Speech Quality Assessment in Wireless Communications With MIMO Systems Using a Parametric Model

Communication service providers use specialized solutions to evaluate the quality of their services. Also, different mechanisms that increase network robustness are incorporated in current communication systems. One of the most accepted techniques to improve transmission performance is the MIMO system. In communication services, voice quality is important to determine the user’s quality of experience. Nowadays, different speech quality assessment methods are used, one of them is the parametric method that is used for network planning purposes. The ITU-T Rec. G107.1 is the most accepted model for wide-band communication systems. However, it does not consider the degradations occurring in a wireless network nor the quality improvement, caused by the MIMO systems. Thus, we propose a speech quality model, based on wireless parameters, such as signal-to-noise ratio, Doppler shift, MIMO configurations, and different modulation schemes. Also, real speech signals encoded by 3 operation modes of the AMR-WB codec are used in test scenarios. The resulting speech samples were evaluated by the algorithm described in ITU-T Rec. P.862.2, which scores are used as a reference. With these results, a wireless function, named <inline-formula> <tex-math notation="LaTeX">$I_{W-M}$ </tex-math></inline-formula> that relates the wireless network parameters with speech quality is proposed and inserted into the wide-band E-model algorithm. It is worth noting that the main novelty of the proposed <inline-formula> <tex-math notation="LaTeX">$I_{W-M}$ </tex-math></inline-formula> is the consideration of the quality improvement incorporated by MIMO systems with different antenna array configurations. The performance validation results demonstrated that the inclusion of <inline-formula> <tex-math notation="LaTeX">$I_{W-M}$ </tex-math></inline-formula> values into the R global score determined a reliable model, reaching a Pearson correlation coefficient and a normalized RMSE of 0.976 and 0.144, respectively.