An Integrated Approach for the Estimation of Mobile Subscriber Geolocation

The continuous growth of wireless services market, fuels the need for precise location dependent services, leading researchers from academia and industry to reassess existing geolocation methods regarding accuracy and availability of position estimation. The proposed method for mobile subscriber geolocation utilizes key concepts from estimation theory and specifically the Kalman filter algorithm to determine an optimal estimate on the actual system state (which primarily includes location, velocity) based on the observations acquired by employing network- or terminal-based techniques, which are briefly presented and assessed thereafter. Given the proven limitations of individual techniques, the alternative strategies for fusion of data are outlined, the details of the operation of a fusion scheme based on the Kalman filter are discussed and the impact of the proposed work over conventional methodologies is quantified.     

Serverless streaming for emerging media: towards 5G network-driven cost optimization

Multimedia Tools and Applications - Immersive 3D media is an emerging type of media that captures, encodes and reconstructs the 3D appearance of people and objects, with applications in...     

A utility-based fuzzy TOPSIS method for energy efficient network selection in heterogeneous wireless networks

Mobile terminals in 4G heterogeneous wireless networks continuously undergo horizontal and vertical handovers. In order for a mobile terminal to be connected to a network in the best possible way in terms of QoS performance and energy consumption, access network selection as the main decision within the handover process is obviously crucial. This paper presents a novel method that takes into account user preferences, network conditions, QoS and energy consumption requirements in order to select the optimal network which achieves the best balance between performance and energy consumption. The proposed network selection method incorporates the use of parameterized utility functions in order to model diverse QoS elasticities of different applications, and adopts different energy consumption metrics for real-time and non-real-time applications. User preferences are easily configured for different application and situation contexts through the use of linguistic assessments and their representation as triangular fuzzy numbers. The aggregation of multiple criteria for the calculation of the overall rating of the networks is performed through the use of the Fuzzy Set Representation TOPSIS method that resolves the issue of inconsistency related to conflicting decision criteria and is modified through the use of the employed utility functions for the elimination of the ranking abnormality problem. Finally, simulations are conducted in order to demonstrate how the proposed method would work and confirm its suitability and effectiveness.