Advances in QoS/E Characterization and Prediction for Next Generation Mobile Communication Systems

Advances in QoS/E Characterization and Prediction for Next Generation Mobile Communication Systems

Charalampos N. Pitas, Apostolos G. Fertis, Dimitris E. Charilas, Athanasios D. Panagopoulos
DOI: 10.4018/978-1-4666-8732-5.ch020
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Abstract

The scope of this work is to present a holistic approach in quality of service (QoS) and quality of experience (QoE) characterization and prediction in modern mobile communication networks. Analytically, multi radio access technologies have been deployed in order to deliver mobile services to quality demanded consumers. Quality of Experience (QoE) parameters describe the End-to-End (E2E) quality as experienced by the mobile users. These parameters are difficult to be measured and quantified. System Quality of Service (SQoS) parameters are metrics that are closely related to the network status, and defined from the viewpoint of the service provider rather than the service user. Moreover, E2E Service Quality of Service (ESQoS) parameters describe the QoS of the services and they are obtained directly from the QoE parameters by mapping them into parameters more relevant to network operators, service providers and mobile users. A useful technique for mobile network planning and optimization is to build reliable quality estimation models for mobile voice and video telephony service.
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Fundamentals Of Quality

Quality of Radio Coverage

Nowadays, mobile networks have been implemented on second (2G), third (3G) and beyond 3G (B3G) generation RAN's. KPIs of 2G and 3G RANs are recommended in recommendation. GSM networks were initially deployed in order to provide CS (circuit switched) mobile telephony service while enhancements like GPRS (General Packet Radio System) and EDGE (Enhanced Data Rates for GSM Evolution) delivered data services to the mobile users. Recently, WCDMA (Wideband Code Division Multiple Access) networks were planned to deliver multimedia services like video telephony and broadband packet data services. Nowadays, LTE (Long Term Evolution) networks based on OFDMA (Orthogonal Frequency Division Multiple Access) and MIMO (Multiple-Input and Multiple-Output) radio technology will launch the data rates to tens Mbps in order to provide bandwidth and QoS demanding full PS (packet switched) services.

Key Terms in this Chapter

Quality of Experience: The satisfaction a user experiences with a service.

Robust Optimization: A field of optimization theory that deals with optimization problems in which a certain measure of robustness is sought against uncertainty that can be represented as deterministic variability in the value of the parameters of the problem itself and/or its solution.

Fuzzy Systems: The term “fuzzy” refers to the fact that the logic involved can deal with concepts that cannot be expressed as the “true” or “false” but rather as “partially true”.

Quality of Service: The overall performance of a telephony or computer network.

Decision Tree: Is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one way to display an algorithm.

Data Mining: Is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use.

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