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One of the most crucial issues in mobile networks is ensuring reliable and stable connectivity during mobility. In recent years, numerous research has examined Fourth Generation (4G) and Fifth Generation (5G) mobile networks to address issues related to handover (HO) self-optimisation. Different approaches have been developed to identify the best Handover Control Parameters (HCPs) settings, including Time-To-Trigger (TTT) and Handover Margin (HOM), since managing HCP values is a key factor in determining the efficiency and accuracy of handover decisions. The purpose of this work is to address the challenges associated with HO management in Sixth Generation (6G) mobile networks, where a massive number of diverse devices, high mobility, and varying network conditions (e.g., Ultra Dense Network (UDN), Heterogeneous Network (HetNet) and Millimetre Waves (mmWaves)) are established. This, in turn, presents complex HO issues which require solutions that can adapt to different deployment settings. To provide a brief background of mobility management, the paper presents the basic HO concept, HO history, and HO procedure. Additionally, a comparison of HO in 4G to 6G is discussed to gain a better understanding of technology development and its effect on HO solutions. Furthermore, the basics of Mobility Robustness Optimisation (MRO) is explained, which involve HCP values. Previous MRO approaches have made significant advancements; however, they often lack adaptability and robustness to dynamic network conditions. By leveraging Artificial Intelligence (AI) algorithms with MRO techniques, this approach offers an improved solution to optimize handover decisions in a self-optimizing manner, thereby enhancing the overall network performance. To achieve this goal, it is necessary to analyze previous MRO and AI-integrated solutions and make comparisons between them. Additionally, the advantages and disadvantages of these solutions are considered. The contribution of this work lies in identifying the directions for HO self-optimization in 6G deployment. It demonstrates that deploying an AI-based solution would benefit future MRO deployments. This survey will aid in the analysis of mobility management challenges, particularly for the future mobile MRO self-optimization implementation in future technologies. [ABSTRACT FROM AUTHOR]

With the advancement of space technology and satellite communications, low-Earth-orbit (LEO) satellite networks have experienced rapid development in the past decade. In the vision of 6G, LEO satellite networks play an important role in future 6G networks. On the other hand, a variety of applications, including many delay-sensitive applications, are continuously emerging. Due to the highly dynamic nature of LEO satellite networks, supporting time-deterministic services in such networks is challenging. However, we can provide latency guarantees for most delay-sensitive applications through data plane traffic shaping and control plane routing optimization. This paper addresses the routing optimization problem for time-sensitive (TS) flows in software-defined low-Earth-orbit (LEO) satellite networks. We model the problem as an integer linear programming (ILP) model aiming to minimize path handovers and maximum link utilization while meeting TS flow latency constraints. Since this problem is NP-hard, we design an efficient longest continuous path (LCP) approximation algorithm. LCP selects the longest valid path in each topology snapshot that satisfies delay constraints. An auxiliary graph then determines the routing sequence with minimized handovers. We implement an LEO satellite network testbed with Open vSwitch (OVS) and an open-network operating system (ONOS) controller to evaluate LCP. The results show that LCP reduces the number of path handovers by up to 31.7% and keeps the maximum link utilization lowest for more than 75% of the time compared to benchmark algorithms. In summary, LCP achieves excellent path handover optimization and load balancing performance under TS flow latency constraints. [ABSTRACT FROM AUTHOR]

With the use of collaborative robots in intelligent manufacturing, human–robot interaction has become more important in human–robot collaborations. Human–robot handover has a huge impact on human–robot interaction. For current research on human–robot handover, special attention is paid to robot path planning and motion control during the handover process; seldom is research focused on human handover intentions. However, enabling robots to predict human handover intentions is important for improving the efficiency of object handover. To enable robots to predict human handover intentions, a novel human handover intention prediction approach was proposed in this study. In the proposed approach, a wearable data glove and fuzzy rules are firstly used to achieve faster and accurate human handover intention sensing (HIS) and human handover intention prediction (HIP). This approach mainly includes human handover intention sensing (HIS) and human handover intention prediction (HIP). For human HIS, we employ wearable data gloves to sense human handover intention information. Compared with vision-based and physical contact-based sensing, wearable data glove-based sensing cannot be affected by visual occlusion and does not pose threats to human safety. For human HIP, we propose a fast handover intention prediction method based on fuzzy rules. Using this method, the robot can efficiently predict human handover intentions based on the sensing data obtained by the data glove. The experimental results demonstrate the advantages and efficacy of the proposed method in human intention prediction during human–robot handover. [ABSTRACT FROM AUTHOR]

The indispensable need to realize smart cities, the cellular network, and particularly 5G, as the common denominator infrastructure for the coexistence of many other wireless technologies, is the apparent enabler infrastructure. One of the significant challenges in cellular networks is continual connectivity. In the wake of ever-increasing time-dependent demand and high mobility, this challenge cannot be adequately addressed by either conventional solutions such as cell splitting, roaming, and base stations number increase or far-from-practical yet unregulated wireless cognitive networks. The proposed roaming service concept, roaming-on-the-fly, complements the classic roaming in many otherwise non-served situations by providing more efficient spectrum utilization management through obviating high-level telecommunications agreements, employing a shared-economy model, and adoption of Ad-Hoc payment methods. The simulation results clearly show elevated visited operator income and uncompromised primary user satisfaction while establishing traditionally-impossible visiting-user services. The spectrum management scheme and the business model in this proposal are as simplistic as possible to make the concept, not the implementation details, the center of focus. More improvements are in perspective by introducing a more delicate spectrum. [ABSTRACT FROM AUTHOR]

