Citas bibligráficas
Belito, A., (2018). Mejora del desempeño de un sistema de comunicación del habla utilizando la codificación convolucional en un canal con desvanecimiento rápido [Tesis, Universidad Nacional de Ingeniería]. http://hdl.handle.net/20.500.14076/17034
Belito, A., Mejora del desempeño de un sistema de comunicación del habla utilizando la codificación convolucional en un canal con desvanecimiento rápido [Tesis]. : Universidad Nacional de Ingeniería; 2018. http://hdl.handle.net/20.500.14076/17034
@mastersthesis{renati/709816,
title = "Mejora del desempeño de un sistema de comunicación del habla utilizando la codificación convolucional en un canal con desvanecimiento rápido",
author = "Belito Allaucca, Aquiles",
publisher = "Universidad Nacional de Ingeniería",
year = "2018"
}
In the present paper we proposed the use of convolution coding to improve the bit error rate in a communication system using the speech coder CELP (Linear Prediction Code Excited) and CP-OFDM modulation, since the channel where the simulation is carried out generates errors of the transmitted bits, therefore, it is important to detect and correct errors in the receiver in an optimal way and convolutional coding with the viterbi algorithm is a good option. The method or procedure to verify the performance of the system is having a channel model that approximates reality, the channel model based on the Markov chains proposed by Gilbert allows to reduce the time and complexity of the simulation compared to other similar techniques based on 2-state Markov chains, also known as bursts of bit errors that is very similar to what happens in mobile communications. The models channel discrete require little computational capacity for simulation because it is subject to probabilities error of bits, if used the physical equations of the channel fast fading, effect doppler, multipath signals and modulation CP-OFDM less to avoid errors caused by the channel, the simulation requires capacity computational. In the investigation, also we consider these negative effects to determine the bit error probabilities and then simulate a system based on Markov chain model. Finally, the results of the measurement of the signal noise quantization of the speech are shown, the improvement of the bit error rate for a channel noise signal ratio of 20.0 dB using the convolutional encoder, and the improvement of speech coding with CELP using a stochastic code book with integer values and through opinion surveys the improvement of the subjective quality of the speech will be measured.
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