Vertical handover algorithm based on multi-attribute and neural network in heterogeneous integrated network

Tan, Xianjun; Chen, Geng; Sun, Hongyu

doi:10.1186/s13638-020-01822-1

Cited by 35 publications

(24 citation statements)

References 22 publications

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“…Tan et al [23] proposed a Multi-Attribute and Neural Network Handover Algorithm for heterogeneous networks with UMTS, GPRS, WLAN, 4G and 5G. Every network has neural network models of its three-layer Back Propagation (BP).…”

Section: Figure 18 Genetic Algorithm Processmentioning

confidence: 99%

Vertical Handover Decision Making Algorithms for 5G Heterogeneous Networks: A Review

Goh¹,

Yew²,

Wen³

et al. 2022

IJETAE

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The wireless networks have been rapidly used in our daily lives, especially mobile wireless networks. An environment consisting of several networks such as WLAN, 4G-LTE, and 5G, is known as a heterogeneous network. Wireless networks are widely used to support various data services such as live video streaming, upload data, download data and cloud service depending upon their capacity and nature. When the mobile terminal is moving, the network availability will be changed. Therefore, the mobile terminal must perform handover from one network to another network in heterogeneous networks to maintain the call and quality of service (QoS). This process is known as Vertical Handover (VHO). A seamless handover is important to provide uninterrupted high quality service while performing the handover. To achieve this, various vertical handover decision making algorithms have been proposed and studied using advanced tools and proven concepts. This paper gives an overview of current research on handover decision making in fifth generation (5G) heterogeneous wireless networks. Keywords—Vertical Handover Decision Making, Heterogeneous Networks, Quality of Service, 5G, Seamless Handover

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Section: Figure 18 Genetic Algorithm Processmentioning

confidence: 99%

Vertical Handover Decision Making Algorithms for 5G Heterogeneous Networks: A Review

Goh¹,

Yew²,

Wen³

et al. 2022

IJETAE

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“…The limitation of the FAHP-TOPSIS algorithm is that it will induce a high number of unnecessary handovers at the high-speed scenario. Furthermore, authors in [16] presented a neural network based MADM handover algorithm. Authors in [17] presented a Genetic algorithm (GA) based MADM handover algorithm.…”

Section: Related Workmentioning

confidence: 99%

Vertical Handover Algorithm for Telemedicine Application in 5G Heterogeneous Wireless Networks

Diong¹,

Goh²,

Chung³

et al. 2021

IJACSA

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In this fast-paced technology era, the advancement of telecommunication systems has made many advanced technologies possible. With the help of the 5G technology, more technologies will become a reality and telemedicine is one of them. Numerous studies have shown that the fatal rate of ischemic heart disease cases can be reduced by sending the realtime patient health data from an ambulance to the medical centre so that healthcare professionals can make early preparation and give immediate treatment in the golden hour. 5G technology offers a high data rate and low latency. However, the coverage of 5G is small compared to 4G. It will induce a high number of unnecessary handovers when an ambulance traverses the 5G networks at high speed and lead to degradation of services quality. Therefore, a fast and accurate vertical handover decision-making algorithm is needed to minimize unnecessary handover in high-speed scenarios. This paper proposes a handover algorithm that integrates the Travelling Time Estimation, Fuzzy Analytic Hierarchy Process (FAHP) and Technique for order of preference by similarity to ideal solution (TOPSIS) algorithms to reduce unnecessary handover in 5G heterogeneous networks. The simulation results show that the proposed algorithm has successfully reduced up to 80.3% of handovers compared to FAHP-TOPSIS based handover algorithm in the high-speed scenario. The proposed handover algorithm can improve the quality of telemedicine services in high-speed scenarios.

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“…In [18], details are provided for the readers as a new innovation in Smart cities Applications. In [19], a novel handover algorithm using multi-attribute and neutral network for heterogeneous integrated network is presented. The algorithm was designed by using interchanged network resources among 4G, 5G, wireless local area network etc.…”

Section: Related Workmentioning

confidence: 99%

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2021

IJWMN

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Recently, many generations of mobile networks have changed from one transition to another transition. The mode of transition from the first generation (1G) to the fifth generation (5G) is characterized by a lot of performance challenges such as delay, speed of the users, mobility, and variety of services. Currently, different from prior generations, 5G is not only concerned with the mobile networks but also, with various applications and different services such as health sector, transportation, energy consumption, safety well as Smart City. All these services are incorporated by 5G. In this paper, we proposed a call admission control (CAC) algorithm with an efficient handoff for both 4G and 5G networks. Simulation is used to evaluate the effectiveness of the proposed algorithm, and the obtained results indicate it considerably performs better than do other algorithms based on valuable metrics such as data throughput, call blocking probability (CBP), and call dropping probability (CDP).

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Vertical handover algorithm based on multi-attribute and neural network in heterogeneous integrated network

Cited by 35 publications

References 22 publications

Vertical Handover Decision Making Algorithms for 5G Heterogeneous Networks: A Review

Vertical Handover Decision Making Algorithms for 5G Heterogeneous Networks: A Review

Vertical Handover Algorithm for Telemedicine Application in 5G Heterogeneous Wireless Networks

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