## 2 Related Work  
With the advent of high-speed rails and 5G networks, losses resulting from handovers have now become a pressing issue that cannot be ignored. In one study [2], handover loss relating to identity verification processes was observed among a large number of mobile terminals (which support 5G high-speed rail mobile networks) in high-speed rail cars when they were executing handovers. To address this problem, the authors of that study proposed two pre-handover authentication solutions for fixed-rail transportation that utilize software-defined networking controllers. These solutions can reduce, to negligible levels, the delays that occur when handovers are executed within the coverage range of the SBSs at a destination and thus provide uninterrupted Internet service. However, they did not consider practical responses to address the signal loss arising from changes in channel environments. [PERSON] and [PERSON] [3] defined a measurement index for measuring load, the data rate of mobile terminals, and the effects of soft handovers on handover failure rates. In that study, the relative positional relationship between two access points and a mobile terminal during a failed handover attempt was observed, and a mathematical analysis was performed to determine the lower bounds for the failed handover and the probability of unnecessary handovers. Relatedly, [PERSON] et al. [4] proposed two handover procedures for mobile relays in long-term evolution-advanced (LTE-A) high-speed rail networks to ease the message overhead and handover time incurred by the handover procedures in LTE-A specifications. The challenges associated with high-speed travel include a more severe Doppler effect, delayed handover triggering, and frequent handovers, which, in turn, lead to a reduction in the reliability of wireless communication networks. To determine the current position of a train more accurately, a combination of positioning rules may have to be applied. One example of this approach is a study conducted by [PERSON] et al. [5], who proposed a solution that utilizes beamforming and positioning information to improve the system handover performance of LTE systems used in high-speed rails. While their results demonstrated the effectiveness of their solution in raising the success rate of handovers, they had only examined situations in which moving trains enjoyed eNodeBs signal coverage and did not consider situations in which there is no signal coverage. [PERSON] et al. [6] pointed out that RSS is a simple and low-cost method for realizing positioning capabilities in wireless sensor networks (WSNs). They proposed a method that addresses existing RSS measurement problems and improves the reliability of RSS sources, which is achieved by estimating the position of indoor WSN goal nodes and utilizing non-Gaussian probability density functions to realistically simulate RSS bias and obtain more accurate measurements. However, the positioning component of their approach requires multiple nodes, making it less feasible to implement in places with less wireless network coverage. [PERSON] and [PERSON] [7] proposed the averaging of RSS samples (collected from different radio frequency channels) to improve range-finding accuracy. Their analysis results indicated that their method reduces the component of RSS variability by reducing multipath effects and interference. [PERSON] et al. [8] proposed a roadside equipment (RSE) assisted positioning method that incorporates GPS+RSS mixed signal to perform lane-level positioning and claimed that their method is more accurate than GPS while also being less complex as a whole. Their simulation and actual measurement results showed that their method provides better accuracy and can identify the lane on which a target vehicle is driving. In heterogeneous networks, vertical handovers are an important branch of user mobility as they directly affect network performance (e.g., throughput, packet delay, and call blocking probability).