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This lecture provides an introduction to digital communications, including topics such as digital communications transceivers, source encoding, and Huffman coding. It also explores the rationale behind digital communications and discusses various digital communication paradigms.
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Electrical Communications SystemsECE.09.331Spring 2009 Lecture 11aApril 7, 2009 Shreekanth Mandayam ECE Department Rowan University http://engineering.rowan.edu/~shreek/spring09/ecomms/
Plan • Digital Communications • Introduction • Digital Communications Transceiver (CODEC/MODEM) • Digital Baseband Communications • Source Encoding • Huffman Coding
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
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 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
Message 1 Message 1 Multiplexer 2 Demultiplexer 1 2 3 1 S 2 3 S Message 2 Message 2 Message 3 Message 3 3 H H 1 Depacket-izing Message 1 2 H Message 1 3 H H 1 Depacket-izing Packetizing Message 2 Message 2 2 H 3 H Message 3 Depacket-izing H 1 Message 3 2 H Digital Communication Paradigms Circuit Switching Sync bits Packet Switching Header bits
Digital Communications Transceiver Anti- aliasing Filter Error Control Encoder Data Encryption Encoder Channel/ Line Encoder Source Encoder Sampling Quantization Modulator MUX ADC Analog i/p CODEC MODEM Multiple access channel Analog o/p Error Control Decoder Data Encryption Decoder Source Decoder Audio Amp Reconstruction/ DAC Equalization / Decision Circuits Demod-ulator DEMUX
Analog Message A/D Converter Source Encoder Digital Source Source Encoding • Why are we doing this? Source Symbols (0/1) Source Entropy Encoded Symbols (0/1) Source-Coded Symbol Entropy
Source Encoding Requirements • Decrease Lav • Unique decoding • Instantaneous decoding
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