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    A Handover Decision Optimization Method Based on Data-Driven MLP in 5G Ultra-Dense Small Cell HetNets
    (Springer, 2025) Riaz, Hamidullah; Ozturk, Sitki; Aldirmaz-Colak, Sultan; Calhan, Ali
    Deploying Ultra-Dense Small Cells (UDSCs) in Heterogeneous Networks (HetNets) introduces advantages such as increased capacity and expanded coverage over conventional HetNets. However, these advantages come at the expense of some challenges during the Handover (HO) process. Radio Link Failure (RLF) and Unnecessary Handover (UHO) are severe among these challenges. To address these issues, accurate setting and optimization of Handover Control Parameters (HCPs), including Handover Margin (HOM) and Time-To-Trigger (TTT), are necessary. Inaccurate adjustment and optimization of HCPs in live networks may lead to underperformance. Thus, this paper proposes a method that optimizes the obtained dataset by developing an algorithm that adjusts HOM and TTT based on related metrics such as RLF and UHO. The optimized dataset is then applied to a Multi-Layer Perception (MLP) model within a developed HO decision algorithm to predict both HOM and TTT, considering user speed, Reference Signal Received Power (RSRP), Signal to Interference plus Noise Ratio (SINR), and cell load. Simulation results showed that the proposed method outperforms the well-known A3 method in terms of Handover Rate (HOR), Handover Failure (HOF), Handover Ping-Pong (HOPP) and RLF by approximately 90.9%, 76.6%, 79.8% and 75%, respectively.
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    A Robust Handover Optimization Based on Velocity-Aware Fuzzy Logic in 5G Ultra-Dense Small Cell HetNets
    (Mdpi, 2024) Riaz, Hamidullah; Ozturk, Sitki; Calhan, Ali
    In 5G networks and beyond, managing handovers (HOs) becomes complex because of frequent user transitions through small coverage areas. The abundance of small cells (SCs) also complicates HO decisions, potentially leading to inefficient resource utilization. To optimize this process, we propose an intelligent algorithm based on a method that utilizes a fuzzy logic controller (FLC), leveraging prior expertise to dynamically adjust the time-to-trigger (TTT), and handover margin (HOM) in a 5G ultra-dense SC heterogeneous network (HetNet). FLC refines TTT based on the user's velocity to improve the response to movement. Simultaneously, it adapts HOM by considering inputs such as the reference signal received power (RSRP), user equipment (UE) speed, and cell load. The proposed approach enhances HO decisions, thereby improving the overall system performance. Evaluation using metrics such as handover rate (HOR), handover failure (HOF), radio link failure (RLF), and handover ping-pong (HOPP) demonstrate the superiority of the proposed algorithm over existing approaches.