Enhanced Bandwidth Based Handover Decision Making Algorithm For Small Cell Wireless Networks

The evolution of 5G small cell networks has led to the advancement of vertical handover decision-making algorithms. A mobile terminal (MT) tends to move from one place to another and, as the 5G network coverage is small, user network access will change frequently and lead to a high probability of unnecessary handover, which is a waste of network resources and causes degradation of service quality. This paper aims to reduce the number of unnecessary handovers in 5G heterogeneous networks by proposing a handover decision-making algorithm that integrates the dwelling time prediction technique and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The proposed algorithm reduces the number of unnecessary handovers by estimating the connection time to a small cell network using the dwell time prediction technique. The TOPSIS evaluates the network quality and chooses the best network based on user preference. The result shows that the proposed handover algorithm reduces the number of unnecessary handovers to small cell networks in high-speed scenarios. It also saves the network connection cost by up to 27.51% compared with the TOPSIS-based handover algorithm. As for throughput achievement, the proposed algorithm yields an improvement of 5.12%. The proposed algorithm significantly reduces the number of unnecessary handovers in the high-speed scenario while fulfilling user preferences.

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“…The network with the lowest cost will be selected as the handover target. The cost function is given by Equation (1).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Achieving a seamless handover is a challenging issue. The evolution of next-generation networks is expected to consider handover management as its main aspect [1].…”

Section: Introductionmentioning

confidence: 99%

Handover Decision-Making Algorithm for 5G Heterogeneous Networks

et al. 2023

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“…In order to alleviate the ping-pong effect, in [ 12 ], the “time prediction for staying method” was used, and whether the target handover AP could provide users with sufficient throughput was used as a handover decision indicator to reduce the overall number of handovers and improve network service efficiency. In [ 13 ], the author decided whether an AP could be selected as the target handover AP by checking whether the UE was facing it.…”

Section: Related Workmentioning

confidence: 99%

User QoS-Based Optimized Handover Algorithm for Wireless Networks

Chu

Wong

Cheng

et al. 2023

Sensors

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Due to the development of wireless network technology, various applications relying on good network quality are widely used on mobile devices. Taking the commonly used video streaming service as an example, a network with high throughput and low packet loss rate can meet the service requirements. When the moving distance of the mobile device is greater than the signal coverage of the AP, it will trigger the handover process to connect to another AP, and cause the network to disconnect and reconnect instantaneously. However, frequently triggering the handover procedure will cause a significant drop in network performance and affect the operation of application services. In order to solve this problem, this paper proposes the OHA and OHAQR. The OHA considers whether the signal quality is good or bad, and uses the corresponding HM method to solve the problem of frequent handover procedures. The OHAQR integrates the QoS requirements of the throughput and packet loss rate into the OHA with the Q-handover score, to provide high-performance handover services with QoS. Our experimental results show that the OHA and OHAQR have 13 and 15 handovers in a high-density scenario, respectively, and are better than the other two methods. The actual throughput and packet loss rate of the OHAQR are 123 Mbps and 5%, respectively, and the network performance is better than that of other methods. The proposed method shows excellent performance in ensuring the network QoS requirements and reducing the number of handover procedures.

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“…However, the handover delay is high because two RSS points within WLAN coverage are needed for the travelling time estimation process. Author in [9] proposed a handover algorithm that combines the travelling distance prediction technique with the bandwidth based handover algorithm. The bandwidth based handover algorithm is less complicated compared to the multi-criteria and intelligence-based handover schemes.…”

Section: Related Workmentioning

confidence: 99%

“…where , , denotes the lower bound value, mid-value and upper bound of the triangular fuzzy number based on Satty's AHP scale table as shown in Table I. Absolutely important (7,9,9) (1/9,1/9,1/7)…”

Section: B Fuzzy-analytic Hierarchy Processmentioning

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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Enhanced Bandwidth Based Handover Decision Making Algorithm For Small Cell Wireless Networks

Cited by 4 publications

References 11 publications

Handover Decision-Making Algorithm for 5G Heterogeneous Networks

Handover Decision-Making Algorithm for 5G Heterogeneous Networks

User QoS-Based Optimized Handover Algorithm for Wireless Networks

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

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