Showing papers on "Handover published in 2019"

A Tutorial on Beam Management for 3GPP NR at mmWave Frequencies

Abstract: The millimeter wave (mmWave) frequencies offer the availability of huge bandwidths to provide unprecedented data rates to next-generation cellular mobile terminals. However, mmWave links are highly susceptible to rapid channel variations and suffer from severe free-space pathloss and atmospheric absorption. To address these challenges, the base stations and the mobile terminals will use highly directional antennas to achieve sufficient link budget in wide area networks. The consequence is the need for precise alignment of the transmitter and the receiver beams, an operation which may increase the latency of establishing a link, and has important implications for control layer procedures, such as initial access, handover and beam tracking. This tutorial provides an overview of recently proposed measurement techniques for beam and mobility management in mmWave cellular networks, and gives insights into the design of accurate, reactive and robust control schemes suitable for a 3GPP NR (NR) cellular network. We will illustrate that the best strategy depends on the specific environment in which the nodes are deployed, and give guidelines to inform the optimal choice as a function of the system parameters.

A Survey on Handover Management: From LTE to NR

Abstract: To satisfy the high data demands in future cellular networks, an ultra-densification approach is introduced to shrink the coverage of base station (BS) and improve the frequency reuse. The gain in capacity is expected but at the expense of increased interference, frequent handovers (HOs), increased HO failure (HOF) rates, increased HO delays, increase in ping pong rate, high energy consumption, increased overheads due to frequent HO, high packet losses and bad user experience mostly in high-speed user equipment (UE) scenarios. This paper presents the general concepts of radio access mobility in cellular networks with possible challenges and current research focus. In this article, we provide an overview of HO management in long-term evolution (LTE) and 5G new radio (NR) to highlight the main differences in basic HO scenarios. A detailed literature survey on radio access mobility in LTE, heterogeneous networks (HetNets) and NR is provided. In addition, this paper suggests HO management challenges and enhancing techniques with a discussion on the key points that need to be considered in formulating an efficient HO scheme.

Efficient Live Migration of Edge Services Leveraging Container Layered Storage

Abstract: Mobile users across edge networks require seamless migration of offloading services. Edge computing platforms must smoothly support these service transfers and keep pace with user movements around the network. However, live migration of offloading services in the wide area network poses significant service handoff challenges in the edge computing environment. In this paper, we propose an edge computing platform architecture which supports seamless migration of offloading services while also keeping the moving mobile user “in service” with its nearest edge server. We identify a critical problem in the state-of-the-art tool for Docker container migration. Based on our systematic study of the Docker container storage system, we propose to leverage the layered nature of the storage system to reduce file system synchronization overhead, without dependence on the distributed file system. In contrast to the state-of-the-art service handoff method in the edge environment, our system yields a 80 percent (56 percent) reduction in handoff time under 5 Mbps (20 Mbps) network bandwidth conditions.

Machine Learning-Based Handovers for Sub-6 GHz and mmWave Integrated Vehicular Networks

Abstract: The integration of sub-6 GHz and millimeter wave (mmWave) bands has a great potential to enable both reliable coverage and high data rate in future vehicular networks. Nevertheless, during mmWave vehicle-to-infrastructure (V2I) handovers, the coverage blindness of directional beams makes it a significant challenge to discover target mmWave remote radio units (mmW-RRUs) whose active beams may radiate somewhere that the handover vehicles are not in. Besides, fast and soft handovers are also urgently needed in vehicular networks. Based on these observations, to solve the target discovery problem, we utilize channel state information (CSI) of sub-6 GHz bands and Kernel-based machine learning (ML) algorithms to predict vehicles’ positions and then use them to pre-activate target mmW-RRUs. Considering that the regular movement of vehicles on almost linearly paved roads with finite corner turns will generate some regularity in handovers, to accelerate handovers, we propose to use historical handover data and $K$ -nearest neighbor (KNN) ML algorithms to predict handover decisions without involving time-consuming target selection and beam training processes. To achieve soft handovers, we propose to employ vehicle-to-vehicle (V2V) connections to forward data for V2I links. The theoretical and simulation results are provided to validate the feasibility of the proposed schemes.

