| Summary: | 博士 === 國立臺灣科技大學 === 電機工程系 === 102 === Communication systems are susceptible to impulse noise, particularly when
the impulse statistics are not time-invariant and are difficult to accurately
model. To address the challenge of impulse noise, a robust and efficient Viterbi
and turbo decoding schemes were devised over memory impulse noise channels.
By accommodating channel states, but without relying on statistical knowledge
of impulses, the Viterbi algorithm (VA) based on an expanded set of trellis
states, was employed to perform maximum likelihood decoding. A detailed
analysis of complexity for the proposed Viterbi decoding was offered; the analytical
results reinforced the efficiency of the proposed scheme compared with
the traditional VA. We also proposed robust turbo decoding algorithm over a
Markov Gaussian channel. The branch metrics obtained from the two- dimensional
trellis diagram of the proposed VA was adapted to propose robust turbo
decoding scheme.
The simulation results indicated that the proposed Viterbi and turbo decoding
schemes are compellingly robust: the bit error probability performance
level attained using the proposed decoders is remarkably close to that of an
optimal decoder, which uses impulse statistics; furthermore, the proposed decoders
were compared with the alpha-penalty function decoder (alpha-PFD).
The reported result showed that the proposed decoders are superior to an
alpha-PFD because alpha-PFD neglects the channel memory property and experiences
an error floor, in fairly general circumstances.
|
|---|
