238_1_lecture4 - EE 238: Multimedia communications and...

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1 EE 238: Multimedia communications and processing Prof. Mihaela van der Schaar email: [email protected] www-page: www.ee.ucla.edu/~mihaela
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2 Lecture 4: Joint source and channel coding over packet networks
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3 Outline Channel and network models Joint source-channel coding for media applications Error control and processing for multimedia over packet networks (with and without feedback) Questions/comments/observations are always encouraged, at any point during the lecture!!
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4 Basic components of a digital communication system The source encoder removes the redundancy in the digital data produced by the source and outputs an information sequence. The channel encoder adds redundancy to the information sequence so that channel errors can be detected or corrected. The output of the channel encoder is a finite sequence of symbols called a channel codeword. The set of possible channel codewords is called a channel code.
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5 Basic components of a digital communication system The modulator maps the channel codeword to a signal that is suitable for transmission over a physical channel. The demodulator converts the received signal into a discrete sequence of real numbers of the same length as the channel codeword.
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6 Multimedia Source Coding Application OSI Layer Application layer error resilience and bandwidth adaptation Streaming media Concepts (Scheduling, Packetization) Transport Network MAC PHY Joint Source- Channel Coding Over Packet Networks Where does this lecture fit in the overall communication system architecture? Channel models (chapter 8.1 -8.3) Joint source-channel coding (chapter 7.5 and 9)
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7 Types of transmission errors Random bit errors - bit inversion, insertion, deletion (imperfections of physical medium) Erasures - Packet loss (congestion, excessive delay) - Erroneous packets (burst of bit errors) Typical networks are unreliable - Wireless networks: random bit errors, long burst errors, and possibly link downs - Internet: packet loss and variable delay due to network congestion
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8 Simple information theory concepts
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9 Mutual information
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10 Discrete Memoryless Channel (DMC) X Y Channel (| ) p yx A DMC is characterized by the relationship between its input X and its output Y , where X and Y are two (hopefully) dependent random variables. Therefore, a DMC is usually represented by the conditional probability (|) pyx of the channel output Y given the channel input X .
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11 Examples of channel capacity
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12 Binary Erasure Channel (BEC) The most-simple DMC channel model that could be used for representing an Internet link or route is the BEC, which is shown below: ± The input X is a binary random variable that can be either a zero or one. ± A loss parameter δ , which represents the probability that the input is lost (“erased” or “deleted”) when transmitted over the BEC channel.
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This note was uploaded on 10/19/2011 for the course ELECTRICLA 216A taught by Professor Marković during the Fall '10 term at UCLA.

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238_1_lecture4 - EE 238: Multimedia communications and...

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