Mobility management for heterogeneous networks (HetNets) remains one of the most important topics of modern research due to the joining of numerous user equipment (UE) with different capabilities. Handover is one of the core issues in network management that allows UEs to navigate, but it remains a challenging issue for continuous development in the field of telecom networking. One of the most important proposals in the field of networking is the Software Defined Network (SDN). This study exploited the SDN by shifting most of the handover procedure cost to SD-Switch and the SD-Controller. Next, we introduced other parameters along with signal strength (signal-to-interference plus noise ratio, delay, bandwidth, UE trajectory, UE speed) to ensure that the appropriate target Point of Access (PoA) is selected for the UE. UEs measure the parameters of neighboring PoAs with their serving PoA, as well as their location coordinates, and then send them to the SD-Switch via their serving PoA. A polynomial function is used in SD-Switch to track the UE's trajectory, and when a handover process is requested from the UE, SD-Switch will choose the appropriate PoA and only send the handover command to the UE for transportation. The performance metrics show an improvement in the proposed method in reducing the number of handovers, packets delay ratio, reducing packets loss ratio, and reducing the average of signaling messages overhead for the entire system. The proposed method reduced the average-signaling message overhead by more than 75% compared to previous studies. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the appearance of more and more bandwidth consuming applications in today's mobile data services market, telecom operators can no longer rely on price to attract and retain subscribers. Seamless roaming has become an important value-added service for improving back-end billing, subscriber relationships, bandwidth preservation through aggregation, quality of service and revenue generation. The paper presents the Mobile IP framework and methodology for supporting seamless global roaming within a geographic mobility domain. The goals and challenges of secured and seamless roaming solution are investigated. The responsibility of individual layers of the TCP/IP protocol stack is ill-defined with respect to mobility. The paper highlights the need for an adaptive generic algorithm to select, optimize and maintain transparent network connectivity for mobile users on the move, despite changing connection types and locations in a heterogeneous network environment. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the development and maturity of virtual reality (VR for short) and artificial intelligence technology, panoramic VR roaming is applied to more and more industries. In the construction engineering industry, due to the complex structure of some key building nodes, the application of panoramic VR roaming technology modeling will play a role in significantly reducing the workload and understanding difficulty of design, construction and management personnel. Therefore, this study improves the parallax map generation method of the belief propagation (BP) algorithm in the panoramic VR roaming to use the form of limit matching and optimizes the energy function and matching primitives in it, so as to propose a spatial model construction method of the panoramic VR roaming based on the improved BP algorithm. The experimental results show that the panoramic VR roaming space model construction method proposed in this study can significantly improve the quality of spatial modeling of building node images, and the normalized values of structural similarity of VR roaming space models designed based on Improved belief propagation (IBP), GC, BP, and DP algorithms are 3.32, 3.23, 2.96, and 2.84, respectively, when the number of iterations is obtained 200 times, is also the highest among the compared methods, for example, when the number of samples is 400, the calculation time of IBP scheme is 14.73 ± 0.85 min, and the highest time of other three schemes is 6.86 ± 0.67 min. Therefore, this virtual space modeling method is designed to be more suitable for application scenarios that require lower computational timeliness. [ABSTRACT FROM AUTHOR]

As mobile devices are widely used and various applications emerge, users have higher demands on data rates and computing power. Software Defined Network (SDN) can configure and manage various devices in the network through a centralized control controller, making the network more flexible. In an SDN-enabled edge computing environment, dense multiple access devices make mobile devices handover frequently, and mobile devices handover between different access points becomes an inevitable problem. To address this problem, we propose an Access Point (AP) handover strategy based on the signal strength and traffic load. The scheme uses the global view and centralized control capability of the SDN controller to obtain, manage, and analyze information, then calculate the weights and compare them, and finally develop the handover policy. On the other hand, to improve system resource utilization and meet the performance demands of different applications, MEC systems need to allocate computing and communication resources appropriately to keep users' Quality-of-Service (QoS) experience. We propose a joint optimization strategy for computing and communication resources based on the Lagrange multiplier method. The policy calculates and analyzes the task execution latency and energy consumption of edge servers and local terminals, and develops an optimization scheme for sub-channel allocation and resource allocation. It aims to reduce latency and energy consumption as much as possible. The results of the experiments in this paper illustrate that the proposed AP handover scheme which is on the basis of received signal strength indicator (RSSI) and traffic load can effectively improve the task completion time and energy consumption performance. The proposed joint optimization strategy of computing and communication resources based on the Lagrange multiplier method can effectively improve energy consumption and delay performance. [ABSTRACT FROM AUTHOR]

With the purpose of providing higher data rate and ultra-reliable and low-latency communications for the users, employing the small cells in the upcoming Fifth-Generation-New Radio (5G-NR) cellular networks and beyond is leading to the serious challenges in mobility management due to dynamicity of the user equipments (UEs). Among different issues related to the mobility of the UEs, the handover management is one of the key procedures to let the UEs experience a high quality of service (QoS)/quality of experience (QoE). So far, many protocols and algorithms have been proposed to enhance the mobility management in 5G-NR from various aspects, but still a thorough survey has not been incorporated to summarize the recent advances and future directions of the mentioned issue. Thus, the handover management and the corresponding challenges stand in the center of concentrations in this paper, with a glance on 4G to the advancements of 5G-NR. The challenges include QoS/QoE, throughput, delay, traffic load, the attacks during authentication process and resource allocation. To overcome the mentioned challenges, the handover procedure is evaluated by some key performance indicators such as handover ratio, handover failure, radio link failure and such like which depend on the received signal quality. The lack of new advancements and novel aspects of handover plus the separation of security and handover issues in previous works are perceived as research gaps and motivations for the current paper. In this regard, this paper aims to specify and analyze the technical issues, to provide an overview on the proposed methods and recent advances and to bring the future directions into the limelight. We categorize the concurrent standards and methods about the handover, and then, we survey the proposed algorithms including theoretical, algorithm-based and pattern-capturing approaches following the authentication process along with the vulnerabilities and the algorithms to counteract the attacks during handover. Also, we study various issues corresponding to network performance during the handover procedure. Finally, we discuss the open problems and future research directions. [ABSTRACT FROM AUTHOR]

Fifth-generation (5G) networks offer high-speed data transmission with low latency, increased base station volume, improved quality of service (QoS), and massive multiple-input–multiple-output (M-MIMO) channels compared to 4G long-term evolution (LTE) networks. However, the COVID-19 pandemic has disrupted the achievement of mobility and handover (HO) in 5G networks due to significant changes in intelligent devices and high-definition (HD) multimedia applications. Consequently, the current cellular network faces challenges in propagating high-capacity data with improved speed, QoS, latency, and efficient HO and mobility management. This comprehensive survey paper specifically focuses on HO and mobility management issues within 5G heterogeneous networks (HetNets). The paper thoroughly examines the existing literature and investigates key performance indicators (KPIs) and solutions for HO and mobility-related challenges while considering applied standards. Additionally, it evaluates the performance of current models in addressing HO and mobility management issues, taking into account factors such as energy efficiency, reliability, latency, and scalability. Finally, this paper identifies significant challenges associated with HO and mobility management in existing research models and provides detailed evaluations of their solutions along with recommendations for future research. [ABSTRACT FROM AUTHOR]

