Handover Algorithm Research Articles

5G Smart Mobility Management Based Fuzzy Logic Controller Unit

In the paper, we propose a fuzzy logic controller system to be implemented for smart mobility management in the 5G wireless communication network. Mobility management is considered as a main issue for all-IP mobile networks future generation. As a network-based mobility management protocol, Internet Engineering Task Force developed the Proxy Mobile IPv6 (PMIPv6) in order to support the mobility of IP devices, and many other results were presented to reduce latency handover and the amount of PMIPv6 signaling, but it is not enough for the application needs in real-time. The present paper describes an approach based on the IEEE 802.21 Media Independent Handover (MIH) standard and PMIPv6, so we present a new vertical handover algorithm for anticipating handover process efficiently. Our object is to propose a smart mobility management that contribute in 5G wireless communication system network operating functions. Two proposed dynamic thresholds were successfully made to guaranty process triggering, and a new primitive MIH is proposed for signaling a needed handover to be done. Simulation results demonstrate a significant reduction of the handover delay, packet loss, handover blocking probability and signaling overhead. Simulation results and tests are accomplished.

ZEUS: Handover algorithm for 5G to achieve zero handover failure

In 5G, the required target for interruption time during a handover (HO) is 0 ms. However, when a handover failure (HOF) occurs, the interruption time increases significantly to more than hundreds of milliseconds. Therefore, to fulfill the requirement in as many scenarios as possible, we need to minimize HOF rate as close to zero as possible. 3GPP has recently introduced conditional HO (CHO) to improve mobility robustness. In this study, we propose “ZEro handover failure with Unforced and automatic time-to-execute Scaling” (ZEUS) algorithm to optimize HO parameters easily in the CHO. Analysis and simulation results demonstrate that ZEUS can achieve a zero HOF rate without increasing the ping-pong rate. These two metrics are typically used to assess an HO algorithm because there is a tradeoff between them. With the introduction of the CHO, which solves the tradeoff, only these two metrics are insufficient anymore. Therefore, to evaluate the optimality of an HO algorithm, we define a new integrated HO performance metric, mobility-aware average effective spectral efficiency (MASE). The simulation results show that ZEUS provides higher MASE than LTE and other CHO variants.

An efficient multicriteria‐based vertical handover decision‐making algorithm for heterogeneous networks

AbstractHeterogeneous networks are designed to offload or route some of data traffics of mobile networks through other co‐located wireless access networks. This technique apparently increases the capacity of mobile network. In such networks, a vertical handover process plays an important role in providing seamless and uninterrupted connectivity as well as the required level of quality‐of‐service along with a wide coverage for all mobile nodes. Traditional vertical handover algorithms that are based on single criterion (eg, received signal strength) are not performing well in terms of excess handover rates, ping‐pong effects, handover delays, handover cost, etc. This research presents an efficient multicriteria‐based vertical handover decision‐making algorithm for heterogeneous networks. This algorithm uses a two‐step execution procedure, the first step evaluates whether the handover is needed or not before initiating a handover process, if needed, then a set of feasible solutions are generated for the vertical handover problem formulated as a multi‐objective optimization problem with two objective functions such asquality factor of networksandhandover processing cost. In the second step, an optimal solution (ie, an appropriate access network) for handover is obtained using a hybrid approach of fuzzy analytic hierarchy process (FAHP) and technique for order preference by similarity to ideal solution (TOPSIS). Our simulation study shows that the proposed algorithm performs well as compared to some other existing algorithms (ie, single‐criterion based, multicriteria with AHP, multicriteria with TOPSIS, and multicriteria with both AHP and TOPSIS) in terms of performance metrics such as handover rate, delay, cost, and energy consumption.

