| Summary: | 碩士 === 國立臺北大學 === 通訊工程研究所 === 94 === Turbo code was emphasized on its performance that achieves very
close to {it Shannon-Limit}. Recently, turbo-coding was extensively
used in many communication systems such as WCDMA system and 3GPP
system, etc. The turbo decoding consists of {it a posteriori
probability (APP) }algorithm and iterative decoding algorithm that
utilize channel information in decoding process. Hence, an efficient
method to estimate the signal-to-noise ratio (SNR) of the channel is
very important and necessary. If the online estimation for SNR of
the channel is mismatched badly, the performance degradation will be
very serious in turbo decoding. Several online channel estimation
methods, whose estimation complexities are too high for practical
decoder design, were proposed before. In this thesis we propose a
new on-line method to estimate the SNR of the additive while
Gaussian noise (AWGN) channel on-line. Our goal is to get an
acceptable performance and reduce the complexity of the estimation.
The proposed decoding algorithm first runs Max-Log-MAP algorithm for
a certain amount of iterations, utilizes the log-likelihood ratios
as well as the absolute first order statistics to estimate the
channel characteristics, and then switches to Log-MAP algorithm
after the channel estimation are done. According to simulation
results over the AWGN channel, our method has similar performance to
the previous method but with much lower complexity.
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