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Mobile data traffic is currently experiencing a significant and continuous increase, with no signs of decrease. This trend can impact the use of 5G mobile networks, which require high speeds and excellent Quality of Service (QoS). Therefore, service providers are expected to meet the growing demands of users and prevent connection or call failures. To address the issue as a contribution, this study proposed the use of traffic offloading integrated with vertical handover algorithm by transferring data flow from cellular to WiFi network. This study aimed to simulate algorithm under four different scenarios, namely distance, bandwidth, transmit power, and system loss. These scenarios were analyzed with respect to the influence of mobility and number of nodes, considering various QoS parameters, namely Received Signal Strength Indicator (RSSI), data rate, power consumption, throughput, and end-to-end delay rate. The simulation results showed an improvement in QoS, particularly in the RSSI parameter. The four scenarios showed that the RSSI value remained consistent despite mobility and number of nodes caused by multiple iterations of offloading between the 5G and WiFi networks. In terms of data rate parameter, the scenarios consistently showed that algorithm prioritized the highest data rate between the networks, even with user mobility conditions. It also consistently used the network with the lowest value as regards power consumption, while prioritizing the highest value in throughput. In terms of the end-to-end delay rate parameter, algorithm used the smallest value between the 5G and the WiFi networks. [ABSTRACT FROM AUTHOR]

The vertical handover policy of space-air-ground integrated cyber-physical systems based on deep reinforcement learning was studied, in which the challenges of complicated network model and difficulties in acquiring prior knowledge for network topology and model were addressed. By jointly taking the system stability, handover cost and network-using cost into account, the vertical handover policy problem was modeled as a constraint Markov decision process (CMDP), and a sufficient condition to ensure the existence of a feasible solution was derived.Furthermore, a constraint-proximal policy optimization (CPPO) algorithm was proposed to solve the CMDP, and also the distributed learning scheme at base station sides was introduced to accelerate the speed of converging. Simulation results verify the validation and superiority of the proposed vertical handover policy as compared with the baselines.

Heterogeneous wireless networks (HWNs) are essential in modern communication systems, as they seamlessly integrate various radio access technologies (RATs). In this context, network selection (NS) emerges as a pivotal element, responsible for selecting the most appropriate network for user equipment (UE) during transitions between RATs. Conventional NS mechanisms, such as the multi-attribute decision-making (MADM) methods, are commonly employed for their fast ranking of RATs, real-time support, and flexibility. However, they suffer from three primary limitations; the rank reversal problem (RRP), overlooking specific user/service requirements while favouring the highest-ranking RAT, and the associated frequent handovers. To address these limitations, in this paper, we first employ one of the most recent and effective MADM approaches, known as the measurement of alternatives and ranking according to the compromise solution (MARCOS), to model and solve the NS problem (MARCOS-NS) for the first time in the literature. We then propose novel sigmoid utility functions to assess the quality of each RAT attribute within the HWNs environment, taking into account user/application requirements. Further, we enhance MARCOS-NS by replacing its original normalization technique with the proposed sigmoid utility functions to overcome its limitation, creating a new MADM approach called MARCOS-Utility. Our results demonstrate the superiority of MARCOS-Utility over conventional MADM approaches as it completely eliminates the RRP, reduces vertical handover occurrences by an average of 33.1%, and achieves a balance between data rate and packet loss ratio for the streaming traffic class.

The integration of Unmanned Aerial Vehicles (UAVs) into future 6G networks will open new possibilities for applications ranging from surveillance to communication infrastructure maintenance, precision agriculture, and surveying. However, ensuring uninterrupted connectivity for UAVs operating in remote or dynamic environments remains a significant challenge. This paper presents a novel approach to achieving seamless handover for UAVs when transitioning between terrestrial and satellite communication networks. The proposed method in this paper, leverages graph theory and develop a decision-making algorithm to optimise handover decisions, minimizing latency, improving performance, and reducing service disruption. It establishes a comprehensive graph model that represents the dynamic topology of available network nodes, including terrestrial base stations and low earth orbit (LEO) satellites, which adapts in real-time to changes in UAV position and network conditions. The approach incorporates a decision-making algorithm that considers several factors, such as received signal strength (RSS), signal-to-noise ratio (SNR), and elevation angle, to determine the optimal time and location for a handover between terrestrial base stations and satellite links. This ensures a seamless transition between communication links, minimizing service disruption. The performance of this method is evaluated through extensive simulations and comparison with existing solutions demonstrating significant improvements in RSS, SNR, throughput, latency, ping-pongs and enhanced overall UAV connectivity. The proposed graph method-based seamless handover solution represents a crucial advancement in enabling reliable and uninterrupted communication for UAVs operating in remote and challenging environments. By managing handovers between terrestrial and satellite networks, this research contributes to the realisation of the full potential of UAVs in emerging applications, thereby advancing the state-of-the-art in UAV technology.

