Speech Quality While Roaming in Next Generation Networks

Abstract

In NGNs, handovers between different wireless access technologies provide seamless roaming during voice calls. The resulting speech quality depends on the audio bandwidth of the speech codecs used in the respective networks, as well as on degradations resulting from the handover, coding, and packet loss. We present the results of four listening experiments where speech quality is quantified as a function of network and codec characteristics, and compare them to estimations obtained from instrumental models. The results show when and under which circumstances a network handover and/or codec changeover should be scheduled in order to obtain better speech quality. This is important for the development of high-quality roaming strategies.

Dynamic Bayesian Networks for Sequential Quality of Experience Modelling and Measurement

“…We simulate this case by changing the codec from NB to WB once the QoE of the user is predicted to fall below or remain constant for some time at a particular threshold (3 for MOS) at the end of four-week (t 4 ). It was shown in [16], that ITU-T G.722 codec gives higher QoE than NB codecs such as ITU-T G.711 and ITU-T G.729 codecs. Thus, we generated data based on this observation, for time t 5 to t 6 and use our algorithm to re-estimate by re-learning the model parameters.…”

“…Mostly experiments are conducted in the lab settings or living lab settings [4] and then conclusions regarding QoE are drawn. This is particularly true for research done on voice and video quality assessment domain [16]. There is also no provision in the current ITU-T and ETSI recommendations and standards such as the ITU-T G.107 [5] and ETSI STF 354 [2] to measure QoE over time.…”

Performance evaluation of a decision-theoretic approach for quality of experience measurement in mobile and pervasive computing scenarios

“…Recently, Moller et al [14] and Tsompanidis et al [18] consider the problem of QoE measurement for VoIP applications in heterogeneous access networks by considering network impairments such as handoffs and network congestion. However, they consider models such as the ITU-T E-Model [4] for QoE measurement.…”

“…Relationships between several parameters such as delay, jitter, packet loss and users QoE has been studied widely in the literature [14], [18]. Even then, these relationships may not correctly model users QoE due to dynamic nature of underlying network conditions and the user environment where uncertainty plays a dominant role.…”

“…In both cases, we assume that handoff occurs at the middle of a voice call. In reality, location of handoff within a call can have different impact in users QoE [14]. 3) IEEE 802.11b WLAN network congestion : To determine the effects of network congestion on voice quality, we used the IEEE 802.11b WLAN connection.…”