Satellite–ground integrated networks (SGIN) are in line with 6th generation wireless network technology (6G) requirements. However, security and privacy issues are challenging with heterogeneous networks. Specifically, although 5G authentication and key agreement (AKA) protects terminal anonymity, privacy preserving authentication protocols are still important in satellite networks. Meanwhile, 6G will have a large number of nodes with low energy consumption. The balance between security and performance needs to be investigated. Furthermore, 6G networks will likely belong to different operators. How to optimize the repeated authentication during roaming between different networks is also a key issue. To address these challenges, on-demand anonymous access and novel roaming authentication protocols are presented in this paper. Ordinary nodes implement unlinkable authentication by adopting a bilinear pairing-based short group signature algorithm. When low-energy nodes achieve fast authentication by utilizing the proposed lightweight batch authentication protocol, which can protect malicious nodes from DoS attacks. An efficient cross-domain roaming authentication protocol, which allows terminals to quickly connect to different operator networks, is designed to reduce the authentication delay. The security of our scheme is verified through formal and informal security analysis. Finally, the performance analysis results show that our scheme is feasible. [ABSTRACT FROM AUTHOR]

5G networks are expected to deliver very high data rates with enhanced quality of service (QoS) at a very low cost. To meet the demands of high data rates and improved QoS, ultra-densification is the key solution used in 5G networks. In this paper we propose a call admission control (CAC) policy by considering the main components of an ultra-dense 5G network, namely, macrocell, picocell and femtocell. The calls in the network are accepted based on the SNIR ranges which help in deciding whether the call will be connected to a macrocell or picocell or femtocell. We also come up with a handover management scheme which regulates the handover of calls between macrocell to macrocell (picocell or femtocell), picocell to macrocell (picocell or femtocell) and femtocell to macrocell (picocell or femtocell). The performance analysis of the proposed CAC policy and the handover management scheme is also conducted in the paper. For this, we construct analytical models with the help of continuous-time Markov chains for the macrocell, picocell and femtocell network to obtain the performance metrics such as blocking probability of new calls and dropping probability of handover calls. The analytical results are further investigated to establish the importance of ultra-densification in 5G network. The proposed analytical models are also validated via simulation. A comparative analysis is also performed between the proposed CAC policy and an existing CAC policy in literature which considers only macrocells and femtocells in the network. [ABSTRACT FROM AUTHOR]

With the rapid developments of fifth generation (5G) mobile communication networks in recent years, different use cases can now significantly benefit from 5G networks. One such example is high-speed trains found in several countries across the world. Due to the dense deployment of 5G millimetre wave (mmWave) base stations (BSs) and the high speed of moving trains, frequent handovers (HOs) occur which adversely affect the Quality-of-Service (QoS) of mobile users. User association for load balancing is also a key issue in 5G networks. Therefore, HO optimisation and resource allocation are major challenges in the mobility management of high-speed train systems. Handover Margin (HOM) and Time-to-Trigger (TTT) parameters are crucial for the HO process since they affect the key performance indicators (KPIs) of high-speed train systems in 5G networks. To manage system performance from the aspect of predictive analytics, we have modelled system performance of mobility management through machine learning (ML). First, the HO management process of a high-speed train scenario is framed as a supervised ML problem. The inputs for the problem are regression task, HOM and TTT and the outputs are key performance indicators (KPIs). Second, data processing is accomplished after generating a simulation dataset. Several methods are employed for the dataset, such as Adaptive Boosting (AdaBoost), Gradient Boosting Regression (GBR), CatBoost Regression (CBR), Support Vector Regression (SVR), Multi-layer Perceptron (MLP), Kernel Ridge Regression (KRR) and K-Nearest Neighbour Regression (KNNR). Tenfold cross validation is then applied for choosing the best hyperparameters. Finally, the deployed methods are compared in terms of the Mean Absolute Error (MAE), Mean Square Error (MSE), Maximum Error (Max E), and R2 score metrics. From the MAE results, CBR achieves the best outcomes for load level and throughput KPIs with 0.003 and 0.0144, respectively. On the other hand, GBR achieves the best results for call dropping ratio (CDR), radio link failure (RLF) and spectral efficiency KPIs with 0.354, 0.082 and 0.354, respectively. CBR also follows GBR for the three KPIs with 0.356, 0.082 and 0.357, respectively. Only a slight difference in estimations is present. MLP achieves the best results for HO ping-pong (HOPP) and HO probability (HOP) KPIs with 0.0045 and 0.011, respectively. This is followed by GBR and CBR. From the MSE outcomes, CBR and GBR exhibit the best results for load level and throughput KPIs with 2e-5 and 3e-5, respectively. GBR attains the best results for CDR, RLF and spectral efficiency KPIs with 0.25, 0.011 and 0.025, respectively. Accordingly, CBR follows GBR with slightly different errors for the three KPI estimations. MLP achieves the best results for HOPP and HOP KPIs with 5e-5 and 3.6e-5, respectively. Again, this is followed by GBR and CBR for the estimation of these results. This indicates that CBR and GBR can capture relationships between inputs and KPIs for the dataset used in this study, outperforming all other methods generally used for solving this problem. [ABSTRACT FROM AUTHOR]

The fifth-generation (5G) ultra-dense networks (UDNs) using dynamic beamforming have drawn massive attention due to their ability to increase spectral and energy efficiency. This paper explores the handoff management process for 5G UDNs with dynamic beamforming. The handoff management between any two base stations is implemented through the beam scanning mechanism based on angle of arrival and angle of departure, allowing base stations to switch seamlessly from one antenna beam to another. Utilizing the beamforming technology allows the base station to track the user location, as well as the user devices' movements during handoff, thus providing a better user experience. The proposed handoff management for 5G UDNs with dynamic beamforming reduces handoff latency significantly, leading to an increase in efficiency. Besides, the proposed system also increases the service availability and supports connections between the base station and user through narrow beams, enabling more users to use the service at the same time. The conclusion presented in this paper is that the proposed handoff management in 5G UDNs with dynamic beamforming is an effective solution to various technical challenges associated with handoff management in wireless networks. [ABSTRACT FROM AUTHOR]

