These days, the relationship between humans and the Internet is undeniable and deeply intertwined, such that the Internet can be considered one of humanity’s essential and vital needs. What would happen to communication, businesses, and the overall lifestyle of humans if the Internet ceased to exist? How would short-term or long-term disruptions impact the economy, welfare, and other major issues in countries? To what extent can the quality of Internet services influence various dimensions, from individuals to cities, countries, and the world? Indeed, given the increasing and ever-growing need for this undeniable phenomenon in the current era, it is concluded that the quality of Internet services (QoS) has become a fundamental necessity today. Operators are in an endless race to provide the best services to their subscribers while striving to lead in technologies that enhance service quality. Consequently, the quality of services they provide determines their survival. With the advancement of mobile networks, a new concept of quality, known as Quality of Experience (QoE), has emerged. This concept considers not only the quality of services but also the user’s satisfaction with the provided service. Accurate measurement of QoE enables operators to offer services tailored to user satisfaction. Measuring and eva‎luating QoE has not been an easy task for operators, as it poses its own unique challenges. For instance, measuring and modeling QoE is highly complex and cannot be assessed using conventional methods based on specific parameters. Another significant challenge in eva‎luating QoE is that operators lack insight into users’ perceptions and feedback regarding the services during their usage. As a result, they are directly or indirectly striving to gather this feedback. In the following sections, methods for modeling quality and obtaining this feedback will be discussed. This can assist operators in meeting users’ quality requirements at any given moment and, consequently, enhance satisfaction with the quality of provided services. Additionally, machine learning models will be proposed to improve the accuracy of measuring this critical phenomenon, and various categories of QoE and QoS will be introduced based on the type of service offered.

12/11/2024 12:00:00 AM

85812

1403/11/24

Review of the eva‎luation Approaches of the Quality of Multimedia Experience in Mobile Phone Network

QoE (كيفيت تجربه) , QoS (كيفيت خدمات) , چند رسانه اي , يادگيري ماشيني

QoE (Quality of Experience) , QoS (Quality of Service) , Multimedia , Machine Learning