# Electrical Communications Systems 0909.331.01 Spring 2005 - PowerPoint PPT Presentation

Title:

## Electrical Communications Systems 0909.331.01 Spring 2005

Description:

### Half-wave dipole antenna. c = f l. c = 3E 08 ms-1. Calculate l for. f = 5 ... Digital/Discrete Information Source: Produces a finite set of possible messages ... – PowerPoint PPT presentation

Number of Views:16
Avg rating:3.0/5.0
Slides: 12
Provided by: shreekant9
Category:
Tags:
Transcript and Presenter's Notes

Title: Electrical Communications Systems 0909.331.01 Spring 2005

1
Electrical Communications Systems0909.331.01
Spring 2005
Lecture 1bJanuary 19, 2005
• Shreekanth Mandayam
• ECE Department
• Rowan University
• http//engineering.rowan.edu/shreek/spring05/ecom
ms/

2
ECOMMS Topics
3
ECOMMS Topics
4
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

5
Comm. Sys. Bock Diagram
Noise
Channel
Rx
m(t)
Tx
r(t)
s(t)
• Low Frequencies
• lt20 kHz
• Original data rate
• High Frequencies
• gt300 kHz
• Transmission data rate

Formal definitions will be provided later
6
Aside Why go to higher frequencies?
Half-wave dipole antenna
c f l c 3E08 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
7
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
Another Classification of Signals (Waveforms)
• 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?

9
Signals and Noise
Lab 1
Comm. Waveform
Noise (undesired)
Signal (desired)
• 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

10
Measures of Information
• Definitions
• Probability
• Information
• Entropy
• Source Rate
• Recall Shannons Theorem
• If R lt C B log2(1 S/N), then we can have
error-free transmission in the presence of noise

MATLAB DEMO entropy.m
11
Summary