Customizable algorithm for data scheduling in long term evolution networks

Abstract

Long Term Evolution (LTE), a standard developed by the 3rd Generation Partnership Project (3GPP), is currently the 4G mainstream technology, providing technology convergence for this generation of cellular communication systems. LTE networks promise data transmission rates of 100 Mbps in the downlink channel. For this high throughput it needs to optimize the use of network resources. LTE uses scheduling techniques for radio resource allocation based on communication channel conditions. This paper presents a heuristic customizable algorithm for multi-user data scheduling in the LTE downlink channel that can prioritize selected types of services. The proposed scheduling scheme is a modified version of the proportional fairness scheduler that uses Analytic Hierarchy Process (AHP) techniques. This allows to aggregate performance criteria to improve resource allocation based on general traffic conditions and a set of predefined service priorities. The approach for this customization is to assign weights to certain parameters used in the resource allocation process, thus modifying the relative importance of these parameters and creating a hierarchy of criteria. Criteria for different types of data are added through comparison matrices. A comparison matrix quantifies the judgment of the decision maker with respect to the relative importance of different criteria. Thus the scheduler can be made flexible and adaptive to different traffic scenarios. Examples are given where video traffic is prioritized.