## 1 Introduction  
The massive growth in the number of connected smart devices and applications that require variant quality of service (QoS) and quality of experience (QoE) requirements has resulted in a huge demand for mobile broadband services with high data rates. To cope with this demand, mobile network capacity and performance must be increased. The 5G new radio (NR) network standard offers the utilization of high-band spectrum such as millimeter wave bands, which can increase the network capacity and provide high coverage to users [1]. The 5G NR technology operates in a wide range of frequencies, balancing between coverage and data rates. Sub-6 GHz bands (4.5 GHz to 6 GHz) provide good coverage and better signal propagation, making them suitable for wider areas. However, data rates are moderate in these bands. In contrast, mmWave bands (24.25 GHz to 100 GHz) offer significantly higher data rates due to their large bandwidth [2, 3]. The use of mmWave is one of the most promising and effective solutions for 5G and beyond (B5G) mobile networks. By using mmWave, wireless networks can achieve high data rates, as mmWave signals can carry a much larger amount of data, even with lower-order modulation schemes for reliable transmission, due to the enormous bandwidths that are available in these bands [4]. Looking ahead, 6G research is actively exploring even higher frequencies and novel technologies to further enhance data rates and network capacity. Potential areas of focus include terahertz (THz) bands exceeding 100 GHz and beyond, as well as advancements in areas like intelligent resource management and network slicing for optimized performance [5]. Nevertheless, mmWave presents certain difficulties for mobile communication as well because of its high sensitivity to abrupt channel changes and problems with obstructions from different structures, including trees and buildings. This may result in severe channel interruptions due to the signal distortion, as well as a substantial path loss when the signal intensity dramatically drops with distance [6]. Therefore, heterogeneous networks, or HetNets, which combine multiple radio access technologies, hold the key to the future of the network beyond 5G. In addition to macro cells, HetNets make use of small cells, which are the most widely used mmWave operating solution due to their low cost, low power consumption, and short-range radio-access nodes. Small cells are low-power base stations (such as picocells, femtocells, microcells, and relays) that offer cellular coverage in areas with high user traffic, whereas macro-cells are high-power base stations that cover broader areas. Despite this, and due to the power disparity between cell types, users tend to initiate connections to high-power cells that have the strongest signal than other cells. Using HetNets is one of the most significant ways to meet the demands on mobile networks to increase their capacity and performance. Users can switch between different types of cells based on their needs, which results in improved data rates and coverage [7]. Small cells can be deployed within the coverage areas of macro cells to enhance network performance and capacity in areas with high or imbalanced user demand. However, implementing HetNets presents significant difficulties with interference management, load balancing (LB), and mobility management (MM). One of the main challenges is the handover (HO) process, which is the technique that enables the mobile user equipment (UE) to switch its connection from one cell to another [8]. Several parameters that can control the HO process such as time-to-trigger (TTT), HO margin (HOM), cell frequency offset, and cell individual offset are called HO control parameters (HCPs), which affect both the QoS and the HO performance of the network [9]. As a result, it is critical to research how HCPs affect HO performance and determine the ideal parameters under various circumstances.