Optimization of Speech signal for improving BER using Adaptive 3-D Turbo Codes
Suman Kshirsagar, Assistant professor in Department of ECE, CBIT, Hyderabad, India.
Manuscript received on November 17., 2019. | Revised Manuscript received on November 24 2019. | Manuscript published on 30 November, 2019. | PP: 12692-12695 | Volume-8 Issue-4, November 2019. | Retrieval Number: D7655118419/2019©BEIESP | DOI: 10.35940/ijrte.D7655.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The introduction of third component in conventional turbo codes improved the code performance for a wide range of block lengths and coding rates with very low error rates. But the parameters such as permeability and permittivity rates were static under noisy environments and hence their adaptability to noisy environment was poor. The proposed A3D-TC has overcome the aforesaid problem. The parameters are made adaptive by generating a Genetic Algorithm (GA) based knowledge source. The bit error rate was minimized by generating parameters based on noise and signal strengths. The improvement is observed for speech signal. At high noise rates the speech signal exhibits minimum bit error rate using this GA based knowledge source and for very few iterations they gave error free signal at low values of signal to noise ratio.
Keywords: A3D-TC, Genetic Algorithm, Permeability Rate, Permittivity Rate, 3D-TC, Bit Error Rate, Signal To Noise Ratio, Iterations.
Scope of the Article: Parallel and Distributed Algorithms.