A new approach for testing voice quality

With a rapidly growing number of 5G networks deployments, the launch of new voice services over 5G New Radio (VoNR) is becoming the top priority for operators. But responding to this demand creates a challenge: maintaining the voice service quality and growing voice revenue through VoLTE expansion, while minimizing CAPEX and OPEX.  In addition, the competition of carrier-grade voice services (VoLTE, VoNR) with OTT voice applications is predicted to grow exponentially with 5G network deployments, presenting a continuously persistent threat to MNOs’ voice service revenue. The powerful MNOs’ counter to this threat is the expansion of the carriers’ VoLTE/VoNR services, while continuously monitoring and benchmarking against OTT voice applications to maintain their voice services at high QoE levels.

Download our updated whitepaper to learn how Infovista’s sQLEAR voice QoE predictor, newly standardized as ITU-T 5.655.1,  is specifically designed to answer these concerns and goals. sQLEAR uniquely bundles network parameters and standardized voice codec and client information, and uses machine learning to provide mobile operators with the network-centric, device-agnostic, audio path-independent, real-time view of the true voice quality being delivered through their 4G and 5G networks. Thus, sQLEAR focuses on network performance to:

• Accurately evaluate device-agnostic voice quality trends and predict future QoE delivery
• Cost-efficiently increase the quality of your VoLTE services using network centric optimization 
• Understand your VoNR quality through network-centric troubleshooting and root-cause analysis   
• Protect your existing voice revenue against OTT alternatives using device agnostic benchmarking