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.)

To enhance the overall communication rate and capacity of mobile networks, a real-time application (RTA)-classification vertical handover (Ac-VHO) scheme is presented for indoor visible light communication (VLC) heterogeneous networks. The scheme considers user mobility, optical link instability, and the variability of real-time applications. It incorporates VLC line-of-sight (LOS) blocking and MT entry into co-channel interference (CCI) areas as triggers, while also providing differentiated delay tolerance intervals and optimized handover dwell time calculations for various RTAs, including video, audio (VoIP), and web/text. A simulation and comparative analysis demonstrate the superior performance of Ac-VHO in terms of signaling cost, and its average rate compared to other methods (hybrid application-aware VHO, dynamic time-dwelling VHO, and static time-dwelling VHO). In addition, it maintains a consistent and relatively high overall quality of user experience (QoE) for different RTA types. [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]

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]

In heterogeneous networks (HetNets), the vertical handover (VHO) is an essential process for mobile users (MUs) aiming to secure ubiquitous connectivity and maintain the highest quality of service (QoS) across various types of radio access technology (RAT), such as wireless fidelity (Wi-Fi), the global system for mobile communication (GSM), and the universal mobile telecommunications system (UMTS). In the literature, many recent VHO research works have been proposed in which a number of critical issues still arise when performing seamless vertical handover, including VHO packet loss, VHO delay, and VHO throughput. Moreover, the security aspect of triggering VHO has not been carefully considered, particularly when an MU intends to use a payment application. In this paper, we present a comprehensive performance evaluation for a new secure VHO algorithm, taking into account all the above issues, for co-located Wi-Fi and UMTS networks. The simulation results are compared with the media independent handover (MIH) IEEE 802.21 standard, which facilitates the seamless transfer of connection among heterogeneous networks. We show that the proposed algorithm outperforms the MIH standard in terms of VHO delay, VHO packet loss, and VHO throughput in providing uninterrupted connection to security-constrained applications. [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]

In millimeter-wave (mmWave) heterogeneous networks, vertical handover plays a crucial role in ensuring seamless communication for user equipment. This paper explores the concept of vertical handover from a Cartesian-plane (CP) perspective with a goal to enhancing the handover process in heterogeneous networks. The methodology involves analyzing the performance of vertical handover (VHO) scheme in millimeter-wave heterogeneous networks using a CP framework. The scheme models the user mobility patterns as obstacle-based and obstacle-free coefficients in relation to the Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) communication links. The performance metrics of number of handovers and average running time were used to demonstrate the superiority of the CP model when compared to the existing Rate based Handover (RBH) and Double Deep Reinforcement Learning (DDRL) schemes, respectively. With respect to the mm-Wave base station density, simulation results showed that the CP scheme achieved 46.87% and 9.62% handover reduction when compared to the RBH and DDRL schemes, respectively. Also, in terms of user velocity, the CP scheme obtained 84.84% and 10.28% handover reduction in comparison to the RBH and DDRL schemes, respectively. Furthermore, the CP scheme also achieved 30.22% and 38.13% reduction in average running time when compared to the existing RBH and DDRL schemes, respectively. • Cartesian-Plane. • Line-of-Sight. • Non-line-of-Sight. • Vertical handover. • User equipment communications. [ABSTRACT FROM AUTHOR]

VHOs (Vertical Handovers) have become popular research problems in real-world environments, with frequencies of access to the network increasing to millions of users. It is required to select and provide the most suitable access network for the users who enter into the network environment. This work introduces a combination of techniques namely M-ANPs (Multiple Analytic Network Processes) combined with TOPSISs (Method for Order Preference by a resemblance to ideal solutions) for choosing access networks that satisfy QoS's (Quality of Services). Generally, networks fail to ensure the successful routing between different access networks which is handled by this research work with its proposed QoS-VHP (QoS-aware vertical Handover Process). In this work initially, handover initiation is performed. After initiation, system discovery is performed to identify the nearest access network which can be reachable with minimum distance and bandwidth consumption. After picking the nearest access network services, a handover decision is achieved to select the most suitable access network which can satisfy the constraints CB's (Costs for Bytes), ABs (Available Bandwidths), Security, D (Packet Delays), J (Packet Jitters) and L (Packet Losses). This optimal selection of access networks is used to Modified TOPSIS Method to ensure a more accurate selection of suitable access networks for reliable data transmission. After the handover decision process, handover execution is performed with the concern of the transport layer which is done by using a modified Stream Control Transmission Protocol. The overall proposal was simulated on an NS2-simulator where the expected parameters like handover delay, probability of handover failure, and throughput are evaluated with the results of 0.69–0.77 s, 0.45, and 80Kbps respectively which, proved its ability to optimize protocols.

