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Introduction to Electrical Communications Systems

This lecture discusses baseband and bandpass signals, communication system block diagrams, frequency allocations, and information theory in electrical communications systems.

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Introduction to Electrical Communications Systems

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  1. Electrical Communications SystemsECE.09.433Spring 2019 Lecture 1bJanuary 24, 2019 Shreekanth Mandayam ECE Department Rowan University http://users.rowan.edu/~shreek/spring19/ecomms/

  2. ECOMMS: Topics

  3. Plan • Baseband and Bandpass Signals • Recall: Comm. Sys. Block diagram • Aside: Why go to higher frequencies? • International & US Frequency Allocations • Intoduction to Information Theory • Recall: List of topics • Probability • Information • Entropy • Signals and Noise

  4. Baseband Signal Baseband Signal Bandpass Signal Demodulation or Detection Modulation Comm. Sys. Bock Diagram Noise Channel Rx m(t) Tx r(t) s(t) • “Low” Frequencies • <20 kHz • Original data rate • “High” Frequencies • >300 kHz • Transmission data rate Formal definitions will be provided later

  5. Aside: Why go to higher frequencies? Half-wave dipole antenna c = f l c = 3E+08 ms-1 Calculate l for f = 5 kHz f = 300 kHz Tx l/2 There are also other reasons for going from baseband to bandpass

  6. Frequency Allocations • International Frequency Allocations: http://www.fcc.gov/oet/spectrum/table/Welcome.html • US Frequency Allocation Chart: http://www.ntia.doc.gov/osmhome/allochrt.html

  7. Info Sink Info Source Comm System Information • Recall: • Information Source: a system that produces messages (waveforms or signals) • Digital/Discrete Information Source: Produces a finite set of possible messages • Digital/Discrete Waveform: A function of time that can only have discrete values • Digital Communication System: Transfers information from a digital source to a digital sink

  8. Deterministic Signals: Can be modeled as a completely specified function of time Random or Stochastic Signals: Cannot be completely specified as a function of time; must be modeled probabilistically What type of signals are information bearing? Another Classification of Signals (Waveforms)

  9. Signals and Noise Lab 1 Comm. Waveform • Strictly, both signals and noise are stochastic and must be modeled as such • We will make these approximations, initially: • Noise is ignored • Signals are deterministic Noise (undesired) Signal (desired)

  10. Measures of Information • Definitions • Probability • Information • Entropy • Source Rate • Recall: Shannon’s Theorem • If R < C = B log2(1 + S/N), then we can have error-free transmission in the presence of noise MATLAB DEMO: entropy.m

  11. Summary

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