Electrical Communications Systems ECE.09.433 Spring 2019 Lecture 7b March 7, 2019 Shreekanth Mandayam ECE Department Rowan University http://engineering.rowan.edu/~shreek/spring19/ecomms/

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

ECOMMS: Topics

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 4-G  5-G protocols.com

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?

Principle 1 0 1 0……… Digital message 1 1 0 0 Digital Analog code 1 1 1 0 1 0……… 0 0 Digital code Analog message modulate 1 0 1 0 AM Sinusoidal carrier FM PM AM & PM

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

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

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?

Source Encoding Requirements Decrease Lav Unique decoding Instantaneous decoding

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) 0.1 0.18 0.4 0.05 0.06 0.1 0.07 0.04

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