Low-Power Wide-Area Network (LPWAN) multi-Radio Access Technology (RAT) devices combine features of different low-power network technologies to flexibly manage heterogeneous requirements stemming from various Internet of Things (IoT) applications. IEEE 802.11ah is a novel technology that is envisioned to provide a “bridge” between Wi-Fi and s, thus it has been often considered as one of the supporting technologies in multi-RAT devices. In such multi- RAT scenarios, network discovery and handover procedures need to be utilized for determining the availability of a given technology and managing if the connection to the technology should be initiated. However, traditional discovery and handover procedures, such as beacon listening, have to be performed periodically and, therefore, consume substantial amount of energy, making them unsuitable for battery-powered IoT devices. To address this issue, we present a mechanism that is able to make more optimal discovery and handover decisions by leveraging the physical location information of the multi- RAT devices. We demonstrate how this approach is feasible in performing energy efficient handovers between a technology (NB-IoT) and IEEE 802.11ah based on estimated location. We do that by showing that the location-based procedure substantially reduces the energy consumption of the mobile device compared to the traditional discovery based on periodical listening for beacons, while maintaining comparable duration of the device’s association to IEEE 802.11ah. Moreover, we evaluate the energy and delay overheads caused by the localization service, showing only slight effects on the performance of the mechanism. [ABSTRACT FROM AUTHOR]

The contemporary wireless networks exhibit heterogeneity, i.e., different types of wireless networks co-exist and fulfill the user's needs. Users amongst the available networks prefer the Wi-Fi and 4G networks. Wi-Fi is a choice for homes and offices for limited coverage and high data rate. While for outdoor, 4G is a better choice due to broader coverage and reasonably better average data rates. As user mobility is high nowadays, smooth session transfer is essential amongst such heterogeneous networks to provide seamless connectivity with the best QoS. Currently, video real-time application traffic is in high demand. This paper investigates the heterogeneous /vertical handover performance for realistic traffic and terminal speeds based on the MIH framework. The MIH is IEEE 802.21 standard to maintain the service continuity amongst heterogeneous networks. The primary focus of this paper is to derive the thresholds for speeds and the link layer predictive triggers. These thresholds are helpful in the design of the algorithms to enhance the QoS and user experience. Further, to understand the limitations of the said standard for a given scenario. The packet loss ratio and handover latency are the QoS parameters. The detailed simulations are carried out in NS-2 by considering a realistic scenario of terminal speeds and application traffic (MPEG-4, H.261, and HDTV). The networks chosen for the analysis are Wi-Fi and 4G. The packet loss ratio and handover latency are considered QoS parameters. For the accuracy of results, simulation time is varied as per the user's speed. We derived predictive trigger and speed thresholds critically examined for the given application traffic. [ABSTRACT FROM AUTHOR]

In current heterogeneous network, the multi-decision attribute vertical handover algorithm is difficult to dynamically adjust the weight value of the network attributes, and thus cannot meet the user’s Quality of Service (QoS) requirements. To solve this issue, this paper aims at accessing the optimal heterogeneous wireless network and guaranteeing the user’s QoS, and proposes an adaptive vertical handover algorithm based on the fuzzy hierarchy-entropy weight method. First, according to user experience, a model of network attribute optimization is constructed by combining subjective fuzzy hierarchical weighting and objective entropy weights. Then, an adaptive mechanism is used to dynamically adjust the weight value of each network attribute according to user experience. Finally, the cost function is used to predict the state of the heterogeneous network to select the optimal wireless network. Simulation experiments verify that the proposed algorithm can effectively reduce the network switching rate, better ensuring the load balancing between heterogeneous wireless networks, and increase the endurance of mobile terminals.