Blockchain-enabled Authentication Handover with Efficient Privacy Protection in SDN-based 5G Networks

Abstract: 5G mobile networks provide additional benefits in terms of lower latency, higher data rates, and more coverage, in comparison to 4G networks, and they are also coming close to standardization. For example, 5G has a new level of data transfer and processing speed that assures users are not disconnected when they move from one cell to another; thus, supporting faster connection. However, it comes with its own technical challenges relating to resource management, authentication handover and user privacy protection. In 5G, the frequent displacement of the users among the cells as a result of repeated authentication handovers often lead to a delay, contradicting the 5G objectives. In this paper, we propose a new authentication approach that utilizes blockchain and software defined networking (SDN) techniques to remove the re-authentication in repeated handover among heterogeneous cells. The proposed approach is designed to assure the low delay, appropriate for the 5G network in which users can be replaced with the least delay among heterogeneous cells using their public and private keys provided by the devised blockchain component while protecting their privacy. In our comparison between Proof-of-Work (POW)-based and network-based models, the delay of our authentication handover was shown to be less than 1ms. Also, our approach demonstrated less signaling overhead and energy consumption compared to peer models.

Handover Skipping for LiFi

Abstract: This paper studies handover skipping, which enables handovers between two non-adjacent access points (APs), in light fidelity (LiFi) networks. LiFi is an emerging wireless communication technology, which operates in a way similar to wireless fidelity (WiFi) but uses light waves as a medium. Compared with WiFi, LiFi has a relatively shorter range with a single AP. This could possibly cause more frequent handovers, and thus, handover skipping techniques are required. Conventional handover skipping methods rely on information about the user's trajectory, which is not ready to use at the AP. In this paper, a novel handover skipping scheme based on the reference signal received power (RSRP) is proposed. The new approach combines the value of RSRP and its rate of change to determine the handover target. Since RSRP is already used in the current handover schemes, the proposed method does not require additional feedback. The results show that compared with the standard handover scheme and the conventional handover skipping method, the proposed method can reduce handover rate by up to 29% and 17% and improve throughput by up to 66% and 26%, respectively.

Handover Challenges for Cellular-Connected Drones

Abstract: We report and discuss cell selection and handover measurements for an aerial drone connected to an LTE-A network in a suburban environment. Our experiments show how the handover frequency increases with increasing flight altitude: A drone flying at a typical height of 150 meters is expected to experience five cell changes per minute compared to only one change for ground users moving at the same speed. This behavior can be explained by the differences between ground and aerial devices in terms of cell selection. It is concluded that revised handover techniques and the consideration of drones in the planning and operation of 4G and 5G radio access networks are required.

Frequent-Handover Mitigation in Ultra-Dense Heterogeneous Networks

Abstract: In a heterogeneous network (HetNet) with ultra-dense small-cell deployment, fast-moving users may experience frequent handovers between small cells owing to the small coverage areas of those cells. Moreover, due to shadowing and channel fading, static or slow-moving users can also experience frequent handovers, called ping-pongs. Such redundant handovers are unacceptable, and can cause packet losses or packet delays leading to a poor user experience. To solve these unwanted handover problems, we propose a frequent handover mitigation algorithm for ultra-dense HetNets. Based on mobility behavior, the proposed algorithm categorizes frequent handover-experience users as either fast-moving or ping-pong users. Fast-moving users are then handed over to the macro layer, and ping-pong users are managed by adjustment of handover parameters. However, if ping-pongs cannot be avoided through handover-parameter adjustment, ping-pong users are handed over to the macro layer as well. Simulation results show that the proposed algorithm can reduce 79.56% of the overall handovers, and increase network throughput by 10.82%.

A Secure and Efficient Access and Handover Authentication Protocol for Internet of Things in Space Information Networks

