Optimal selection of target radio access points in ultra-dense mobile heterogeneous networks

Abstract

The deployment of 5G technology all over the world in recent years has led to the formation of very dense heterogeneous networks together with the already installed old-generation base stations. This thesis focuses on the problem of mobility management and handover decision-making in ultra-dense heterogeneous networks (UDHNs), particularly within the context of 4G and 5G Radio Access Technologies (RATs). As mobile users move across overlapping cells with varying coverage and capacity, ensuring seamless connectivity becomes increasingly challenging. This study specifically addresses handover decision algorithms, which are essential to maintain service continuity and network quality. The main objective of this work is to develop and evaluate a handover decision-making algorithm based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Unlike conventional methods that rely on fixed criteria weights, the proposed algorithm dynamically adjusts these weights depending on the velocity of the user equipment (UE). The decision criteria include Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Signal-to-Interference-plus-Noise Ratio (SINR), base station load, and distance between UE and candidate base stations. A simulation environment was constructed to test and compare the performance of three algorithms: Conditional Handover (CHO), standard TOPSIS, and the proposed Dynamic TOPSIS. The simulations were conducted using realistic mobility scenarios across various UE speeds (5 to 50 m/s). Key performance indicators such as the handover probability (HOP), handover ping-pong probability (HPPP), handover failure rate (HOF), and average serving RSRP were analyzed. The findings indicate that the suggested Dynamic TOPSIS algorithm surpasses the other two methodologies. At elevated mobility (50 m/s), the ping-pong probability diminished to 0.8%, in contrast to 6.6% with CHO and 15.3% with conventional TOPSIS. Furthermore, the mean signal strength during handovers was enhanced, signifying increased network stability and user experience. In conclusion, the study illustrates that integrating user speed into the handover decision-making process enhances mobility management efficiency and intelligence. The suggested strategy provides a low-complexity and pragmatic solution for enhancing handover performance in congested 4G and 5G networks.