Currently, there are four major protocols for EV roaming that support electric vehicle drivers to access charge points from different networks with a single user registration through roaming agreements between charge point operators (CPOs) and mobility service providers (MSPs): the Open Clearing House Protocol (OCHP), the Open InterCharge Protocol (OICP), the eMobility Inter-operation Protocol (eMIP), and the Open Charge Point Interface (OCPI). These protocols facilitate data exchange between CPOs and MSPs using a roaming hub or peer-to-peer connections. On the other hand, the Open Charge Point Protocol (OCPP) is the standard protocol widely used for communication between the charge point and the central system within the CPO's internal system. OCPP has been integrated into many charge point products today, where OCPP 1.6 supports Simple Object Access Protocol (SOAP) and JavaScript Object Notation (JSON) data format over the WebSocket, with the charge point acting as the WebSocket client and the central system as the WebSocket server. The aim of this study is to further enhance the functionality of OCPP by integrating the role of the WebSocket client into the central system to support EV roaming for EV drivers. This new approach describes the architecture that includes the actors and their roles, which are the Charge Point that delivers energy to electric vehicles, the Central System that manages the Charge Point and requests for EV roaming, and the National Access Point that acts as a roaming hub in the proposed EV roaming system. Additionally, three simulation models have been created, each representing an actor and their role in the proposed system. The feasibility and effectiveness of the proposed EV roaming system are evaluated through experiments during high traffic load conditions of a network using the simulation models and actual charge point products. The experiment scenarios specifically focus on cases related to user authorization and billing. This study only concern on the time consumption for user authorization. The results confirm that the proposed EV roaming system can be implemented based on the enhanced functionality of the OCPP, with the average time for user authorization over five attempts range between 3 ms for the simplest scenario one to 2200 ms for the most complex scenario four, which can be considered quite impressive. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Carrier aggregation (CA) is a technology introduced by the Long-Term Evolution-Advanced (LTE-A) system to increase user throughput by combining a selected number of component carriers (CCs). Its integration with heterogeneous networks enables the mobile user equipment to take advantage of increased throughput and radio coverage of various access technologies. However, due to the mobility of user equipment, these innovations have increased the likelihood of handoff scenarios, resulting in a high outage probability and low throughput. Handover is a crucial part of mobility management since it enables users to move from one cell to another while maintaining connections. However, no single access technique can provide seamless communication without interruption or delay. As a result, creating a suitable handover decision algorithm is necessary for ensuring highquality service continuity and dependable user equipment access to the network at all times. An Adaptive Real-Time Spectrum Selection Framework and Handover Decision Algorithm (RSSF-HDA) with optimal resource allocation to the deployed system model is presented in this paper. This effort is geared toward preventing communication failure and improving system performance. It further positions the 4G LTE-A framework for inclusive coexistence with the current 5G New Radio enhanced Mobile Broadband (eMBB) use case scenario. The results of the simulation reveal that this method increases system performance in terms of Cell edge spectral efficiency and Handover success rate above 10% and 13%, respectively, when compared to Conventional Handover Decision Algorithm (Conv-HDA) and Multi-Influence Factor Handover Decision Algorithms (MIFHDA). [ABSTRACT FROM AUTHOR]

Summary: The Internet of Vehicles (IoV) has become a lot of concern for scientific society because of its rising importance in creating an intelligent transportation system. However, the existing systems addressed handover and network selection difficulties, but they did not solve the necessity for frequent handover problems. Hence, in this research, handover decision difficulties are removed by using a novel state‐action–reward–state‐action reinforcement learning method in which it learns the current policy action to determine whether a handover decision is required in the fast‐moving vehicle therefore the handover failure problem is reduced. Moreover, the existing fuzzy rules do not consider non‐line‐of‐sight and the learning capabilities of the neural networks to select the suitable network therefore it creates network selection difficulty. Hence, the network selection difficulties are removed by using a novel fuzzy‐based graph neural network in which the fuzzy logic is connected to the graph hierarchical structure to select the right network therefore the efficient and suitable network is selected on the internet of vehicle communication. Moreover, the existing process is to select the routes completely established on the ancient broadcast history of the vehicles and their channel metrics which causes the frequent handover and poor performance of the network. Hence, the routing selection problem is eliminated by using a novel cluster‐based routing algorithm in which the vehicle was divided into clusters to select the efficient route of the internet of the vehicle therefore the best routing path is carried out. As a result, the proposed system is improving the quality of the service and reducing the handover failure and delay of the system. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is an emerging technology that provides services to any smart device at any place. Due to the large volume of data and dynamicity, the IoT environment faces challenges in terms of overloading and energy consumption. To resolve those issues, we proposed MISSION (MobIlity taSk Scheduling OffloadiNg) method to solve these problems, and for that, we present four phases. (1). History aware handover process, in this stage we manage the mobility of IoT devices to reduce the retransmission rate. The handover is managed by 5G gateway for that we proposed Mobility Aware Proximal Policy Optimization (MAPPO) algorithm with RSS, direction, and distance parameters. (2). Multi criteria based task classification and scheduling, in this stage first the tasks are classified into four types such as real time task, non-real time task, delay sensitive task and resource intensive task and the classified tasks are given to the input for scheduling, for scheduling we consider a priority, maximum response time, size of data, task completion time and energy. Both the classification and scheduling are done by Di-Process Modular Neural Network (Di-MNN). (3). Energy aware task allocation, in this process, first we calculate the weight value of the task using First Fitness based Animal Migration Optimization (FFAMO) which considers processing time, processing cost, throughput, and energy consumption parameters. And then the weighted task is assigned to the optimal fog by using Capacity based Hungarian Assignment algorithm (CH2A) by considering the load of task, waiting time, energy consumption, and distance which allocates the task optimally. (4). Efficient task offloading on virtual fog nodes, during scheduling or task allocation the fog node gets overloaded that time virtual fog is created by the central fog node using graph entropy. Finally, simulation is done by iFogsim which evaluates the performance in terms of completion time, energy consumption, delay, response time, number of unnecessary handovers, offloading time, bandwidth utilization, and fog load and throughput. [ABSTRACT FROM AUTHOR]

Navigation and positioning is a new growth point of wireless services. And seamless positioning is the current development trend of navigation and positioning services. In view of the problems that dynamic handover cannot be performed during site movement, STA only selects the optimal AP according to the indication of received signal strength, and the handover delay is too long. This paper proposes a research on indoor and outdoor seamless positioning technology based on artificial intelligence and intelligent switching algorithm. The purpose is to study the influence of reducing the positioning data with too large error on the final positioning result. The method of this paper is to propose an intelligent switching algorithm and then discuss the research status and development direction of indoor positioning technology and outdoor positioning technology, respectively, and point out the switching methods between them. The role of these methods is to analyze the current situation of indoor and outdoor navigation technology, especially the development route of seamless positioning technology. It determines the strategy of integrating heterogeneous positioning systems to build a seamless positioning system to maximize the use of existing positioning system resources. This paper studies the design and implementation of the seamless positioning system through the simulation experiment of the intelligent switching algorithm and finally tests the system through the experimental vehicle. The online experiment results show that the system can achieve high positioning accuracy in indoor and outdoor environments, especially at its junction, and the positioning errors in all directions are within 0.2 m. [ABSTRACT FROM AUTHOR]