Abstract: Space information network (SIN) makes it possible for any object to be connected to the Internet anywhere, even in the areas with extreme conditions, where a cellular network is not easy to deploy. Access authentication is the key to secure users’ access control in SIN, mainly to prevent illegal adversaries from getting access to SIN services. However, the highly complicated communication environment of SIN (e.g., exposed links, higher signal delay, etc.) poses a challenging issue in the design of a secure and efficient authentication scheme. Although some authentication schemes have been proposed for SIN, they are unsuitable for Internet of Things (IoT) in SIN due to the high signaling overhead and insufficient security properties. Therefore, in this paper, we design a provably secure and efficient authentication protocol, along with an efficient handover mechanism, for IoT in SIN. In our design, we introduce a new authentication system model, where the satellites are given the ability to authenticate users to avoid the online involvement of the network control center (NCC) when authenticating users, thereby reducing long authentication delay and avoiding a single point of bottleneck in NCC. Furthermore, the support of batch verification in our design can significantly enhance handover efficiency when a group of users switch to another satellite. Our further analysis shows that our scheme is secure against various attacks and can meet a variety of security requirements. In addition, performance evaluation shows the superiority of our scheme on both delay and handover efficiency compared with existing schemes.

A Satellite Handover Strategy Based on the Potential Game in LEO Satellite Networks

Abstract: In a low earth orbit (LEO) satellite network, handover management across satellite spot beams needs to be addressed to decrease handover times while using network resources efficiently since the speed of LEO satellites is much higher than that of mobile nodes. In this paper, we propose a novel satellite handover strategy based on the potential game for mobile terminals in a LEO satellite communication network. To continue communication with the counterpart, the user has to switch among the covered LEO satellites. In a software-defined satellite network (SDSN) architecture, the satellite handover can be viewed as a bipartite graph. To balance the satellite network workload, we propose a terminal random-access algorithm based on the target of userspace maximization. The simulated handover conducted on a typical LEO satellite network, Iridium, corroborates the effectiveness of the proposed handover strategy.

Service Migration in Fog Computing Enabled Cellular Networks to Support Real-Time Vehicular Communications

Abstract: Driven by the increasing number of connected vehicles and related services, powerful communication and computation capabilities are needed for vehicular communications, especially for real-time and safety-related applications. A cellular network consists of radio access technologies, including the current long-term evolution (LTE), the LTE advanced, and the forthcoming 5th generation mobile communication systems. It covers large areas and has the ability to provide high data rate and low latency communication services to mobile users. It is considered the most promising access technology to support real-time vehicular communications. Meanwhile, fog is an emerging architecture for computing, storage, and networking, in which fog nodes can be deployed at base stations to deliver cloud services close to vehicular users. In fog computing-enabled cellular networks, mobility is one of the most critical challenges for vehicular communications to maintain the service continuity and to satisfy the stringent service requirements, especially when the computing and storage resources are limited at the fog nodes. Service migration, relocating services from one fog server to another in a dynamic manner, has been proposed as an effective solution to the mobility problem. To support service migration, both computation and communication techniques need to be considered. Given the importance of protocol design to support the mobility of the vehicles and maintain high network performance, in this paper, we investigate the service migration in the fog computing-enabled cellular networks. We propose a quality-of-service aware scheme based on the existing handover procedures to support the real-time vehicular services. A case study based on a realistic vehicle mobility pattern for Luxembourg scenario is carried out, where the proposed scheme, as well as the benchmarks, are compared by analyzing latency and reliability as well as migration cost.

Network Selection Algorithm for Multiservice Multimode Terminals in Heterogeneous Wireless Networks

Abstract: The rapid popularization of multimode terminals that simultaneously run multiple services (such as browsing web pages during a video session) has brought a decent amount of attention to the network selection problem of multimode terminals. However, most network selection algorithms proposed for vertical handoff are only suitable for terminals running a single service. This paper proposes a network selection algorithm for multiservice multimode terminals in heterogeneous wireless networks. The algorithm considers user preferences, network attributes, and service characteristics. Entropy and fuzzy analytic hierarchy process (FAHP) are used to calculate the objective weights of the network attributes and the weights determined by the service characteristics, respectively. The comprehensive weights of network attributes are obtained by combining the user preferences and service priority. At the same time, different utility functions are used to calculate the utility values of the network attributes for multiservice. Finally, the simple additive weighting (SAW) method is used to synthesize the utility values and the comprehensives weights, while the most appropriate network is selected by a technique for order preference by similarity to an ideal solution (TOPSIS) and a threshold. The simulation results show that the proposed algorithm can accurately select the most appropriate network by considering different factors. Compared to the existing two MMT network selection algorithms, it can reduce the number of vertical handovers and obtain better user experience while satisfying user’s preferences and service’s requirements, thus solving the multiservice multimode terminals network selection problem.

