Hard handover for load balancing in long term evolution network

Abstract

This thesis presents a hard handover for load balancing in Long Term Evolution (LTE) network. LTE is a cellular self-organizing network (SON) standardized by Third Generation Project (3GPP) to optimally provide high data rate and high quality of service to end users. However, the huge amount of data requirements for the diverse multimedia services by LTE subscribers is fast affecting the network’s quality of service (QoS) negatively. On the other hand, the need for an optimized energy consumption algorithm to reduce the network access cost and optimize the battery life of the user’s equipment (UE) is also on the increase. Therefore, the main aim of this thesis is to provide a new solution for load control as well as providing energy efficient solution for both the network and the mobile devices. In the first contribution, a new network-energy efficient handover decision algorithm for load balancing is developed. The algorithm uses load information and reference signal received power (RSRP) as decision parameters for the handover decision scheme. The second contribution focuses on the development of an optimized handover decision algorithm for the load balancing and ping-pong control. The algorithm uses the cell load information, the received signal strength (RSS) and an adaptive timer as inputs for the handover decision procedure. Besides, the third contribution is on the development of a handover decision algorithm to optimize the UEs energy consumption as well as load balancing optimization. Overall, key performance indicators such as load distribution index (LDI), number of unsatisfied users (NUU), cumulative number of ping-pong handover request (CNPHR), cumulative number of non-ping-pong handover request (CNNPHR), average throughput of the cell (ATC), handover blocking rate (HBR), new call blocking rate (NCBR) and number of handover calls (NHC) were evaluated through simulations. The results were compared with some other works in the literature. In particular, the proposed algorithm achieved over 10% higher for LDI, 50% lower for NUU, 30% higher for CNPHR and 5% lower for CNNPH when compared with works in the literature. Other results are 10% higher for ATC, 75% lower for HBR and 40% lower for NCBR. In general, the proposed handover decision algorithm for energy efficient load balancing management in LTE has proven its ability for energy consumption optimization, load balancing management and pingpong handover control.