Handover and load balancing self-optimization models in 5G mobile networks

The need for load balancing will be more significant in fifth generation mobile network and beyond due to the massive upsurge in the quantity of users and rising use of small cell sizes. The load balancing function must be efficiently designed to distribute loads between various cells by moving excess traffic from high-load cells to adjacent inactive cells. The load balancing self-optimization feature is an important function that optimises the handover control parameter by switching some loads in overloaded cells to adjacent cells with fewer loads. This paper has focused on analysing the performance of load balancing self-optimization within fifth generation cellular networks. Also, this paper provides a brief overview about load balancing in 5G and 6G mobile networks and highlighting the sources of issues, technical challenges, some of the suggested solutions and highlighting the research challenges that are needed to be addressed in the second phase of 5G and 6G mobile networks. At the same time highlighting the research that has been conducted in the literature to address these stranding issues. Study also, developing simulation model that can be utilized to study, investigate and analysing LBSO in 5G mobile network with a variety of mobile speed scenarios. The work developed a simulation model that is utilized to study, investigate, and analyse LBSO in 5G mobile networks with a variety of mobile speed scenarios. Optimization algorithms were selected from the literature and validated to ensure their efficiency and functionality with different mobility scenarios, based on the UE condition after each measurement report. The network evaluation and analysis have been conducted in terms of ping-pong handover probability, radio link failure and spectral efficiency. The simulation outcomes explain that the Optimization based on the Distance algorithm demonstrated a noticeable performance enhancement through significantly reduces the PPHP, RLF and SE for different mobile speed scenarios over the entire simulation as compared to the Cost Function and Fuzzy Logic algorithms. These obtained results indicate that the location of user is a significant factor that contributes effectively in optimizing handover control parameters in future mobile networks. Thus, considering the distance as a direct or not direct factor in designing handover Optimization algorithms will contribute effectively in estimating the suitable handover control parameters in mobile networks.