Fifth Generation (5G) signals using the millimeter wave (mmWave) spectrums are highly vulnerable to blockage due to rapid variations in channel link quality. This can cause the devices or User Equipment (UE) to suffer from connection failure. In a dual connectivity (DC) network, the channel's intermittency issues were partially solved by maintaining the UE's connectivity to primary (LTE advanced stations) and secondary (5G mmWave stations) simultaneously. Even though the dual-connected network performs excellently in maintaining connectivity, its performance drops significantly due to the inefficient handover from one 5G mmWave station to another. The situation worsens when UE travels a long distance in a highly dense obstacle environment, which requires multiple ineffective handovers that eventually lead to performance degradation. This research aimed to propose an Adaptive TTT Handover (ATH) mechanism that deals with unpredictable 5G mmWave wireless channel behaviors that are highly intermittent. An adaptive algorithm was developed to automatically adjust the handover control parameters, such as Time-to-Trigger (TTT), based on the current state of channel condition measured by the Signal-to-Interference-Noise Ratio (SINR). The developed algorithm was tested under a 5G mmWave statistical channel model to represent a time-varying channel matrix that includes fading and the Doppler effect. The performance of the proposed handover mechanism was analyzed and evaluated in terms of handover probability, latency, and throughput by using the Network Simulator 3 tool. The comparative simulation result shows that the proposed adaptive handover mechanism performs excellently compared to conventional handovers and other enhancement techniques. [ABSTRACT FROM AUTHOR]

Given the growing number of devices and their need for internet access, researchers are focusing on integrating various network technologies. Concerning indoor wireless services, a promising approach in this regard is to combine light fidelity (LiFi) and wireless fidelity (WiFi) technologies into a hybrid LiFi and WiFi network (HLWNet). Such a network benefits from LiFi's distinct capability for high-speed data transmission and from the wide radio coverage offered by WiFi technologies. In this paper, we describe the framework for the HWLNet architecture, providing an overview of the handover methods used in HLWNets and presenting the basic architecture of hybrid LiFi/WiFi networks, optimization of cell deployment, relevant modulation schemes, illumination constraints, and backhaul device design. The survey also reviews the performance and recent achievements of HLWNets compared to legacy networks with an emphasis on signal to noise and interference ratio (SINR), spectral and power efficiency, and quality of service (QoS). In addition, user behaviour is discussed, considering interference in a LiFi channel is due to user movement, handover frequency, and load balancing. Furthermore, recent advances in indoor positioning and the security of hybrid networks are presented, and finally, directions of the hybrid network's evolution in the foreseeable future are discussed. [ABSTRACT FROM AUTHOR]

This research investigates the performance of energy consumption referred to data rates in a disaster environment. The traffic is divided into low and high data rates. Referring to the QoS traffic class, the low data rate is between 100 kbps (web surfing) to 150 kbs (voice-over IP application), meanwhile, the high data rate is about 500 kbps and use for video conferencing. During a natural disaster, users' connections rely on the affected mobile towers that have limited power of battery backup due to power failure. The amount of energy left over in the battery is equal to the number of connections managed by the tower. If no countermeasure is taken for the high traffic users, the affected towers may be dysfunctional due to no power left to operate, hence difficult for search and rescue operation. Therefore, energy consumption based on data rate analysis was investigated by using handover decision parameters. From the result, high data rate consumes more power consumption of base station (BS) than low data rate. So, we integrate 0.2 partial of high rate and 0.8 partial of low data rate users to our proposed handover algorithm for user satisfaction during natural disaster. Simulation results show that the network performance for the number of handovers per ratio for high data rate based on number of UEs is considered high for Case 5 although it uses more low data rate type of traffic than high data rate. Hence, by using the proposed handover algorithm, it will not burden the affected BSs which only depend on battery backup due to hardware failure during natural disaster. [ABSTRACT FROM AUTHOR]

5G use cases, for example enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and an ultra-reliable low latency communication (URLLC), need a network architecture capable of sustaining stringent latency and bandwidth requirements; thus, it should be extremely flexible and dynamic. Slicing enables service providers to develop various network slice architectures. As users travel from one coverage region to another area, the call must be routed to a slice that meets the same or different expectations. This research aims to develop and evaluate an algorithm to make handover decisions appearing in 5G sliced networks. Rules of thumb which indicates the accuracy regarding the training data classification schemes within machine learning should be considered for validation and selection of the appropriate machine learning strategies. Therefore, this study discusses the network model’s design and implementation of self-optimization Fuzzy Qlearning of the decision-making algorithm for slice handover. The algorithm’s performance is assessed by means of connection-level metrics considering the Quality of Service (QoS), specifically the probability of the new call to be blocked and the probability of a handoff call being dropped. Hence, within the network model, the call admission control (AC) method is modeled by leveraging supervised learning algorithm as prior knowledge of additional capacity. Moreover, to mitigate high complexity, the integration of fuzzy logic as well as Fuzzy Q-Learning is used to discretize state and the corresponding action spaces. The results generated from our proposal surpass the traditional methods without the use of supervised learning and fuzzy-Q learning. [ABSTRACT FROM AUTHOR]

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The non-terrestrial network (NTN) is a network that uses radio frequency (RF) resources mounted on satellites and includes satellite-based communications networks, high altitude platform systems (HAPS), and air-to-ground networks. The fifth generation (5G) and NTN may be crucial in utilizing communication infrastructure to provide 5G services in the future, anytime and anywhere. Based on the outcome of the Rel-16 study, the 3rd generation partnership project (3GPP) decided to start a work item on an NTN in 5G new radio (NR) Rel-17, and the focus of the study was on mobility management procedures, due to the movements of NTN platforms; especially, low earth orbit (LEO) satellites. Handover enhancements were discussed to tackle the frequent handover due to the fast satellite movement. Therefore, the major problem of handover in LEO satellite systems was the signaling storm created by handing over all user equipment (UE) in a cell to a new cell because when the UE crosses the boundary between the neighboring cell of a satellite, an intra-satellite or cell handover occurs; thus, all users in a cell are expected to experience a change of cell due to handover every few seconds. In addition, UE location is not easy to define due to moving cell/beam situations. In this study, we propose machine learning-based solutions for handover decisions in non-terrestrial networks for cell handovers or intra-satellite handovers to reduce signaling storms during handovers where the handover requests will be executed by clustered users. First, the dataset was generated by the simulator that simulates communication between users and satellites. Second, we preprocessed the data, and also used the feature creation technique to create the distance feature using the Haversine formula, and then applied clustering and classification algorithms. The experimental results show that the distance between a user and its cell center is an important parameter for handover decisions in NTN, and the random forest outperforms all models with a higher accuracy of 99% along with a better F1-score of 0.9961. [ABSTRACT FROM AUTHOR]

