Unnecessary Handoffs Research Articles

Изучение необязательной энергопередачи в сетях WLAN: проблемы и последние достижения

Recently, the issue of unnecessary handoff in WLAN networks has been the subject of recent research efforts. WLANs are designed to provide high-speed connectivity in a limited area, similar to their wired counterparts. The IEEE 802.11 Standard has become widely adopted for wireless LANs. The handoff algorithm allows mobile nodes to switch between access points (APs) as they move between areas serviced by different APs. However, determining when to initiate a handoff poses challenges, particularly concerning unnecessary handoffs. Many researchers have investigated this issue and have proposed mechanisms to address it. Thus, this study focuses on reviewing the related works about handoff and discusses the challenges and recent advances.

Fuzzy Tree Schematic for Spectrum Handoff Reduction in Cognitive Radio Networks

Spectrum is a limited resource, so it must be used effectively. The fixed spectrum allocation method currently in operation may not sustain the growth in the network access users, which continues to increase over time. Many studies have shown that the spectrum deficiency problem can be solved with cognitive radio network (CRN) technology. CRN allows flexible spectrum utilization. Spectrum handoff is one of the fundamental prerequisites for dynamic spectrum access in cognitive radio networks. The ping-pong effect is one of the problems caused by the frequent occurrence of unnecessary handoff spectrum. So, in CRN, the right handoff decision is needed to avoid the ping-pong effect. The proposed fuzzy system carries the concept of a fuzzy tree that uses two fuzzy inference systems (FIS), which work in two stages, namely FIS-1 and FIS-2. In the early stages, the FIS-1 controls the secondary users (SU) power and prevents interference with the primary users (PU). FIS-2 is used to execute precise spectrum handoff decisions. The test results show that the amount of handoff spectrum has decreased by up to 43 % compared to other methods, which are only 60 %. This results in a decrease of 16.67% from the previous method. Thus, the ping-pong effect can be minimized with the right handoff decisions.

Multi-criteria Handoff Decision making Algorithm for Seamless Mobility in Heterogenous Wireless Networks

Wireless networks have been through many transformations to provide Quality of Service (QoS) and seamless mobility. Handoff management plays a vital role in maintaining quality of service while roaming. The focus of the paper is to develop a handoff technique for optimized handoff decision making. Multi-Criteria Decision Making (MCDM) techniques are utilized for making decision where more than one contradicting parameter are involved. Fuzzy Analytic Hierarchy Process (FAHP) is used for weight calculation and Fuzzy Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) decides the rank of available networks. The proposed technique utilizes six network parameters i.e., received signal strength, bandwidth, signal to interference & noise ratio, delay, packet loss, and bit error rate for weights calculation under different traffic classes and three decision makers i.e., network, mobile node, and user preference for optimized handoff. The results show that the proposed technique effectively classify the best available network in terms of their rank and reduces the number of unnecessary handoffs.

Comprehensive Improvement of Cardiology Inpatient Transfers: A Bed-availability Triggered Approach.

Patient transfers pose a potential risk during hospitalizations. Structured communication practices are necessary to ensure effective handoffs, but occur amidst competing priorities and constraints. We sought to design and implement a multidisciplinary process to enhance communication between pediatric cardiovascular intensive care unit and cardiology floor teams with a comprehensive approach evaluating efficiency, safety, and culture. We conducted a prospective quality improvement study to enact a bed-availability triggered bedside handoff process. The primary aim was to reduce the time between handoff and unit transfer. Secondary metrics captured the impact on safety (reported safety events, overnight transfers, bounce backs, and I-PASS utilization), efficiency (transfer latency, unnecessary patient handoffs, and cumulative time providers were engaged in handoffs), and culture (team members perceptions of satisfaction, collaboration, and handoff efficiency via survey data). Eighty-two preimplementation surveys, 26 stakeholder interviews, and 95 transfers were completed during the preintervention period. During the postintervention period, 145 handoffs were audited. We observed significant reductions in transfer latency, unnecessary handoffs, and cumulative provider handoff time. Overnight transfers decreased, and no negative impact was observed in reported safety events or bouncebacks. Survey results showed a positive impact on collaboration, efficiency, and satisfaction among team members. Developing safer handoff practices require a collaborative, structured, and stepwise approach. Advances are attainable in high-volume centers, and comprehensive measurement of change is necessary to ensure a positive impact on the overall patient and provider environment.

Enhancing Handover for 5G mmWave Mobile Networks Using Jump Markov Linear System and Deep Reinforcement Learning.

