Evaluation of handover effectiveness with progressive user behavior in self-organized LTE networks

Abstract

In LTE networks, when a user moves from one sector to another sector within the same eNB, it’s essential to keep the ongoing call steady. This occurrence is referred to as a handover (HO). The ping-pong and call drop rate may be minimized with proper HO decision-making, resulting in a higher quality of service. For this reason, it’s quite difficult to set up both the handover failure and handover ping-pong simultaneously. This study evaluates HO performance by adjusting several HO control parameters, such as HO offset, time to trigger, and HO margin, to get the best possible results. The HO control settings may be adjusted using a hybrid method called tent chaotic map, adaptive inertia weight, opposition-based learning into whale optimization algorithm (TAOWOA). Apart from that, by automating MLB and TAOWOA, network performance is improved by using a self-organized network. Under progressive traffic loads and user mobility, the HO failure (HOF), call dropping ratio (CDR), HO ping-pong(HOPP), and packet delivery ratio are assessed. Performance parameters based on optimization-MLB have significantly increased performance when compared to conventional HO performance improvement methods, according to the simulation findings.