Reduction of the Noise Effect to Detect the DSSS Signal using the Artificial Neural Network

Autor: Aya Y. Khudhair, Rajaa aldeen Abd Khalid
Rok vydání: 2021
Předmět:
Zdroj: 2021 1st Babylon International Conference on Information Technology and Science (BICITS).
DOI: 10.1109/bicits51482.2021.9509880
Popis: This paper presents the design of a direct sequence spread spectrum system. the data bits are transmitted over the Additive White Gaussian Noise (AWGN) channel this makes the receiver in direct sequence spread spectrum DSSS system )not able to retrieve the original bits without noise and to solve this problem, the proposed model using backpropagation (ANN) artificial neural network, ANN is used to reduce the added noise values to data at 10000 bits each bit is extended by the length of PN code (127 bits ), ANN is succeeded in elimination the noise values in the most cases of Signal-to-Noise Ratio (SNR) . MATLAB, being utilized to design DSSS systems for obtaining a system parameter as well as The bit error rate BER performance of the system is evaluated in the AWGN environment at different values of SNR. The proposed method is succeeded in the detection of the data signal at BER equals 0 in the most cases of SNR.
Databáze: OpenAIRE