Radio access network node, radio terminal, core network node, and method therefor

Abstract: A target RAN node (3) is configured to: receive, directly from a core network (5), core network context information about a handover of a radio terminal (1) from a first network to the second network; and control communication of the radio terminal (1) based on the core network context information. The target RAN node (3) is further configured to transfer a handover signaling message to a source RAN node on a direct interface (101) in response to receiving the core network context information. The core network context information includes at least one of flow information, slice information, and security-related information. It is thus possible, for example, to provide an inter-RAT handover procedure involving transfer of handover signaling messages on a direct inter-base-station interface.

Advanced Handover Self-optimization Approach for 4G/5G HetNets Using Weighted Fuzzy Logic Control

Abstract: The future fifth generation (5G) wireless communications support the ultra-dense networks where deployments of a large number of small cells coexist with current 4G networks. However, the dense small cell deployment is facing a technical challenge in mobility management due to the increased number of handovers (HOs), especially in heterogeneous networks (HetNets). The increasing probability of HOs may cause HO failure (HOF) or HO ping-pong (HOPP) which degrades the system performance. To solve this problem, we propose a weighted fuzzy self-optimization (WFSO) approach for the optimization of the handover control parameters (HCPs). In this approach, the HO decision relies on three considered attributes: signal-to-interference-plus-noise ratio, traffic load of serving and target base station, and user equipment’s velocity. The self-optimized HCPs, namely the HO margin and time-to-trigger are adjusted according to the current status of these attributes to improve the HO performance. Simulation results indicate that the proposed WFSO approach significantly lowers the rates of HOPP, radio link failure and HOF in comparison with the other algorithms found in the literature.

SDN-Based Handover Authentication Scheme for Mobile Edge Computing in Cyber-Physical Systems

Abstract: Mobile edge computing (MEC) in cyber-physical systems (CPSs) with massive resource-constrained edge computing node (ECN) faces new challenges in security provisioning. The traditional centralized security authentication schemes with low performance are no longer applied for MEC in CPS. Due to the mobility of ECN, it is extraordinarily practical for ECN to establish a security association with another AP once leaving the service area of its current AP. In this paper, we represent the related research and propose a novel and efficient software-defined networking (SDN)-based handover authentication scheme for MEC in CPS (SHAS). An authentication handover module (AHM) in the SDN controller is applied for key distribution and authentication management. Before ECN handovers, the AHM distributes a key to the current serving AP for ECN further handover. Whenever a handover happens, target AP requests the AHM for the one-time session key (OSK) to authenticate the ECN. The target AP and ECN can proceed with the 3-way handshake protocol by the OSK to achieve mutual authentication and secret key confidentiality. Using the logical derivation of Burrows, Abadi, and Needham and formal verification by automated validation of Internet security protocols and applications (AVISPAs), proposed SHAS scheme can get mutual authentication and secret key confidentiality with a strong anti-attack ability. The simulation results show that the SHAS scheme has the characteristics of lower computational delay and less communication resources. Finally, the practical demonstration of our scheme is done using the widely accepted NS-3 simulation.

A Hybrid Unicast-Multicast Network Selection for Video Deliveries in Dense Heterogeneous Network Environments

Abstract: Resource management in emerging dense heterogeneous network environments (DenseNets) is a challenging issue. The employment of multicast transmissions in this scenario has potential to address the problems. On one hand, the large number of smart user mobile devices and user expectations for high-quality rich media services has determined a growing demand for network resources; in DenseNets, mobile users have to make the choice in terms of the network to connect to, in order to balance energy saving and delivery performance. On the other hand, the proliferation of user accesses to the existing and future network infrastructure will bring along with it the operators need for optimizing the radio resource usage. This paper proposes a hybrid unicast-multicast utility-based network selection algorithm (HUMANS), which offers the additional option of selecting multicast transmissions in the network selection process during video delivery. By serving users with good channel conditions via unicast transmissions and users with poor channel quality conditions via multicast, HUMANS allows outperforming other solutions in terms of outage percentage and average quality of transmission, in both low- and high-density scenarios. Most importantly, at the same time it guarantees operators a more efficient resource utilization.