Mobile data has become an integral part of everyday life, making Internet trends more and more profound and deeply embedded in life and the future. Mobile broadband (MBB) is one of the main aims of fifth-generation (5G) networks due to unprecedented growth in data demand. However, 5G networks are not yet deployed in many countries, whereas existing MBB networks, such as third generation (3G) and fourth generation (4G), are available in most world countries. As a result, there is a need to monitor and troubleshoot end-to-end network performance and ensure a better user experience. This paper provides an overview of MBB networks in terms of deployment environments, performance metrics, and implementation scenarios. It highlights the most important criteria for assessing MBB performance and the applications and measurement methods utilized, such as external and internal measurements and the classification of geographical areas. In addition, it provides measurement-based performance analyses of two existing mobile network operators (MNOs) (Omantel and Ooredoo) in the Sultanate of Oman. This performance analysis uses data measurements in various indoor and outdoor environments in five cities (Muscat, Ibra, Sur, Bahla, and Al kamil Wal Wafi). Several performance metrics are considered, such as signal level and quality, throughput, ping rate, and handover. Experimental results demonstrate that the 4G networks were the dominant networks in all measured locations for indoor and outdoor scenarios. Moreover, 5G data measurements are also recorded in the capital city of Oman, Muscat. The results of the 5G measurements show that both MNOs achieved a higher data rate with a lower ping rate. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Ensuring a seamless connection with various types of mobile user equipment (UE) items is one of the more significant challenges facing different generations of wireless systems. However, enabling the high-band spectrum -- such as the millimeter wave (mmWave) band -- is also one of the important factors of 5G networks, as it enables them to deal with increasing demand and ensures high coverage. Therefore, the deployment of new (small) cells with a short range and operating within the mmWave band is required in order to assist the macro cells which are responsible for operating long-range radio connections. The deployment of small cells results in a new network structure, known as heterogeneous networks (HetNets). As a result, the number of passthrough cells using the handover (HO) process will be dramatically increased. Mobility management (MM) in such a massive network will become crucial, especially when it comes to mobile users traveling at very high speeds. Current MM solutions will be ineffective, as they will not be able to provide the required reliability, flexibility, and scalability. Thus, smart algorithms and techniques are required in future networks. Also, machine learning (ML) techniques are perfectly capable of supporting the latest 5G technologies that are expected to deliver high data rates to upcoming use cases and services, such as massive machine type communications (mMTC), enhanced mobile broadband (eMBB), and ultra-reliable low latency communications (uRLLC). This paper aims to review the MM approaches used in 5G HetNets and describes the deployment of AI mechanisms and techniques in "connected mode" MM schemes. Furthermore, this paper addresses the related challenges and suggests potential solutions for 5G networks and beyond. [ABSTRACT FROM AUTHOR]

Vehicular ad-hoc networks (VANET) suffer from dynamic network environment and topological instability that caused by high mobility feature and varying vehicles density. Emerging 5G mobile technologies offer new opportunities to design improved VANET architecture for future intelligent transportation system. However, current software defined networking (SDN) based handover schemes face poor handover performance in VANET environment with notable issues in connection establishment and ongoing communication sessions. These poor connectivity and inflexibility challenges appear at high vehicles speed and high data rate services. Therefore, this paper proposes a flexible handover solution for VANET networks by integrating SDN and fog computing (FC) technologies. The SDN provides global knowledge, programmability and intelligence functions for simplified and efficient network operation and management. FC, on the other hand, alleviates the core network pressure by providing real time computation and transmission functionalities at edge network to maintain the demands of delay sensitive applications. The proposed solution overcomes frequent handover challenges and reduces the processing overhead at core network. Moreover, the simulation evaluation shows significant handover performance improvement of the proposed solution compared to current SDN based schemes, especially in terms of handover latency and packet loss ratio under various simulation environments. [ABSTRACT FROM AUTHOR]

The Heterogeneous Network (HetNet) based ultra-dense network is the possible solution to cope up with the exponential growth in data traffic. The HetNet deployment provides benefits of load balancing, better connectivity and higher data rate to the users. However, the diversity in transmit power results in downlink (DL)/uplink (UL) imbalance and poses a serious issue in mobility management. Adoption of DL/UL decoupled (DUDe) handover (HO) method where DL and UL HO occurs separately which could possibly improve the user's quality of service and network performance. The control parameters involved in this DUDe HO procedure should be properly configured to achieve the expected performance. In this work, simulation analysis has been carried out to explore the dependency of these control parameters on various factors such as Inter-Site-Distance (ISD), velocity and offloading. The analytical results provide interesting insights about the control parameter configuration in decoupled wireless connection. From the analysis results, measurement configuration strategy has been developed to configure the HCP in decoupled HO method. The results show the proposed method achieves increase in dwell time when compared to the legacy coupled HO method. [ABSTRACT FROM AUTHOR]

This paper proposes a multifrequency seamless dual-link handover scheme based on beamforming for the high-speed railway (HSR) communication, i.e., when the train travels to the edge of overlapping area of the adjacent two cells, a gain beam is assigned to the overlapping area by the target base station (BS) using a beamforming technique to cover the entire region to enhance the received signal strength (RSS) and handover opportunity. The switching antenna is allowed to handover multiple times to improve the traditional scheme and reduce the handover failure probability (HFP) greatly. In the process of signal reception, considering the impact of the intercell cochannel interference on the RSS, the proposed scheme uses signal to interference ratio (SIR) instead of the RSS to indicate the received signal quality to optimize handover mode. The handover success probability (HSP) is analyzed to describe the relationship between train location and the probability. We also establish a probabilistic model and corresponding handover algorithm for the proposed scheme to complete the handover operations and theoretically analyze a series of indexes including handover trigger probability (HTP), HFP, communication interruption probability (CIP), and HSP. Theoretical and experimental results show that the proposed scheme can effectively improve the HTP and HSP and greatly reduce the HFP and the CIP. [ABSTRACT FROM AUTHOR]

The co‐channel interference and frequent handoff are two important issues that have a great impact on the spectrum and energy efficiency in the non‐orthogonal multiple access (NOMA) with successive interference cancellation (SIC) in the small cell networks (SCN). This paper investigates the performance of SIC decoding order based on the users' channel state information (CSI) and random SIC decoding order under the perfect and imperfect conditions for the handoff optimization in SCNs with NOMA. The effect of SIC decoding order in the joint base station association and power control problem is studied by considering the motion of mobile users (MUs). Two optimization problems are formulated using the number of associated MUs, the number of handoffs, and the transmit power of all MUs, under the maximum allowable transmit power and minimum average‐rate constraints. Two objectives are combined into a single‐stage optimization problem through the weighted sum method. The formulated problem is solved using a game theory‐based algorithm and primal decomposition theory. The simulation results show that changing the SIC decoding order can lead to performance improvement in the uplink NOMA‐ based SCNs. Also, it is shown that the proposed algorithm can significantly reduce the frequent handoffs in small cell networks. [ABSTRACT FROM AUTHOR]

