KEYWORDS: Digital filtering, Signal processing, Wavelets, Electronic filtering, Data processing, Filtering (signal processing), Interference (communication), Signal to noise ratio, Error analysis, Computing systems
The article is devoted to increasing the efficiency of digital signal processing in the conditions of high level of interference, for which the efficiency and reliability of the transmission of information have a priority over the speed of transmission and the amount of CP resources used. The authors provide readers with the improvement of current methods in order to increase the performance of information transmitting in difficult conditions environment. The method of determining the decomposition coefficients, which uses the replacement of the biorthogonal coefficients of the wavelet decomposition with the approximation sum using a series of quasi-random delta sequences, is used in the work, which is used to eliminate the Gibbs effect in signal processing. The method for evaluating the spectrum of the signal for an adaptive threshold method, which uses a multi-window average estimation of the logarithmic spectrum of the signal, is improved. A method of the fast median filtration which processes the finite quantities of date vector with splitting an original data vector onto some parts has been developed. The method of parallel fast wavelet transform is improved, which uses the partition of the data vector into blocks for processing data using a local wavelet transform in the diagonal sequence. The theoretical researches and modeling demonstrate the significant efficiency of the newly proposed and improved methods.
In this article, we discuss the powerful class of channel codes referred to as turbo codes. We commence with a brief discussion for turbo decoding algorithms. It is proposed to use an PL-log-MAP algorithm. Some numerical results and research experiments, such as simulation for bit error rate estimation for images transmission, have been presented. The performance of the PL-log-MAP algorithm is shown to have the closest performance to the original log-MAP solution.
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