Mobility Management for Intro/Inter Domain Handover in Software-Defined Networks

Abstract: To provide satisfactory Quality of Service (QoS) on the move, efficient mobility management is indispensable to provide mobile users with seamless and ubiquitous wireless connectivity. However, both the conventional centralized mobility architecture and the upcoming distributed mobility management face fundamental challenges such as sub-optimal routing, scalability, and so on. The emerging software-defined networking (SDN) architecture can efficiently manage network operations, and accordingly provides a new direction to address the challenges in mobility management. In this paper, we propose an SDN-based Mobility Management (SDN-MM) scheme to support seamless Intro/Inter domain handover with route optimization. SDN-MM decouples mobility management and packet forwarding functions by installing route optimizing and mobility control logics in an SDN controller, but exempting it from traffic redirecting. In SDN-MM, a comprehensive set of signaling operations are designed in order to provide transparent and efficient mobility support for ongoing sessions in each handover scenario, which prevents packet loss and tunneling overhead, and accordingly provide improved QoS to mobile users. For data communications, an SDN controller in SDN-MM pre-calculates the optimal end-to-end route before a handover, and decides whether to migrate traffic to the route by balancing the performance gain and the signaling overhead, which greatly improves bandwidth resource utilization. Finally, we develop a novel analytical model to evaluate the performance of SDN-MM, including signaling overhead, handover latency, and packet delivery cost. The simulation results have been provided to demonstrate that the proposed SDN-MM can greatly improve handover performance and maintain high resource utilization efficiency as well.

Dynamic Mobility Load Balancing for 5G Small-Cell Networks Based on Utility Functions

Abstract: Deployment of small cells was introduced to support high data rate services and expand macro cell coverage for the envisioned 5G networks. A small cell network, which has a smaller size, along with the user equipment (UE) mobility, frequently undergoes unbalanced load status. Consequently, the network performance is affected in terms of throughput, increasing handover failure rate, and possibly higher link failure rate. Hence, load balancing has become an important part of recent researches on small cell networks. Mobility Load Balancing (MLB) involves load transfer from an overloaded small cell to under-loaded neighbouring small cells for the more load-balanced network. This transfer is performed by adjusting the handover parameters of the UEs according to the load situations of the small cells in the vicinity. However, inaccurate adjustment of parameters may lead to inefficient usage of network resources or degrade the Quality of Service (QoS). In this paper, we introduce a Utility-based Mobility Load Balancing algorithm (UMLB) and a new term named load balancing efficiency factor (LBEF). The UMLB algorithm considers the operator utility and the user utility for the MLB-based handover process. While LBEF is proposed to order the overloaded cells properly for the MLB algorithm operation. The simulation results show that the UMLB minimizes standard deviation with a higher average-UE data rate when compared to existing load balancing algorithms. Therefore, a well-balanced network is achieved.

A Mobility Management Architecture for Seamless Delivery of 5G-IoT Services

Abstract: Mobile Edge Computing (MEC) and Network Slicing techniques have a potential to augment 5G-IoT network services. Telecommunication operators use a diverse set of radio access technologies to provide services for users. Mobility management is one such service that needs attention for new 5G deployments. The QoS requirements in 5G networks are user specific. Network slicing along with MEC has been promoted as a key enabler for such on-demand service schemes. This paper focuses on radio resource access across heterogeneous networks for mobile roaming users. A unified service architecture is proposed enabling seamless handover between a 5G (New Generation Core) service and a 4G (Evolved Packet Core) service via the network slicing paradigm. An identifier-locator (I-L) concept that allows active source-IP sessions is used to handle the seamless hand-over. Signaling costs, service disruptions and other resource reservation requirements are considered in the evaluation to assure that profit for mobile edge operators is achieved. Simulation experiments are considered to provide performance comparisons against the state-of-the-art Distributed Mobility Management Protocol (DMM).

