Handover Scheme for 5G Communications on High Speed Trains

Banna, Rasha El; ElAttar, Hussein M.; Aboul-Dahab, Mohamed A.

doi:10.1109/fmec49853.2020.9144880

Cited by 11 publications

(5 citation statements)

References 18 publications

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“…Handover (HO) or handoff is defined as the process of transferring a connection from a current serving BS to another in the network [60], which is a critical process to address in wireless cellular networks due to the mobility of the UE [61]. Figure 5 presents the principal symbols used to prove the HO laws used in this section.…”

Section: Number Of Handoversmentioning

confidence: 99%

An Adaptive Cell Selection Scheme for 5G Heterogeneous Ultra-Dense Networks

Alablani

Arafah

2021

IEEE Access

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Fifth-generation (5G) cellular networks are a promising technology to meet the rapid growth in wireless traffic. Small cells are critical in fulfilling the requirements of 5G networks. A heterogeneous ultra-dense network (HUDN) is an enabling technology consisting of several types of small cells to enhance the performance of 5G networks effectively. A critical issue of HUDN is the cell selection method because the traditional technique for cell selection is inapplicable in such a network. This study proposes a novel adaptive cell selection (ADA-CS) scheme. It adapts to various characteristics of HUDNs and vehicle movements. It performs six phases to select the best base station with which to be associated. Simulation results show that, with low-and medium-speed vehicles, the ADA-CS scheme outperforms the traditional protocol in terms of the average number of handovers by 42.39%. In addition, it is superior to some relevant recent schemes by up to 36.53%. The adaptation feature of the proposed protocol provides additional improvements regarding the average number of handovers with high-speed vehicles. Therefore, it achieves superiority in terms of the average number of handover failures and unnecessary handovers. In addition, the ADA-CS scheme enhances the average achievable downlink data rates and spectral efficiency per vehicle by 3.98% and 2.79% compared with the traditional and the relevant recent schemes.

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Section: Number Of Handoversmentioning

confidence: 99%

An Adaptive Cell Selection Scheme for 5G Heterogeneous Ultra-Dense Networks

Alablani

Arafah

2021

IEEE Access

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“…Therefore, Wireless communication is extensively integrated into smart rail transit systems, allowing seamless interaction between rail vehicles, signal systems, dispatching centers, and passenger terminals to enable functions like realtime monitoring, navigation, and information dissemination, ensuring precise control and efficient service delivery. Additionally, high-speed wireless communication supports advanced functionalities, such as high-definition video monitoring, real-time location tracking, and intelligent scheduling commands, improving system safety and efficiency [7,8,1].…”

Section: Introductionmentioning

confidence: 99%

Periodic Prediction Based Integrated Solutions for Wireless Communication and Edge Computing in Smart Railway Systems

Ren,

Song,

Long

et al. 2024

Preprint

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This paper addresses the challenges of wireless communication and intelligence in smart railway system under high-speed mobile environments, particularly the issues of Doppler effect and dynamic variability. Solutions that integrate wireless communication and edge computing is proposed. The system model based on the operational characteristics of high-speed trains is established. By analyzing historical data and employing statistical methods, the probability distribution of high-speed train operation times is studied, revealing the operational patterns across different intervals. On this foundation, an intelligent task allocation model is proposed, which optimizes the deployment of edge servers and task allocation strategies to minimize task processing costs while ensuring the stability of communication links. To address the Doppler effect and selective channel enhancement issues in high-speed mobile environments, channel prediction with periodic information is used to reduce interference and ensure the reliability of data transmission. Furthermore, intelligent scheduling system based on edge computing with predictive models is established, supporting advanced scheduling and optimizes train timetables. The algorithm is based on established scheduling rules, effectively managing the high-speed railway system and improving system efficiency. Compared with existing scheduling algorithms, the proposed method demonstrates significant advantages in reducing signal distortion, enhancing signal reliability, and optimizing resource utilization and costs.

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“…Various techniques have been proposed to address these impairments but they still encounter some drawbacks in terms of throughput degradation [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. This project mainly focused on the development of a network selection framework for vehicle communication networks.…”

Section: Introductionmentioning

confidence: 99%

Handover Network Selection for Vehicle in LTE-A Communication Networks

Yusof

Jaafar

Ya’acob

et al. 2023

ARASET

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One of the challenges to achieving smooth communications in heterogeneous networks is to find the right balance between various handover parameters for network selection. The Receive Signal Strength (RSS) from a network's Point of Attachment (PoA) is the primary factor used in traditional approaches to network selection. Therefore, network selection is vital for a successful handover in the vehicle communications network. However, vehicles moving through such diverse networks faced difficulties like frequent unwanted handovers, selecting the wrong candidate networks for handovers, and taking too long to finish the drawn-out handover procedure, which results in failed handovers. All of these factors will impair the efficiency of the handover process, which will affect the smooth operation of the vehicles. Hence, the main idea of this research is to improve the handover network performance selection performance. The proposed work is for vehicles to self-evaluate a candidate list of Access Points (AP) that are located in the vehicle movement direction and select the best underlying candidate network. In this project, the network selection framework of the vehicle communications network with the distance between the target candidate and the trajectory of the vehicle movement was developed as well as the vehicle mobility information. The important parameters which are the relative direction index, proximity index and residence time index are chosen to identify the best candidate network. Once the target of the base station has been identified, then the optimum value of the distance is calculated using the Particle Swarm Optimization (PSO) technique to initiate the handover process. The performance of the proposed handover network selection is simulated and evaluated using MATLAB software. The results show that the proposed handover network selection method improved the successful handover rate as compared to the conventional method.

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Handover Scheme for 5G Communications on High Speed Trains

Cited by 11 publications

References 18 publications

An Adaptive Cell Selection Scheme for 5G Heterogeneous Ultra-Dense Networks

An Adaptive Cell Selection Scheme for 5G Heterogeneous Ultra-Dense Networks

Periodic Prediction Based Integrated Solutions for Wireless Communication and Edge Computing in Smart Railway Systems

Handover Network Selection for Vehicle in LTE-A Communication Networks

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