Analytic Hierarchy Process-Based Cell Ranking In Cellular Networks Using Continuous Cellular Statistical Measure Technique For Telemedicine Applications

Abstract

ABSTRACTTelemedicine, e-medicine, and virtual theatres are upcoming techniques in medical field. In telemedicine application, remote monitoring of critical patients by doctor is a key value in which the real-time data is exchanged via mobile technology. Hence, provision of this sort of real-time bandwidth hungry multimedia critical data seamlessly over mobile networks is a challenging task. In present cellular era, demand towards video-based multimedia services is growing enormously against basic voice services. For instance, the latest smartphones equipped with social networking applications are more popular making voice services obsolete. Hence, allocation of bandwidth efficiently to video, multimedia applications, and selection of optimal cell is a challenging task. In this paper, a novel technique namely continuous cellular statistical measure (CCSM) for optimal cell selection among cell cluster based on cellular statistics such as call blocking ratio (CBR), signal to interference plus noise ratio (SINR), and inter cell interference (ICI) is introduced especially for telemedicine applications. These parameters are measured and stored in Network Management Entity of the cell cluster. Network management entity is proposed in master base station of a cell cluster. The master base station analyses the statistics of all cells in a cluster periodically. The cells are ranked based on rule-based ranking using analytic hierarchy process. The ranking is communicated to all cells in a cluster for optimal cell selection. Thus, CCSM technique reduces unnecessary handover during transmission of real-time critical data to mobile doctor. So, by analysing cell statistics such as SINR, CBR, and ICI optimal cell among cell cluster is estimated using CCSM technique.