Artificial Intelligence-Based Handoff Management for Dense WLANs: A Deep Reinforcement Learning Approach

Abstract: So far, the handoff management involved in the wireless local area network (WLAN) has mainly fallen into the handoff mechanism and the decision algorithm. The traditional handoff mechanism generates noticeable delays during the handoff process, resulting in discontinuity of service, which is more evident in dense WLANs. Inspired by software-defined networking (SDN), prior works put forward many seamless handoff mechanisms to ensure service continuity. With respect to the handoff decision algorithm, when to trigger handoff and which access point to reconnect to, however, are still tricky problems. In this paper, we first design a self-learning architecture applicable to the SDN-based WLAN frameworks. Along with it, we propose DCRQN, a novel handoff management scheme based on deep reinforcement learning, specifically deep $Q$ -network. The proposed scheme enables the network to learn from actual users’ behaviors and network status from scratch, adapting its learning in time-varying dense WLANs. Due to the temporal correlation property, the handoff decision is modeled as the Markov decision process (MDP). In the modeled MDP, the proposed scheme depends on the real-time network statistics at the time of decisions. Moreover, the convolutional neural network and the recurrent neural network are leveraged to extract fine-grained discriminative features. The numerical results through simulation demonstrate that DCRQN can effectively improve the data rate during the handoff process, outperforming the traditional handoff scheme.

Deep Learning-Based Relay Selection In D2D Millimeter Wave Communications

Abstract: This paper proposed a novel deep learning-based relay selection scheme in millimeter wave (mmWave) Device-to-Device (D2D) communication underlying the fifth generation (5G) cellular networks. Relay selection seems to be a promising solution to extend the coverage and solve the blocking problem of mmWave direct communication. In the case of direct path blocking, the base station (BS)/user equipment (UE) has several candidate devices to be selected as a relay. Despite that, conventional scheme when the direct path is blocked, the direct communication link is handover from mmWave to a lower frequency band using a fast session transfer (FST) technique. Such a blocking problem can be solved multi-hop communications by relaying data based on select another device as a relay. Motivated by the importance of selecting the optimal relay which increases reliable connectivity in mmWave communication and expansion of coverage. The proposed deep learning model is developed to overcome the challenges of selected the optimal relay based with low complexity and high efficiency. The proposed scheme considers a deep learning model learns how to predict the best relay for relaying the data in high-reliability communication. The in-depth learning approach is recommended due to its capability in constructing an intelligent model that can take successful decisions and make precise predictions. Simulation results show that the proposed relay selection algorithm outperforms the conventional relay selection in D2D technique in the spectral efficiency and the energy efficiency

An Experimental Evaluation of LTE-A Throughput for Drones

Abstract: This work presents an experimental performance study on the wireless communication of a quadrocopter connected to an LTE-Advanced network. Measurements of TCP traffic analyze how the received power level, signal-to-interference ratio, and throughput depend on the flight height. An average throughput of 20 Mb/s in the downlink and 40 Mb/s in the uplink is achieved at 150 m. We also show how the number of line-of-sight links to base stations rises with height and leads to an increased handover rate.

Road to 5G Reduced-Latency: A Software Defined Handover Model for eMBB Services

Abstract: Recently, handover execution has still been damaging 5G latency requirement due to having three states in virtual evolved packet core (vEPC). Here, the desired end-to-end delay (e2eDelay) should be less than 4 m/sec without any mobility interruption on an enhanced mobile broadband (eMBB) service of vEPC. To handle this requirement, we need to focus on the Markov model of e2eDelay. It can be measured by the concatenation of edge and core delays in the downlink eMBB service from a remote source to a mobile user. Here, edge delay is directly affected by the core network via a decreased packet delivery ratio to edge under huge-traffic intensity background. Therefore, target eNodeB decision by considering only edge network can be misleading. To overcome this, we jointly consider edge and core delays, which are differently affected by each handover states: 1) preparation, 2) execution, and 3) completion. The joint consideration of edge and core can be only handled with a novel cost-effective software-defined ultra-dense network (SDUN) framework by dynamically removing state 2). It triggers handover via network-centric monitoring; and then, it predetermines optimal TeNB with a proposed optimization formula and shortest core path according to traffic intensities of OpenFlow switches. Here, SDUN controller is cost-efficient by the proposed parallel runnable algorithms: parallel edge delay optimization and parallel shortest delay path. In the performance evaluation SDUN is first emulated for a specific eMBB traffic, i.e., QUIC based HTTP/3 video content traffic with 1080p resolution, and second simulated in system-level on MATLAB. It meets 5G requirements as follows: SDUN decreases core delay 7.16 m/sec per a UE under huge-traffic intensity and keeps edge delay under 5G requirement with 20% more delivery ratio than conventional one. Moreover, the cost of SDUN controller is analyzed as O(k4log2(k)) and the cost efficiency is observed as the 50% increased scalability level with the acceptable 8% extra virtual memory usage.

