COMBINING MUSIC AND LMS ALGORITHMS ON THE RECTANGULAR MICROPHONE ARRAY FOR MEETING ROOMS

Abstract

This study presents a beamforming microphone that utilizes a uniform rectangular array (URA) structure specifically designed for meeting rooms. The
microphone operates by combining the multiple signal classification (MUSIC) algorithm and the least mean squares (LMS) algorithm to effectively track and
direct the beam towards the desired signal direction. This results in reduced power consumption and energy savings for the microphone. The results achieved
through simulation for three signals within the frequency range of 1.3kHz to 1.4kHz satisfy the specified criteria. When comparing the performance of MUSIC
with the conventional beamforming (CB) algorithm and minimum variance distortionless response (MVDR) algorithm, the MUSIC algorithm achieved a peak-
to-average power ratio (PAPR) of 50dB at a signal-to-noise ratio (SNR) of 36dB. In contrast, the MVDR and the CB achieved PAPRs of 36dB and 10dB, respectively.
Prior to reaching saturation, the root mean square error (RMSE) of the MUSIC algorithm was 1.3° at the SNR of 0dB, which was the smallest compared to the
MVDR algorithm at 1.9° and the CB algorithm at 5.1°. Following the point of saturation, the MVDR algorithm achieved the same level of error as the MUSIC
algorithm. However, the CB algorithm remained higher than 5 degrees. Despite the LMS algorithm's slower convergence time of approximately 0.06s in
comparison to the Recursive Least Squares (RLS) algorithm, there is no difference in error thereafter.