Research on handover strategy of heterogeneous networks based on user service quality

SummaryIn view of the handover problem of visible light communication (VLC) and WiFi, most of existing works focus on optimization of vertical handover algorithm of heterogeneous network. However, cooperative handover strategy of horizontal handover (HHO) and vertical handover (VHO) was rarely studied. In the situation, this paper proposes a cooperative horizontal VHO (CHVHO) strategy for heterogeneous network based on quality of experience (QoE). This strategy mainly coordinates the HHO and VHO of the network from the aspects of building servers and the simplification of indoor movement model, which improves the QoE allocated to users. Simulation results demonstrate that, compared with traditional immediate VHO (IVHO) and dwell VHO (DVHO), this strategy can be adaptive to user movement and get higher average QoE.

Reinforcement learning-based joint self-optimisation method for the fuzzy logic handover algorithm in 5G HetNets

5G heterogeneous networks (HetNets) can provide higher network coverage and system capacity to the user by deploying massive small base stations (BSs) within the 4G macrosystem. However, the large-scale deployment of small BSs significantly increases the complexity and workload of network maintenance and optimisation. The current handover (HO) triggering mechanism A3 event was designed only for mobility management in the macrosystem. Directly implementing A3 in 5G-HetNets may degrade the user mobility robustness. Motivated by the concept of self-organisation networks (SON), this study developed a self-optimisation triggering mechanism to enable automated network maintenance and enhance user mobility robustness in 5G-HetNets. The proposed method integrates the advantages of subtractive clustering and Q-learning frameworks into the conventional fuzzy logic-based HO algorithm (FLHA). Subtractive clustering is first adopted to generate a membership function (MF) for the FLHA to enable FLHA with the self-configuration feature. Subsequently, Q-learning is utilised to learn the optimal HO policy from the environment as fuzzy rules that empower the FLHA with a self-optimisation function. The FLHA with SON functionality also overcomes the limitations of the conventional FLHA that must rely heavily on professional experience to design. The simulation results show that the proposed self-optimisation FLHA can effectively generate MF and fuzzy rules for the FLHA. The proposed approach can minimise the HO, ping-pong HO, and HO failure ratios while improving network throughput and latency by comparing with conventional triggering mechanisms.

Research and Simulation of Handover Algorithm in Mobile Communication System

In order to improve the handover rate and quickly handover the target cell, the handover control algorithm of the mobile communication system is explored, and the handover algorithm that combines signal strength and signal quality is researched. At the same time, it is experimentally demonstrated, and the handover user and the new user will be connected. The influence of the entry control threshold setting on the system was compared.

A centralized architecture for autonomic quality of experience oriented handover in dense networks

This paper presents an Optimised Handover (HO) Algorithm for Dense Wireless Local Area Networks (WLANs) based on a novel architecture of Software Defined Wireless Network (SDWN). The work has been designed to be effective in large network environments with a high density of Access Points (APs) and stations, which increase the chances of the Ping-Pong HO effect. Specifically, it considers Quality of Experience (QoE) by applying an optimised HO algorithm for WLANs, which relies on Fuzzy Logic Control Theory (FLCT) combined with Adaptive Hysteresis Values (AHVs). SDWN allows to monitor and manage the networks and to autonomously programme the APs through a centralized controller. The paper includes also a detailed performance analysis of the algorithm developed in an SDWN-based simulator implemented through OPNET. Specifically, our algorithm achieved promising performance results compared to the state of the art in terms of QoE, throughput, delay and reduction of the ping-pong HO effect.

A Pre-authorization Algorithm for WiMAX Network to Reduce Handover Signaling

IEEE 802.16e is a platform capable of meeting those standards in modern wireless networks that demand broad bandwidth and high-speed mobility. One of the most significant problems with IEEE 802.16e is that although the handover technology provides smooth high volume data services at a high speed scale, it only specifies a mechanism without including precise methods or algorithms for handover that can be delegated. Another issue is handover signaling during the re-entry process when a mobile station requests access to the next possible base station. This paper proposes PAA (Pre-Authorization Algorithm) which accepts incoming requests quickly because it already has the incoming request’s information saved. PAA reduces call dropping for high speed users at the edge of cell and mitigates the ping-pong effect. Finally MATLAB was used to present the results that shows reducing in signaling time.

