  Here we have proposed two decoding strategies of low-density parity-check
(LDPC) codes over Markov noise channels with bit flipping noise. The
sum-product algorithm used for decoding LDPC codes over memoryless channels is
extended to include channel estimation and how much gain we obtain by doing so
is simulated and verified. LDPC codes have been studied for years over
memoryless channels and are known to have excellent performance. However, these
codes over channels with memory is the topic of current research. Here,
channels with memory are characterized by Markov modeling which is a useful
busty channel model. With sufficient no. of states, they are able to model
sufficient noise characteristics. We have gone for a two-state system as it
shows a good compromise between complexity and performance.
