Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/49825
Título: Incorporating Wireless Communication Parameters Into the E-Model Algorithm
Palavras-chave: E-model
Multiple-Input-Multiple-Output (MIMO)
MIMO system E-model
Packet loss
Speech quality assessment
Wireless communication
Múltiplas Entradas e Múltiplas Saídas
Qualidade vocal - Avaliação
Comunicação sem fio
Data do documento: Fev-2021
Editor: Institute of Electrical and Electronics Engineers (IEEE)
Citação: RODRÍGUEZ, D. Z. et al. Incorporating Wireless Communication Parameters Into the E-Model Algorithm. IEEE/ACM Transactions on Audio, Speech, and Language Processing, [S. I.], v. 29, p. 956-968, 2021. DOI: 10.1109/TASLP.2021.3057955.
Resumo: Telecommunication service providers have to guarantee acceptable speech quality during a phone call to avoid a negative impact on the users’ quality of experience. Currently, there are different speech quality assessment methods. ITU-T Recommendation G.107 describes the E-model algorithm, which is a computational model developed for network planning purposes focused on narrowband (NB) networks. Later, ITU-T Recommendations G.107.1 and G.107.2 were developed for wideband (WB) and fullband (FB) networks. These algorithms use different impairment factors, each one related to different speech communication steps. However, the NB, WB, and FB E-model algorithms do not consider wireless techniques used in these networks, such as Multiple-Input-Multiple-Output (MIMO) systems, which are used to improve the communication system robustness in the presence of different types of wireless channel degradation. In this context, the main objective of this study is to propose a general methodology to incorporate wireless network parameters into the NB and WB E-model algorithms. To accomplish this goal, MIMO and wireless channel parameters are incorporated into the E-model algorithms, specifically into the Ie,eff and Ie,eff,WB impairment factors. For performance validation, subjective tests were carried out, and the proposed methodology reached a Pearson correlation coefficient (PCC) and a root mean square error (RMSE) of 0.9732 and 0.2351, respectively. It is noteworthy that our proposed methodology does not affect the rest of the E-model input parameters, and it intends to be useful for wireless network planning in speech communication services.
URI: https://ieeexplore.ieee.org/document/9351640
http://repositorio.ufla.br/jspui/handle/1/49825
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