Research on Handover Algorithm Based on Dynamic Beamforming in HSR Cutting Scene

High-speed train passes through the cutting terrain, signal propagation is significantly affected by the steep sides, resulting in a high probability of handover interruption. To solve this problem, this paper proposes a location-assisted dynamic beamforming handoff algorithm. This solution uses the vehicle-mounted GPS and the arrival angle of the incoming wave to determine the location of the Mobile Relay Node (MRN) and ensure the stability of signal transmission during the operation of the train in the overlapping area. According to the path loss of the High-speed Railway (HSR) cutting scene, calculate the Handover Interruption Probability (HIP), the Handover Trigger Probability (HTP) and the Handover Success Probability (HSP). The simulation results have showed that the proposed algorithm has lower HIP and higher HSP, compared with the traditional handover solution. It ensures the stability of handover in complex scenes, and has better performance in improving the handover efficiency of HSR communication systems.

Adaptive Vertical Handover Algorithm based on Fuzzy Hierarchy-entropy Weight Method

Adaptive Vertical Handover Algorithm based on Fuzzy Hierarchy-entropy Weight Method

Fast Handover Algorithm Based on Location and Weight in 5G-R Wireless Communications for High-Speed Railways.

With the booming development of high-speed railways (HSRs), key technologies of wireless communications need to be constantly innovated. In particular, the frontier issue of low delay of the handover for the fifth generation (5G) in fast-moving scenarios has attracted attention from both industry and academia. Based on an analysis of a large number of measured data and the location of the user equipment (UE), a fast handover algorithm is proposed to solve the problem of long delay for a train moving at high speed in a 5G-railway (5G-R). By calculating the speed of a train and its direction of movement, a reasonable handover mode is selected and the handover chain of neighboring cells is identified. The location of the train can be calculated to determine whether UE enters the defined identification zone of pre-handover. Depending on the values collected in the measurement report, the command of the handover is triggered when the weight of the target cell is greater than that of the source cell. Our experimental results show that the delay of the fast handover algorithm is reduced by 2.03%, and the success rate of the handover is increased by 0.42%. Research directions for smart railways are discussed based on these findings.

Vertical handover in heterogeneous networks using WDWWO algorithm with NN

ABSTRACT In heterogeneous networks, Vertical Handover (VH) plays a vital consequence of customer mobility as they have a high impact on networking performance like delay, throughput and call block probability. Even in the presence of various existing works, VH management exhibit certain drawbacks like method complexity, difficult network modelling and inaccurate handover. Thus, a hybrid methodology is proposed in this work which can provide accurate VH and considerable reduction in working complexity. Here, a combination of Deep Residual Neural (DRN) and Wind-Driven Water Wave Optimisation (WDWWO) is introduced to perform VH. Accurate prediction of Received Signal Strength (RSS) is a difficult task for mobile users while moving from one network to another. In order to tackle this situation, DRN is used with WDWWO based weight optimisation, hence the name Optimised DRN (ODRN). Almost every networking parameters like bandwidth, delay, throughput, velocity, BER, SNR, energy consumption, monetary cost and data traffic are included in ODRN modelling. The proposed work is implemented in NS2 platform and resultant performances like energy consumption, RSS, throughput, packet delivery ratio, packet loss, handover failure rate, algorithm convergence and latency are compared with conventional methods of D-TOPSIS, FIS-ENN and F-AHP.