Simulation is a cost-effective, simple, and straightforward approach to implementing a system for exhaustive analysis. Many commercial and open-source simulators, such as NS2, NS3, OMNET++, OPNET, QualNet, etc., exist in the literature to simulate wired and wireless networks. However, the major challenge in dealing with open-source simulators is analysing the results and presenting their performance metrics. Further, the ever-increasing demands of the users in terms of higher data rates with uninterrupted connections resulted in a heterogeneous wireless network (HWN) that supports the integration of WiFi, WiMAX, LTE, etc. Amongst all network simulators available in the literature, NS2 and NS3 are the most popularly used by the research community because of their immense support for implementing and verifying innovative networking algorithms. Furthermore, with the contribution of the National Institute of Science and Technology (NIST), NS2 supports the simulation of WiFi and WiMAX heterogeneous wireless networks with Media Independent Handover and Mobile-IPv6 which is yet to be supported entirely by NS3. However, the major shortcoming of NIST's contribution is the ease of developing a simulation script followed by result analysis. In continuation with the NIST's contribution, this paper proposes a Graphical User Interface-based evaluation suite (ES) for the simulation of User Datagram Protocol applications' in HWN, referred to as ES-HWN. With the support of this suite, the research community can quickly develop the heterogeneous wireless network simulation script followed by the textual and graphical results of handover, packets sent and received, throughput, packet delay, and jitter. The proposed ES-HWN supports the configuration of 10 WiFi and WiMAX interface mobile nodes with two WiFi-Access Points and a WiMAX-Base Station. Besides, it supports the configuration of UDP-based applications' packet size and transmission rate. Finally, over many experiments, ES-HWN exhibited 100% reliable results. [ABSTRACT FROM AUTHOR]

In this era of telecommunication, quality of service (QoS) is the prime metric for defining the performance of wireless networks. However, QoS is highly affected by the levels of signal strength. Variations in signal strength lead to several undesirable consequences, increasing wireless device's power consumption, especially during handover. In the perspective of Green Networking, to devise energy-efficient handover techniques, this paper compares the power consumption of wireless nodes under different states of affairs, leading to variations in signal strength. A vertical handover scenario between Wi-Fi and WiMAX networks was carried out to analyze the power consumption of two different sets of nodes, namely Type-I and Type-II nodes. Five different scenarios leading to signal strength fluctuations during handover were considered during the study. The initial energy levels of nodes were calculated at three different voltage levels, namely charge voltage, nominal voltage and cut-off voltage. The results explained the individual battery drainage pattern of wireless nodes with variations in signal strength under different scenarios and evaluated the cumulative power consumption of wireless nodes with variable signal strength at three voltage levels. Network performance was analyzed based on residual energy of nodes, throughput and packet delivery ratio. The cumulative analysis of power consumption presented in this paper can provide a prominent proposal of the battery drainage pattern of wireless nodes for various scenarios leading to variable signal strength, which can serve as a roadmap for devising energy-efficient mechanisms during handover in new generation ubiquitous networks. [ABSTRACT FROM AUTHOR]

Enhanced mobile broadband is an essential target in fifth-generation (5G) networks with higher demands among service consumers. It offers very high-speed Internet connections for several geographical areas: urban, suburban, and rural. Many mobile network operators (MNOs) continuously monitor the quality of service in terms of multiple services to guarantee high network performance. To the best of our knowledge, no extensive studies and analyses are conducted on mobile broadband (MBB) services that cover various implementation scenarios and several performance metrics. This study comprehensively analyzes the existing MBB performance in an urban area: Cyberjaya City, Malaysia. The measurement data were collected through drive tests from various MNOs supporting 3G and 4G technologies: Maxis, Celcom, Digi, U Mobile, and Unifi. Several performance metrics, such as signal quality, throughput (downlink and uplink), ping, and handover, were measured during the drive tests. The data measurements were conducted in two scenarios: outdoor and indoor environments. Measurement results of the outdoor drive test demonstrate that the maximum average throughput with downlink and uplink data rates is 14.3 and 7.1 Mbps, respectively, whereas the minimum average ping and loss are 36.5 ms and 0.14, respectively, for all MNOs. However, the in-building measurements achieve an acceptable overall average data rate of 2 Mbps. This paper provides several suggestions and recommendations for MBB providers to improve their performance networks and quality of experience to meet customers' satisfaction. Several limitations not considered in this study and can point to possible future work are presented. [ABSTRACT FROM AUTHOR]

With the rapid growth of data traffic and mobile devices, it is imperative to provide reliable and stable services during mobility. Heterogeneous Networks (HetNets) and dense networks have been identified as potential solutions to address the upcoming capacity crunch, but they also pose significant challenges related to handover optimization. This paper presents a comprehensive review of recent handover decision algorithms in HetNets, categorizing them based on their decision techniques and summarizing their input parameters, techniques, and performance evaluations. Our study highlights the technical challenges and opportunities related to handovers in HetNets and dense cellular networks and provides key findings from recent studies. The significance of this survey is to provide a comprehensive overview of handover decision algorithms in HetNets and dense cellular networks, which can aid in the development of more advanced handover optimization approaches. [ABSTRACT FROM AUTHOR]

Multipath communication has recently arisen as a promising tool to address reliable communication in vehicular networks. The architecture of Multipath TCP (MPTCP) is designed to facilitate concurrent utilization of multiple network interfaces, thereby enabling the system to optimize network throughput. In the context of vehicular environments, MPTCP offers a promising solution for seamless roaming, as it enables the system to maintain a stable connection by switching between available network interfaces. This paper investigates the suitability of MPTCP to support resilient and efficient Vehicleto-Infrastructure (V2I) communication over heterogeneous networks. First, we identify and discuss several challenges that arise in heterogeneous vehicular networks, including issues such as Head-of-Line (HoL) blocking and service interruptions during handover events. Then, we propose a cross-layer path management scheme for MPTCP, that leverages real-time network information to improve the reliability and efficiency of multipath vehicular communication. Our emulation results demonstrate that the proposed scheme not only achieves seamless mobility across heterogeneous networks but also significantly reduces handover latency, packet loss, and out-of-order packet delivery. These improvements have a direct impact on the quality of experience for vehicular users, as they lead to lower application layer delay and higher throughput. [ABSTRACT FROM AUTHOR]

Adaptation of handover parameters in ultra-dense networks has always been one of the key issues in optimizing network performance. Aiming at the optimization goal of effective handover ratio, this paper proposes a deep Q-learning (DQN) method that dynamically selects handover parameters according to wireless signal fading conditions. This approach seeks good backward compatibility. In order to enhance the efficiency and performance of the DQN method, Long Short Term Memory (LSTM) is used to build a digital twin and assist the DQN algorithm to achieve a more efficient search. Simulation experiments prove that the enhanced method has a faster convergence speed than the ordinary DQN method, and at the same time, achieves an average effective handover ratio increase of 2.7%. Moreover, in different wireless signal fading intervals, the method proposed in this paper has achieved better performance. [ABSTRACT FROM AUTHOR]

