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Enhancing the quality of voice communications by acoustic noise cancellation (ANC) using a low cost adaptive algorithm based Fast Fourier Transform (FFT) and circular convolution

In this paper a module consisting of a Fast Least Mean Square (FLMS) filter is modeled and verified to eliminate acoustic noise, which is a problem in voice communication. However the acoustic noise cancellation (ANC) is modeled using digital signal processing technique especially Simulink Blocksets. The needed algorithm code is generated in Matlab Simulink programming. At the simulation level, results of simulink implementation prove the module behavior for cancellation of noise in voice communication using the FLMS adaptive algorithm. The main scope of this paper is to implement the module, benefiting the advantage of DFT (Discrete Fourier transform) circular convolution properties and Fast Fourier Transform (FFT) high computation speed in frequency domain rather adaptive algorithms Normalized Least Mean Square (NLMS) and Recursive Least Square (RLS) in time domain with high complexity, also the simplicity of the implementation using simulink programming.