In spite of several promising attributes that motivate industry players to adopt visible light communication (VLC), its strong coverage limitation is a major disincentive. A reasonable way to overcome this bottleneck in indoor environments is to capitalize on the prevailing wireless local area network (WLAN) to boost reliable mobile access. To this end, a vertical handover (VHO) scheme is required to smoothly merge VLC networks and WLANs. Thus, this article presents an adaptive VHO scheme which considers the cause of a VLC link disruption and the types of applications running in a user device (UD) to make appropriate handover decisions. The proposed hybrid application-aware VHO (HA-VHO) technique combines three approaches (immediate handover, static dwell timing and dynamic dwell timing), in order to improve the overall handover outcome. Performance comparisons with other VHO designs (immediate VHO, dwell VHO and channel adaptive dwell VHO) reveal that the HA-VHO scheme provides higher data rates in most cases, while adaptively reducing the total signaling cost of inter-network handovers. What is more, it can provide relatively high quality of experience (QoE) for real-time applications. [ABSTRACT FROM AUTHOR]

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.

Visible light communication (VLC) channel quality depends on line-of-sight (LoS) transmission, which cannot guarantee continuous transmission due to interruptions caused by blockage and user mobility. Thus, integrating VLC with radio frequency (RF) such asWireless Fidelity (WiFi), provides good quality of experience (QoE) to users. A vertical handover (VHO) scheme that optimizes both the cost of switching and dwelling time of the hybrid VLC–WiFi system is required since blockage on VLC LoS usually occurs for a short period. Hence, an automated VHO algorithm for the VLC–WiFi system based on the hidden Markov model (HMM) is developed in this article. The proposed VHO prediction scheme utilizes the channel characterization of the networks, specifically, the measured received signal strength (RSS) values at different locations. Effective RSS are extracted from the huge datasets using principal component analysis (PCA), which is adopted with HMM, and thus reducing the computational complexity of the model. In comparison with state-of-the-art VHO handover prediction methods, the proposed HMM-based VHO scheme accurately obtains the most likely next assigned access point (AP) by selecting an appropriate time window. The results show a high VHO prediction accuracy and reduced mixed absolute percentage error performance. In addition, the results indicate that the proposed algorithm improves the dwell time on a network and reduces the number of handover events as compared to the threshold-based, fuzzy-controller, and neural network VHO prediction schemes. Thus, it reduces the ping-pong effects associated with the VHO in the heterogeneous VLC–WiFi network. [ABSTRACT FROM AUTHOR]

Summary: In 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. [ABSTRACT FROM AUTHOR]

Abstract 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.

Different Radio Access Technologies (RATs) coexist in the same area has encouraged the researchers to get profit from the available networks by selecting of the best RAT at each moment of the call session to satisfy the user requirements. In this paper, we address a real-world problem which is the frequent mobility of the users in heterogeneous networks. We present in this paper a framework that allows users to select the best networks for the whole call session especially form a mobility perspective. The framework consists of several steps, starting by the path prediction which is performed using a Markov model order 2. The second step is to make the network selection on the zones of each predicted path, while in the third step; we get the best RAT’s configuration for each predicted path. Finally, we use another function to select one of the best configurations to be used for all the possible used paths. The results show that our proposal performs very well by eliminating the unnecessary vertical handover while maintaining a good Quality of Service (QoS).

In heterogeneous networks (HetNets), the vertical handover (VHO) is an essential process for mobile users (MUs) aiming to secure ubiquitous connectivity and maintain the highest quality of service (QoS) across various types of radio access technology (RAT), such as wireless fidelity (Wi-Fi), the global system for mobile communication (GSM), and the universal mobile telecommunications system (UMTS). In the literature, many recent VHO research works have been proposed in which a number of critical issues still arise when performing seamless vertical handover, including VHO packet loss, VHO delay, and VHO throughput. Moreover, the security aspect of triggering VHO has not been carefully considered, particularly when an MU intends to use a payment application. In this paper, we present a comprehensive performance evaluation for a new secure VHO algorithm, taking into account all the above issues, for co-located Wi-Fi and UMTS networks. The simulation results are compared with the media independent handover (MIH) IEEE 802.21 standard, which facilitates the seamless transfer of connection among heterogeneous networks. We show that the proposed algorithm outperforms the MIH standard in terms of VHO delay, VHO packet loss, and VHO throughput in providing uninterrupted connection to security-constrained applications.

