A Dissertation submitted in ful llment of the requirements for the degree of Master
of Science in the
School of Electrical and Information Engineering
January, 2017 / Permutation codes provide the required redundancy for error correction in a noisy
communication channel. Combined with MFSK modulation, the outcome produces
an e cient system reliable in combating background and impulse noise in the com-
munication channel. Part of this can be associated with how the redundancy scales
up the amount of frequencies used in transmission.
Permutation coding has also shown to be a good candidate for error correction in
harsh channels such as the Powerline Communication channel. Extensive work has
been done to construct permutation code books but existing decoding algorithms
become impractical for large codebook sizes. This is because the algorithms need
to compare the received codeword with all the codewords in the codebook used in
encoding.
This research therefore designs an e cient soft-decision decoder of Permutation
codes. The decoder's decision mechanism does not require lookup comparison with
all the codewords in the codebook. The code construction technique that derives the
codebook is also irrelevant to the decoder.
Results compare the decoding algorithm with Hard-decision plus Envelope Detec-
tion in the Additive White Gaussian Noise (AWGN) and Rayleigh Fading Channels.
The results show that with lesser iterations, improved error correction performance
is achieved for high-rate codes. Lower rate codes require additional iterations for
signi cant error correction performance. The decoder also requires much less comup-
tational complexity compared with existing decoding algorithms. / MT2017
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:wits/oai:wiredspace.wits.ac.za:10539/22995 |
| Date | January 2017 |
| Creators | Kolade, Oluwafemi Ibrahim |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | Online resource (xiii, 83 leaves), application/pdf |
Page generated in 0.002 seconds