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Due to the presence of interference from the neighboring symbols decoding complexity increases.
Specific realizations are shown to be better than alternatives of linear encoding and decoding complexity.
After describing the necessary preliminaries it deals with STBCs with low maximum-likelihood (ML) decoding complexity.
LDPC codes achieve better performance and lower decoding complexity than turbo codes, with a major drawback of high encoding complexity.
As soon as more languages are considered the training and decoding complexity of the speech recognizer increases.
It supports linear decoding complexity for maximum-likelihood (ML) decoding.
Simulation results show that the proposed scheme reduced decoding complexity more than the FC scheme.
The decoding complexity reduction is commonly achieved by exploiting the orthogonality embedded in the STBC codeword.
Time should be considered only for decoding complexity comparison between the different SI techniques.
The huge size causes both decoding complexity and decoding time to increase.
Then, the increase of N1 has a negative impact on the IT and ML decoding complexity.
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