Low Density Parity Check Convolutional Decoding on Markov Channels

Low Density Parity Check Convolutional Decoding on Markov Channels

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Low Density Parity Check (LDPC) convolution codes, the convolutional counterparts of LDPC block codes, were presented in 1999. Along with the allure of good performance, LDPC convolutional codes (LDPC CC) allow for variable packet length transmission, which makes them suitable for use in packet-switched networks. This thesis describes a technique to decode LDPC CCs over channels with memory, a.k.a. Markov channels. A review of the concepts for iteratively decoding LDPC block and Convolutional codes over memoryless channels is followed by a review of decoding LDPC block codes on channels with memory. A sequential decoding algorithm for LDPC CCs over Markov Channels is derived, and demonstrated over the Gilbert Elliot channel as an example. Complexity analysis reveals that the number of operations per time step decreases, at the expense of increased memory and latency. This trade-off is favorable for low-power applications.In fact, all (digital) systems that can be modelled after fig. 1.1 can employ digital error control coding. The figure shows the block diagram of a digital communications system with a message source that inputs symbols into a channel encoderanbsp;...


Title:Low Density Parity Check Convolutional Decoding on Markov Channels
Author: Manohar P. Kashyap
Publisher:ProQuest - 2007
ISBN-13:

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