Method for reducing of noise by improving signal-to-noise-ratio in wireless LAN

TL;DR

This paper proposes a noise reduction method using linear prediction error filters and adaptive digital filters to improve signal-to-noise ratio in wireless LAN, applicable to speech, images, and MRI.

Contribution

It introduces a combined approach with LPEF and ADF for noise reduction in speech and MRI, demonstrating effectiveness in wireless LAN environments.

Findings

Effective noise reduction in speech signals using LPEF and ADF.

Wideband MRI achieves image quality comparable to conventional MRI in SNR.

Method improves signal clarity in wireless LAN transmissions.

Abstract

The signal to noise ratio (SNR) is one of the important measures for reducing the noise.A technique that uses a linear prediction error filter (LPEF) and an adaptive digital filter (ADF) to achieve noise reduction in a speech and image degraded by additive background noise is proposed. Since a speech signal can be represented as the stationary signal over a short interval of time, most of speech signal can be predicted by the LPEF. This estimation is performed by the ADF which is used as system identification. Noise reduction is achieved by subtracting the reconstructed noise from the speech degraded by additive background noise. Most of the MR image accelerating methods suffers from degradation of acquired images, which is often correlated with the degree of acceleration. However, Wideband MRI is a novel technique that transcends such flaws.In this paper we proposed LPEF and ADF for reducing the noise in speech and also we demonstrate that Wideband MRI is capable of obtaining images with identical quality as conventional MR images in terms of SNR in wireless LAN.