Due to their limited computation capabilities and battery life, Internet of Things (IoT) networks face significant challenges in executing delay-sensitive and computation-intensive mobile applications and services. Therefore, the Unmanned Aerial Vehicle (UAV) mobile edge computing (MEC) paradigm offers low latency communication, computation, and storage capabilities, which makes it an attractive way to mitigate these limitations by offloading them. Nevertheless, the majority of the offloading schemes let IoT devices send their intensive tasks to the connected edge server, which predictably limits the performance gain due to overload. Therefore, in this paper, besides integrating task offloading and load balancing, we study the resource allocation problem for multi-tier UAV-aided MEC systems. First, an efficient load-balancing algorithm is designed for optimizing the load among ground MEC servers through the handover process as well as hovering UAVs over the crowded areas which are still loaded due to the fixed location of the ground base stations server (GBSs). Moreover, we formulate the joint task offloading, load balancing, and resource allocation as an integer problem to minimize the system cost. Furthermore, an efficient task offloading algorithm based on deep reinforcement learning techniques is proposed to derive the offloading solution. Finally, the experimental results show that the proposed approach not only has a fast convergence performance but also has a significantly lower system cost when compared to the benchmark approaches. [ABSTRACT FROM AUTHOR]

The advancements in wireless communication go in leaps and bounds ushering in due attention to spectrum sharing. Spectrum scarcity isoneof the major limitations causing hardships in the existing wireless networks. Cognitive Radio Networks (CRNs) emerge as a solution to tide over such humps. It prompts the secondary user (SU) to look out for unused spectrum and utilize them. The CRN helps the SU by permitting it to switch over to unused portions of the spectrum. When a primary user (PU) claims back the spectrum, SU is obliged to perform a spectrum handoff. The SU decides the type of policy to be chosen for the handoff. Such a decision-making step during the handoff of the spectrum is imperative only if a changing policy is required. In this research work, Artificial Neural Networks (ANNs), Logistic Regression and SupportVector Machine (SVM) are proposed and implemented for a seamless handoff in CRN. From the experimental verifications, it is observed that the training accuracy is 97.9% and 97.6% for ANN and SVM, respectively. But during the actual phase, SVM to a certain extent performed better. This is due to the convergence nature of SVM on global minima. [ABSTRACT FROM AUTHOR]

The internet of things (IoT) has become one of the most important technologies of the 21st century. The IoT environment is composed of heterogeneous IoT communication networks. These technologies are complementary and need to be integrated to meet the requirements of different types of IoT applications that require the mobility of the IoT device under different IoT communication networks. In this paper, the vertical handover decision method is considered to select the appropriate network among different IoT technologies. So, IoT devices, equipped with several radio technologies, can select the most suitable network based on several criteria like quality of service (QoS), cost, power, and security. In this work, a multi-attribute decision-making algorithm (MADM) based on techniques for order preference by similarity to an ideal solution (TOPSIS) that uses chi-square distance instead of Euclidean distance is proposed. The network reputation is added to reduce the average number of handoffs. The proposed algorithm was implemented to select the best technology depending on the requirements of the different IoT traffic classes. The obtained results showed that our proposition outperforms the traditional MADM algorithms. [ABSTRACT FROM AUTHOR]

Visible light communication (VLC) has the advantages of rich spectrum resources, endogenous safety and anti-electromagnetic interference, so the application of VLC to the Industrial Internet of Things is one of its current development directions. Due to the limited coverage of light emitting diodes (LEDs), dense placement is often required in industrial manufacturing scenarios. However, mobile users will face frequent handover between these LEDs, and reliable reception of signals on mobile terminals requires receivers with a large detection area. In this paper, we used a cubic receiver to increase the detection area, which is more conducive to signal reception than a single photo-detector plane receiver. Then we studied the handover scheme for a cubic receiver to ensure the performance of the communication link. We also rotated the receiver to further improve signal quality and obtain the optimal rotation angles using a genetic algorithm with low complexity. The results show that a cubic receiver has a better received signal quality than a plane receiver, and rotation can enhance the signal quality more. In addition, it can be seen that the handover for the cubic receiver depends not only on the distance, but also on its structure, angle and position. Considering these factors jointly when performing a handover, users can connect to LEDs, which provide the best quality of service, and system communication performance can be improved. [ABSTRACT FROM AUTHOR]

While seemingly simple, handover requires joint coordinate efforts from both partners, commonly in dynamic collaborative scenarios. Practically, humans are able to adapt and react to their partner's movement to ensure seamless interaction against perturbations or interruptions. However, literature on robotic handover usually considers straightforward scenarios. We propose an online trajectory generation method based on Dynamic Movement Primitives to enable reactive robot behavior in perturbed scenarios. Thus, the robot is able to adapt to human motion (stopping should the handover be interrupted while persisting through minor disturbances on the partner's trajectory). Qualitative analysis is conducted to demonstrate the capability of the proposed controller with different parameter settings and against a non-reactive implementation. This analysis shows that controllers with reactive parameter settings produce robot trajectories that can be deemed as more coordinated under perturbation. Additionally, a randomized trial with participants is conducted to validate the approach by assessing the subject perception through a questionnaire while measuring task completion and robot idle time. Our method has been shown to significantly increase the subjective perception of the interaction with no statistically significant deterioration in task performance metrics under one of the two sets of parameters analyzed. This paper represents a first step towards the introduction of reactive controllers in handover tasks that explicitly consider perturbations and interruptions. [ABSTRACT FROM AUTHOR]

In this work, we propose a novel framework for generalizing a desired trajectory pattern, encoded using Dynamic Movement Primitives (DMP), subject to kinematic constraints. DMP have been extensively used in robotics for encoding and reproducing kinematic behaviours, thanks to their generalization, stability and robustness properties. However, incorporating kinematic constraints has not yet been fully addressed. To this end, we design an optimization framework, based on the DMP formulation from our previous work, for generalizing trajectory patterns, encoded with DMP subject to kinematic constraints, considering also time-varying target and time duration, via-point and obstacle constraints. Simulations highlight these properties and comparisons are drawn with other approaches for enforcing constraints on DMP. The usefulness and applicability of the proposed framework is showcased in experimental scenarios, including a handover, where the target and time duration vary, and placing scenarios, where obstacles are dynamically introduced in the scene. [ABSTRACT FROM AUTHOR]