RETRACTED ARTICLE: Self organizing distributed mobility management for next generation mobility protocol

Fast handoff convention for fundamental administration of mobile IPv6 situations has for quite some time been an examination territory in logical world. It has been key issue in deployment of distributed mobility management protocol in network. The instrument for computing execution measurements for delay, throughput, and packet loss intensify the assessing connected convention. The stage under the simulative field in accomplice based hierarchical MIPv6 (PHMIPv6) focus to progress in the speed upgrade of handover the executives activities by handing-off some motioning on chosen accomplice nodes before really changing to new access point. The paper introduces new technique called Son, DMM pmipv6, which depends on self-managed protocol dmmpmipv6. Self-organization network system is arranging and respected by a predefined deep learning neural handover algorithm dependent on the mobility management method, to prepare itself to the sorted out association network is utilized for SON rely upon the prepared feed-forward Network. This paper has the concerned over the discovering Traceability of network through the proposed Son and DMM pmipv6.

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

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 real-time 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.

Location Aware Vertical Handover in a VLC/WLAN Hybrid Network

Visible light communication (VLC) has emerged as a promising technology for wireless communication as it offers higher data rates and secure data transmission along with providing indoor illumination. However, VLC is restricted by the line of sight (LoS) nature of the optical channel that consequently results in light path blockages. Therefore, an effective solution would be to combine VLC with a radio frequency (RF) system to form a hybrid VLC/RF network that would take into account the preferences of an end-user with the practicality of implementation. In such networks, an efficient vertical handover (VHO) technique is the most critical element as it ensures a seamless transition between the two networks. In this work, we propose a vertical handover technique that utilizes the user’s location information to make a handover decision. We found that the frequency of light path blockages increases with the increasing number of users in a confined space, resulting in significant performance deterioration. This additional information is then utilized so that the VHO algorithm effectively selects the most feasible network. The proposed algorithm has been tested against the immediate vertical handover algorithm (I-VHO) and the dwell vertical handover algorithm (D-VHO) with two different dwell times. The average number of handovers, quality of experience (QoE), and packet loss have been set as performance metrics. We show from several simulation scenarios that the proposed method results in a fewer number of handovers while maintaining higher QoE and lower packet loss.

Adaptive Handover Algorithm for LTE-R System in High-Speed Railway Scenario

With the rapid development of high-speed railway, the LTE-R communication system has more requirements for the handover success rate. An adaptive handover algorithm based on random suppression in high-speed railway scenario is proposed. The algorithm establishes an elliptic function relationship between the hysteresis threshold and the train speed, so that the hysteresis threshold can be adjusted adaptively with the train speed, which lessens the challenge of high-speed train forward handover. At the same time, the normal distribution random number is introduced to suppress the reverse handover in order to reduce the ping-pong handover rate. Finally, the effectiveness of the algorithm is verified in different scenarios. Simulation results show that compared with the traditional A3 algorithm, the proposed adaptive handover algorithm based on random suppression can improve the handover trigger probability and handover success probability and avoid the increase of ping-pong handover rate.

Location-Based Vertical Handovers in Wi-Fi Networks With IEEE 802.11ah

IEEE 802.11ah is a new sub-GHz Wi-Fi technology that provides several advantages over traditional Wi-Fi such as a higher communication range, enhanced scalability, and lower energy consumption, however at the cost of substantially lower throughput. With the aim of simultaneously benefiting from multiple Wi-Fi technologies, recent proposals suggest combining a number of these technologies into a single device. This, however, compromises the energy efficiency of the device, as it implies concurrent utilization of different radio access interfaces. To mitigate this issue, the device should utilize the interface of a certain technology only when there is a high probability of establishing communication over that technology. Traditional vertical handover algorithms are not designed for this purpose as they rely on continuous beacon listening or active probing, even if the device is not in the range of a given technology. To address this issue, vertical handover algorithms based on the combination of devices’ physical locations and either Radio Environmental Maps (REM) or propagation modeling have been proposed. Moreover, their suitability and encouraging performance have been demonstrated for a number of the established Low-Power Wide-Area Network (LPWAN) technologies. However, their appropriateness for Wi-Fi-based networks with IEEE 802.11ah is currently unknown, which provides the main motivation for this work. Specifically, we carry out an extensive experimental performance evaluation of two location-based vertical handover algorithms in the context of Wi-Fi-based networks with IEEE 802.11ah. Our results demonstrate the feasibility of location-based handovers in this context. We base our findings on the fact that location-based algorithms can maintain comparable data communication quality as the beacon listening-based baseline, while simultaneously reducing the utilization of the IEEE 802.11ah and IEEE 802.11n radio access interfaces by a factor of 2 and 10, respectively.

