Electrical%20Communications%20Systems%20ECE.09.331%20Spring%202008 - PowerPoint PPT Presentation

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Electrical%20Communications%20Systems%20ECE.09.331%20Spring%202008

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Title: ECOMMS Lecture Author: Shreekanth Mandayam Last modified by: Shreekanth Mandayam Created Date: 9/21/1998 7:15:22 PM Document presentation format – PowerPoint PPT presentation

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Title: Electrical%20Communications%20Systems%20ECE.09.331%20Spring%202008


1
Electrical Communications SystemsECE.09.331
Spring 2008
Lecture 10aApril 1, 2008
  • Shreekanth Mandayam
  • ECE Department
  • Rowan University
  • http//engineering.rowan.edu/shreek/spring08/ecom
    ms/

2
Plan
  • Digital Communications
  • Introduction
  • Digital Communications Transceiver (CODEC/MODEM)
  • Digital Baseband Communications
  • Source Encoding
  • Huffman Coding

3
ECOMMS Topics
4
Digital Communications
  • Some Milestones
  • Claude Shannon, 1948
  • X.25 (Telephony)
  • IEEE 802.3 (Ethernet)
  • ARPANET, 1969
  • IEEE 802.5 (FDDI)
  • ISO-OSI 7-layer Network Reference Model
  • CDMA
  • GSM
  • VOIP
  • SIP

protocols.com
5
Digital Communications Rationale
  • Information Theory
  • What is the fundamental limit on the compression
    and refinement of information generated by the
    source?
  • What is the fundamental limit on the transmission
    rate of information over a noisy channel?
  • How do we approach these limits?

6
Principle
Digital message
1 1
1 0 1 0
0 0
Digital code
Analog message
modulate
1 0 1 0
Sinusoidal carrier
AM
FM
PM
AM PM
7
Digital Communication Paradigms
Circuit Switching
Sync bits
Packet Switching
Header bits
8
Digital Communications Transceiver
Anti- aliasing Filter
Data Encryption Encoder
Error Control Encoder
Channel/ Line Encoder
Source Encoder
Sampling
Quantization
Modulator
MUX
ADC
Analog i/p
CODEC
MODEM
Multiple access channel
Analog o/p
Data Encryption Decoder
Error Control Decoder
Audio Amp
Source Decoder
Reconstruction/ DAC
Equalization / Decision Circuits
Demod-ulator
DEMUX
9
Source Encoding
Source Symbols (0/1) Source Entropy
Encoded Symbols (0/1) Source-Coded Symbol
Entropy
  • Why are we doing this?

10
Source Encoding Requirements
  • Decrease Lav
  • Unique decoding
  • Instantaneous decoding

11
Huffman Coding
  • 2-Step Process
  • Reduction
  • List symbols in descending order of probability
  • Reduce the two least probable symbols into one
    symbol equal to their combined probability
  • Reorder in descending order of probability at
    each stage
  • Repeat until only two symbols remain
  • Splitting
  • Assign 0 and 1 to the final two symbols remaining
    and work backwards
  • Expand code at each split by appending a 0 or 1
    to each code word
  • Example
  • m(j) A B C D E F G H
  • P(j) 0.1 0.18 0.4 0.05 0.06 0.1 0.07 0.04

12
Summary
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