Despite the seemingly exponential growth of mobile and wireless communication, this same technology aims to offer uninterrupted access to different wireless systems like Radio Communication, Bluetooth, and Wi-Fi to achieve better network connection which in turn gives the best quality of service (QoS). Many analysts have established many handover decision systems (HDS) to enable assured continuous mobility between various radio access technologies. Unbroken mobility is one of the most significant problems considered in wireless communication networks. Each application needs a distinct QoS, so the network choice may shift appropriately. To achieve this objective and to choose the finest networks, it is important to select a best decision making algorithm that chooses the most effective network for every application that the user requires, dependent on QoS measures. Therefore, the main goal of the proposed system is to provide an enhanced vertical handover (VHO) decision making program by using a Multi-Criteria Fuzzy-Based algorithm to choose the best network. Enhanced Multi-Criteria algorithms and a Fuzzy-Based algorithm is implemented successfully for optimal network selection and also to minimize the probability of false handover. Furthermore, a double packet buffer is utilized to decrease the packet loss by 1.5% and to reduce the number of handovers up to 50% compared to the existing systems. In addition, the network setup has an optimized mobility management system to supervise the movement of the mobile nodes. [ABSTRACT FROM AUTHOR]

Copyright of Study on Optical Communications / Guangtongxin Yanjiu is the property of Study on Optical Communications Editorial Office 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.)

Heterogeneous wireless networks that are used for seamless mobility are expected to face prominent problems in future fifth generation (5G) cellular networks. Due to their proper flexibility and adaptable preparation, remote-controlled unmanned aerial vehicles (UAVs) could assist heterogeneous wireless communication. However, the key challenges of current UAV-assisted communications consist in having appropriate accessibility over wireless networks via mobile devices with an acceptable Quality of Service grounded on the users’ preferences. To this end, we propose a novel method based on cooperative game theory to select the best UAV during handover process and optimize handover among UAVs by decreasing the i) end-to-end delay, ii) handover latency, and iii) signaling overheads. Moreover, the standard design of software-defined network with media-independent handover is used as forwarding switches in order to obtain seamless mobility. Numerical results derived from the real data are provided to illustrate the effectiveness of the proposed approach in terms of number of handovers, cost, and delay. [ABSTRACT FROM AUTHOR]

Visible light communication (VLC) channel quality depends on line-of-sight (LoS) transmission, which cannot guarantee continuous transmission due to interruptions caused by blockage and user mobility. Thus, integrating VLC with radio frequency (RF) such asWireless Fidelity (WiFi), provides good quality of experience (QoE) to users. A vertical handover (VHO) scheme that optimizes both the cost of switching and dwelling time of the hybrid VLC–WiFi system is required since blockage on VLC LoS usually occurs for a short period. Hence, an automated VHO algorithm for the VLC–WiFi system based on the hidden Markov model (HMM) is developed in this article. The proposed VHO prediction scheme utilizes the channel characterization of the networks, specifically, the measured received signal strength (RSS) values at different locations. Effective RSS are extracted from the huge datasets using principal component analysis (PCA), which is adopted with HMM, and thus reducing the computational complexity of the model. In comparison with state-of-the-art VHO handover prediction methods, the proposed HMM-based VHO scheme accurately obtains the most likely next assigned access point (AP) by selecting an appropriate time window. The results show a high VHO prediction accuracy and reduced mixed absolute percentage error performance. In addition, the results indicate that the proposed algorithm improves the dwell time on a network and reduces the number of handover events as compared to the threshold-based, fuzzy-controller, and neural network VHO prediction schemes. Thus, it reduces the ping-pong effects associated with the VHO in the heterogeneous VLC–WiFi network.

In wireless heterogenous networks, mobile terminals are covered by different wireless networks with varying quality of services to ensure the delivery of different classes of services. In this paper, Particle swarm optimization (PSO) was applied to the distance to ideal alternative (DIA) technique in the framework of network selection in a heterogenous wireless network. The PSO was applied to overcome the subjectivity and bias in the weights’ assignment process used in multiple attribute decision making (MADM). The PSO was utilized to optimize the weights of the DIA method through the maximization of the absolute value of the summation of the ranking differences among candidate networks. In this regard, two different optimization functions were introduced and used to generate the optimum weights. The performance of the PSO-based handover for the DIA method was investigated in terms of ranking difference, ranking abnormalities, and network selection. The results show that the proposed PSO-based weights’ assignment technique increased the ranking difference and reduced the ranking abnormalities without degrading the network selection when compared to the conventional DIA technique. The results of this paper are expected to widen the application of the DIA method and other MADM techniques to the handover process in wireless networks and other decision-based challenges in other fields. [ABSTRACT FROM AUTHOR]