Channel
encoder, which includes a forward error correcting (FEC) code followed
by an interleaver, plays a vital role in improving the error performance
of digital storage and communication systems. In most of the
applications, the FEC code and interleaver parameters are known at the
receiver to decode and de-interleave the information bits, respectively.
But the blind/semi-blind estimation of code and interleaver parameters
at the receiver will provide additional advantages in applications, such
as adaptive modulation and coding, cognitive radio, non-cooperative
systems, etc. The algorithms for the blind estimation of code parameters
at the receiver had previously been proposed and investigated for known
FEC codes. In this paper, we propose algorithms for the joint
recognition of the type of FEC codes and interleaver parameters without
knowing any information about the channel encoder. The proposed
algorithm classify the incoming data symbols among block coded,
convolutional coded, and uncoded symbols. Further, we suggest analytical
and histogram approaches for setting the threshold value to perform
code classification and parameter estimation. It is observed from the
simulation results that the code classification and interleaver
parameter estimation are performed successfully over erroneous channel
conditions. The proposed histogram approach is more robust against the
analytical approach for noisy transmission environment and system
latency is one of the important challenges for the histogram approach to
achieve better performance.
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