Development of Genetic Algorithms Based Efficient Load Balancing Models for LTE Networks

Abstract

In the present decade, wireless technology shows a greater newlinegrowth. In addition, the recently increased usage and development of newlinehigh-end mobile devices with increased users has more demands for newlinehigh bandwidth. The model is expected to be developed with higher rate newlineof Quality of Service (QoS) with minimal complexities and cost. For newlinethat, in recent times, 4G or Fourth Generation wireless broad bands are newlinewidely used, which is a integration of wireless standards, which are newlinefurther enhanced into Long Term Evolution (LTE) technology. newlineAdditionally, the model involves in providing consistent data delivery newlinewith higher transmission rate with minimal latency. Efficient network newlineutilization and traffic management are considered as the significant newlinefactors of LTE models. newlineWhen the roaming mobile users continuously utilizes the network newlineresources, from one cell to another, there is a requirement for dynamic newlineload management. Hence, load balancing is more significant in self- newlineorganized network model, has become a emerging research domain in newlinerecent days. Moreover, the load balancing process involves in newlinetransferring the load from one cell to its neighbor based on overloading newlineand availability of free resources, which provides balanced load newlinedistribution, enhance QoS and network performances. With that cause, newlinethis work involves in developing Genetic Algorithm based Efficient newlineLoad Balancing (GA-ELB) Model. For attaining the objective, the newlinework presents three models. newline1. Opposition based Spider Monkey Optimization (OSMOA) for newlineCell Handover in LTE. newlinevi newline2. Spider Monkey Optimization for Efficient Load Balancing (SMO- newlineELB) for Optimal Cell Selection. newline3. Dynamic Load Balancing Mechanism using Advanced Real- newlineCoded Genetic Algorithm (DLBM-ARGA) for advanced newlinecommunications in LTE. newlineIn first phase of work, optimal cell selection process is derived newlinebased on the estimation of load factor in each cell.