Self-Organizing Networks Prospects for Group Scheduling for Disaster Relief and Public Safety Communications in Cellular Networks
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The demand for cellular communications is anticipated to continue its hasty growth in the forthcoming future, triggered by new bandwidth hungry applications such as voice over LTE, high-definition video streaming, and multimedia file sharing in mobile phones. This has placed enormous pressure on cellular communications in terms of demand for Quality of Service (QoS), capacity, and resource management. Henceforth, the apposite utilization of obtainable spectrum is required. Public Safety (PS) organizations’ capability to exchange information is crucial to meliorate the coordination in emergency junctures. Recent catastrophes have underlined the need to enhance broadband and seamless connectivity to the PS organizations. This thesis outlines the governing issues necessitated in this, and also additional requirements of the network are addressed regardless of dynamic channel conditions and locations. In this thesis, subscribers are divided into groups viz., PS groups and regular subscriber groups. A new scheme, beyond the type of services being used by subscribers, priorities and fairness, is developed. In order to abridge operational costs and efforts, SONs (Self Organizing Networks) are implemented in this thesis and the prospects have been discussed. Additionally, Group Scheduling is implemented to achieve better performance for PS and regular subscribers groups. An advanced scheduling algorithm for group scheduling is developed which provides better QoS for multi-services and a better trade-off between Quality of Service and radio resource management. This scheduling algorithm provides a better balance between multi-QoS purveying to support mixes of sensitive traffic and best effort traffic. This phenomenon is used to choose the best subscriber and the group. Several metrics have been devised and are used for this purpose. Extensive simulation results are shown for both the conditions viz., normal and emergency conditions.
Table of Contents
Introduction -- Background -- Our work -- MATLAB code implementation -- Results and analysis -- Conclusions