Handover Probability Analysis of Anchor-Based Multi-Connectivity in 5G User-Centric Network

Abstract: In order to reduce the handover cost due to network densification, this letter proposes an anchor-based multi-connectivity (MC) architecture and derives compact expressions of handover probabilities (HOPs) through stochastic geometry analysis in user-centric network (UCN). For MC a given user connects with multiple access points (APs), and the best one is chosen as a handover anchor to provide control-plane, which reduces the handover rate. Moreover, HOPs are quantified for a typical user moving with a random direction and a fixed speed in an irregular UCN with APs modeled as a Poisson point process. The simulation and analytical results show that the HOP in control-plane achieves a decrease of more than 40% over the traditional handover scheme in the LTE system.

Location-Based Discovery and Vertical Handover in Heterogeneous Low-Power Wide-Area Networks

Abstract: Low-power wide-area network (LPWAN) multi-radio access technology (RAT) devices promise enabling Internet of Things (IoT) use-cases that simultaneously require high coverage and data rates, and low energy consumption. For such devices, active probing is usually used for discovering if communication between a mobile terminal (MT) and a base station (BS) or a handover of the MT across LPWAN technologies should be initiated. Because of continuous probing, this procedure increases signaling overhead and energy consumption of the MT. Assuming that the location information of the MT is required for enabling an IoT use-case, this information can potentially also be used for enhancing the discovery and vertical handover procedures in heterogeneous LPWANs. Hence, we propose a location-based mechanism for making discovery and handover decisions in outdoor LPWANs. We do that under the assumption that the location of the MT can be estimated with a certain level of localization errors, while the perfectly accurate location information of the BSs are known to the MT. The mechanism grounds the decisions on the expected SNR between the MT and the BS, which removes the need for continuous probing. If the location information of the MT can be estimated with GPS-like accuracy, we demonstrate that the mechanism can achieve more than 90% correct discovery decisions. We also show that the mechanism is highly accurate in determining if a handover between technologies should be initiated. For an order of magnitude less accurate location information (e.g., for SigFox-based fingerprinting), we show that the mechanism can still make reasonable discovery decisions.

Using machine learning for handover optimization in vehicular fog computing

Abstract: Smart mobility management would be an important prerequisite for future fog computing systems. In this research, we propose a learning-based handover optimization for the Internet of Vehicles that would assist the smooth transition of device connections and offloaded tasks between fog nodes. To accomplish this, we make use of machine learning algorithms to learn from vehicle interactions with fog nodes. Our approach uses a three-layer feed-forward neural network to predict the correct fog node at a given location and time with 99.2 % accuracy on a test set. We also implement a dual stacked recurrent neural network (RNN) with long short-term memory (LSTM) cells capable of learning the latency, or cost, associated with these service requests. We create a simulation in JAMScript using a dataset of real-world vehicle movements to create a dataset to train these networks. We further propose the use of this predictive system in a smarter request routing mechanism to minimize the service interruption during handovers between fog nodes and to anticipate areas of low coverage through a series of experiments and test the models' performance on a test set.

Intelligent Process of Spectrum Handoff/Mobility in Cognitive Radio Networks

Abstract: Cognitive radio is an innovative technology in the field of wireless communication systems, aimed at significantly improving the use of the radio spectrum while allowing secondary users to access the spectral band opportunistically. Spectrum management mechanism ensures the transmission of data by controlling the efficiency of operation between the primary and secondary networks. The main task of spectrum management is to ensure that secondary users benefit from the spectrum without interfering with primary users. This paper deals with some of the important characteristics of spectrum mobility in the cognitive radio networks. The new management approaches of the mobility and the connection are designed to reduce the latency and loss of information during spectrum handoff, a list of channel safeguard is maintained in this effect, but the maintenance and update are a challenge. In this paper, we describe the reasons and mechanisms of spectrum handoff. Protocols have been developed to illustrate this handoff mechanism. We also make a comparison between the different methods of spectrum handoff. The simulation results obtained confirm that the protocols developed and the proposed method performed better than the pure reactive handoff method.