Q-Learning vertical handover scheme in two-tier LTE-A networks

Global mobile communication necessitates improved capacity and proper quality assurance for services. To achieve these requirements, small cells have been deployed intensively by long term evolution (LTE) networks operators beside conventional base station structure to provide customers with better service and capacity coverage. Accomplishment of seamless handover between Macrocell layer (first tier) and Femtocell layer (second tier) is one of the key challenges to attain the QoS requirements. Handover related information gathering becomes very hard in high dense femtocell networks, effective handover decision techniques are important to minimize unnecessary handovers occurred and avoid Ping-Pong effect. In this work, we proposed and implemented an efficient handover decision procedure based on users’ profiles using Q-learning technique in an LTE-A macrocell-femtocell networks. New multi-criterion handover decision parameters are proposed in typical/dense femtocells in microcells environment to estimate the target cell for handover. The proposed handover algorithms are validated using the LTE-Sim simulator under an urban environment. The simulation results showed noteworthy reduction in the average number of handovers.

A Multi-criteria based handover algorithm for vehicle-to-infrastructure communications

Maintaining seamless quality of service (QoS) requirements for ongoing delay sensitive applications during handover processes for Vehicle-to-Infrastructure (V2I) communication over heterogeneous networks is a challenging task. The situation becomes even more challenging to deal with for multi-tier heterogeneous networks with various network sizes. To overcome the above challenges, we propose a multicriteria-based handover algorithm for V2I communications (V2I-MHA) to be used in multi-tier heterogeneous network environments. V2I-MHA selects the most appropriate underlying target network for handover based on QoS profiles of the ongoing applications and services. Moreover, our proposed algorithm filters out the inappropriate candidate networks using a multi-criteria decision-making technique based on Simple Additive Weighting (SAW) approach. However, our approach ensures that the most appropriate candidate network for handover processes is selected not only based on QoS requirements of the ongoing applications, but also on the knowledge of candidate network parameters (e.g. bandwidth, packet latency, packet losses, and service pricing). A multi-mode vehicle On-Board Unit (OBU) containing Long Term Evolution-Advanced (LTE-A) and Wi-Fi network interface cards is developed in the Riverbed (previously OPNET) simulator for system performance evaluation. The simulation results show that the proposed V2I-MHA outperforms (in terms of handover failure rate and packet losses) the existing handover methods.

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

A novel vertical handover algorithm based on multi-attribute and neural network for heterogeneous integrated network is proposed in this paper. The whole frame of the algorithm is constructed by setting the network environment in which we use the network resources by switching between UMTS, GPRS, WLAN, 4G, and 5G. Each network build their own three-layer BP (Back Propagation, BP) neural network model and then the maximum transmission rate, minimum delay, SINR (signal to interference and noise ratio, SINR), bit error rate, user moving speed, and packet loss rate which can affect the overall performance of the wireless network are employed as reference objects to participate in the setting of BP neural network input layer neurons and the training and learning process of subsequent neural network data. Finally, the network download rate is adopted as prediction target to evaluate performance on the five wireless networks and then the vertical handover algorithm will select the right wireless network to perform vertical handover decision. The simulation results on MATLAB platform show that the vertical handover algorithm designed in this paper has a handover success rate up to 90% and realizes efficient handover and seamless connectivity between multi-heterogeneous networks.