals Time and Frequency Domains Bandwidth and Channel Capacity. Data Communication Performance Measurements.

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CS 313 Introduction to Computer Networking & Telecommunication

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  1. CS 313 Introduction to Computer Networking & Telecommunication Theoretical Basis of Data Communication Chi-Cheng Lin, Winona State University

  2. Topics • Data Communication Performance Measurements • Analog/Digital Signals • Time and Frequency Domains • Bandwidth and Channel Capacity

  3. Data Communication Performance Measurements • Throughput • How fast data can pass through an entity • Number of bits passing through an imaginary wall in a second • Bit time • Duration of a bit (time for a bit ejected into network) • 1 / throughput • Propagation time (propagation delay) • Time required for one bit to travel from one point to another • Propagation speed depends on medium and signal frequency

  4. Message Transmission Delay Total transmission delay = (size_of_message / throughput) + propagation_time Time Sender 01101… Receiver 01101… t0 t1 t2 t3 first bit sent last bit sent first bit arrived last bit arrived propagation_time

  5. Message Transmission Delay - Example • What is the transmission delay of a 2 KB message transmitted over a 2 km cable that has a throughput 40 Mbps and a propagation delay of 8 µs/km? • Answer: Total transmission delay = (size_of_message / throughput) + propagation_time = (2048 x 8 bits / 40x106 bits/sec) + 8 µs/km x 2 km = 409.6 x 10-6 sec + 16 µs = 425.6 µs What is the bit time? 5

  6. Signals • Information must be transformed into electromagnetic signals to be transmitted • Signal forms • Analog or digital

  7. Analog/Digital Signals • Analog signal • Continuous waveform • Can have a infinite number of values in a range • Digital signal • Discrete • Can have only a limited number of values • E.g., 0 and 1, i.e., two levels, for binary signal

  8. Time Vs. Frequency Domain • A signal can be represented in either the time domain or the frequency domain.

  9. Period (Time) and Frequency

  10. Composite Signals • A composite signal can be decomposed into component sine waves - harmonics • The decomposition is performed by FourierAnalysis • DC component is the one with frequency 0.

  11. Frequency Spectrum and Bandwidth • Frequency spectrum • Collection of all component frequencies it contains • Bandwidth • Width of frequency spectrum

  12. Digital Signal - Decomposition • A digital signal can be decomposed into an infinite number of simple sine waves (harmonics) A digital signal is a composite signal with an infinite bandwidth. • More harmonics components = better approximation • Animation • Significant spectrum • Components required to reconstruct the digital signal

  13. Bandwidth-Limited Signals • (a) A binary signal and its root-mean-square Fourier amplitudes.

  14. Bandwidth-Limited Signals (2) • (b) – (e) Successive approximations to the original signal.

  15. Channel Capacity • Channel capacity • Maximum bit rate a transmission medium can transfer • Nyquist theorem for noiseless channels • C = 2H log2V where C: channel capacity (bit per second) H: bandwidth (Hz) V: signal levels (2 for binary) • C is proportional to H  bandwidth puts a limit on channel capacity

  16. Channel Capacity • Shannon Capacity for noisy channels • C = H log2(1 + S/N) where C: (noisy) channel capacity (bps) H: bandwidth (Hz) S/N: signal-to-noise ratio dB = 10 log10S/N • In practice, we have to apply both for determining the channel capacity.

  17. Examples • Noiseless channel. Consider a noiseless channel with a bandwidth of 3000 Hz transmitting a signal with two signal levels. What is the maximum bit rate of this channel? • Noiseless channel. Consider the same noiseless channel, transmitting a signal with four signal levels (for each level, we send two bits). What is the maximum bit rate of this channel? • Extremely noisy channel. Consider an extremely noisy channel in which the value of the signal-to-noise ratio is almost zero. In other words, the noise is so strong that the signal is faint. What is the channel capacity of this channel?

  18. Examples • Theoretical highest bit rate of a regular telephone line. A telephone line normally has a bandwidth of 3000 Hz (300 Hz to 3300 Hz). The signal-to-noise ratio is usually 35dB, i.e., 3162. What is the capacity of this channel? • Applying both theorems. We have a channel with a 2 MHz bandwidth. The S/N for this channel is 127; what is the appropriate bit rate and signal level?

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