coding - Coding for Communications Lecture 1 Introduction...

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1 Coding for Communications Lecture 1 Introduction Channel models Motivation Digital communications : Computer networks, wireless telephony, data and media storage, RF communication (terrestrial, space) • Transmission over communication channels is prone to errors , due to: – background noise, mutual interference between users, attenuation in channels, mechanical damage, multipath propagation, …
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2 Model of a communication system Coder and decoder in a communication system
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3 How do we model the possibility that errors are generated during transmission over the channel? source source encoder channel encoder modulator channel destination source decoder channel decoder (error correction) demodulator encoded bits received bits We denote as p the probability that an output bit contains an error The BSC models the insertion of errors during transmission over the channel? source source encoder channel encoder modulator channel destination source decoder channel decoder (error correction) demodulator encoded bits received bits We denote as p the probability that an output bit contains an error ( bit error probability or cross-over probability ) Equivalent channel model
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4 A BSC model could also include the encoder-
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This note was uploaded on 04/24/2011 for the course EE 4421 taught by Professor Mondin during the Spring '11 term at California State University Los Angeles .

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coding - Coding for Communications Lecture 1 Introduction...

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