1. Electrical Communications Systems ECE.09.433 Spring 2019
Lecture 7b March 7, 2019
Shreekanth Mandayam
ECE Department
Rowan University

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 (Ethernet)
ARPANET, 1969
IEEE (FDDI)
ISO-OSI 7-layer Network Reference Model
CDMA
GSM
VOIP
4-G  5-G
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 1 0 1 0……… Digital message 1 1 0 0 Digital Analog code
………
Digital
code
Analog
message
modulate AM
Sinusoidal carrier FM PM
AM & PM

7. Digital Communication Paradigms
Multiplexer
Message 2
Message 3
Message 1 1 2 3 S
Demultiplexer
Circuit Switching
Sync bits
Packet Switching
Header
bits
Packetizing
Message 2
Message 3
Message 1 1 H 2 3
Depacket-izing

8. Digital Communications Transceiver
Anti-
aliasing
Filter
Data
Encryption
Encoder
Error
Control
Encoder
Source
Encoder
Channel/
Line
Encoder
Sampling
Quantization
MUX
Modulator
ADC
Analog i/p
CODEC
MODEM
Multiple access channel
Analog o/p
Data
Encryption
Decoder
Error
Control
Decoder
Audio
Amp
Reconstruction/
DAC
Source
Decoder
Equalization /
Decision
Circuits
DEMUX
Demod-ulator

9. Source Encoding Why are we doing this? Encoder Source Encoded Symbols
Analog
Message
A/D
Converter
Digital
Source
Encoder
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 Splitting Example
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)

12. Summary No lecture on Tuesday, March 1 Finish Lab 2 in the evening
Tim is getting pizza