The Fifth Generation (5G) mobile networks use millimeter waves (mmWaves) to offer gigabit data rates. However, unlike microwaves, mmWave links are prone to user and topographic dynamics. They easily get blocked and end up forming irregular cell patterns for 5G. This in turn causes too early, too late, or wrong handoffs (HOs). To mitigate HO challenges, sustain connectivity, and avert unnecessary HO, we propose an HO scheme based on a jump Markov linear system (JMLS) and deep reinforcement learning (DRL). JMLS is widely known to account for abrupt changes in system dynamics. DRL likewise emerges as an artificial intelligence technique for learning highly dimensional and time-varying behaviors. We combine the two techniques to account for time-varying, abrupt, and irregular changes in mmWave link behavior by predicting likely deterioration patterns of target links. The prediction is optimized by meta training techniques that also reduce training sample size. Thus, the JMLS–DRL platform formulates intelligent and versatile HO policies for 5G. When compared to a signal and interference noise ratio (SINR) and DRL-based HO scheme, our HO scheme becomes more reliable in selecting reliable target links. In particular, our proposed scheme is able to reduce wasteful HO to less than 5% within 200 training episodes compared to the DRL-based HO scheme that needs more than 200 training episodes to get to less than 5%. It supports longer dew time between HOs and high sum rates by ably averting unnecessary HOs with almost half the HOs compared to a DRL-based HO scheme.

Research on Multi-beam Handover Invitation Technology for GEO Mobile Satellite System

Different from the terrestrial cellular system, the GEO mobile satellite system has its own characteristics, such as the extremely large beams, the long propagation delay and the diversity of the MS (Mobile Station) velocity. Based on these characteristics, a cooperative beam-cluster is constructed, and a handover invitation technology based on the coordinated multi-beam is proposed in the paper. Using the sending mechanism of handover invitation by a variable sliding window, the technology can avoid the occurrence of the phenomenon of “ping pong” handover to realize seamless handover, and make the handover quick, efficient and reliable. Simulation results show that the algorithm significantly increases the handover success rate, prevents the unnecessary handoff and has a favourable adaptability to the high velocity MS.

Mm‐Wave micro‐wave integrated Sub‐RAN for CRAN performance enhancement

Coordinated Multi-Point (CoMP) transmission in Cloud Radio Access Network (CRAN) requires a large amount of data transmission and processing within a coherence time window. Hence, CoMP transmission puts a lot of burden on the central processor and back-haul unit. Also, establishing CoMP for high-mobility users is challenging due to small coherence window and large beamforming overhead over mm-Wave transmission. This paper proposes a two-layer CRAN architecture with intelligent mm-Wave and micro-Wave allocation. A dual connectivity framework has been introduced to increase the coverage of high-mobility users. Further, it is shown that the proposed scenario reduces the load on the central processor and central back-haul. To avoid unnecessary handoffs, a mobility management algorithm is also proposed, which can provide seamless connectivity to the users irrespective of their velocity. Further, through simulation results, it is shown that the proposed network outperforms the existing CRAN framework.

Reinforcement Learning Based Vertical Handoff Decision Algorithm for Next Generation Wireless Network

Next-generation wireless network systems and technologies provide a new paradigm for achieving the fastest access to any network. But one of the significant design concerns is the support of handoff, irrespective of the services. The key objective of this work is to enable a node to make appropriate decisions for performing handoff through Reinforcement learning. The work concentrates on the handoff decision phase for choosing the best network with a minimum delay during the handoff process. The reduction in decision delay has been achieved by minimizing the number of handoffs. The environment is modeled as a Markov decision process with the aim of increasing the total anticipated reward per link. The network resources that are used by the link is taken by a reward function and network switching cost that is utilized to model the signaling and processing load incurred on the network during handoff. It has been shown that the total number of unnecessary handoffs can be decreased enhancing the performance of heterogeneous networks. Also, an assessment of the proposed scheme with the existing Vertical handoff decision algorithm like the Simple Additive Weighting method (SAW) has been made and the results show an improved performance over SAW.

Improvement of the Handover Performance and Channel Allocation Scheme using Fuzzy Logic, Artificial Neural Network and Neuro-Fuzzy System to Reduce Call Drop in Cellular Network

Due to handover failure, call drop occurs frequently. When a large number of incoming and handoff calls arrive at the same time, the performance of the conventional handoff algorithms may fall down. Moreover, multiple factors such as signal quality and available channels of cellular network can’t be evaluated in conventional algorithms. When mobile station (MS) moves, the connection of MS with nearby base station (BS) has to be switched from one to adjacent station. In this case, unnecessary handoffs will be occurred due to lack of proper decision of handoffs or lack of consideration about signal quality with available free channels. As a result call drop will occur frequently. For performing handoff efficiently, fuzzy logic based handoff decision algorithm, adaptive handoff threshold level using neural network and priority based dynamic channel allocation algorithm using neuro-fuzzy system has been proposed in this work. These algorithms will mainly focus on the proper decision of handoff based on evaluating signal strength, available free channels, spectrum efficiency, MS speed and distance from BS so that unnecessary and inefficient handoffs can’t be performed. Simulation revealed that using neuro-fuzzy system, the channel capacity, SIR and Handoff management were improved better than the others in terms of spectrum utilization efficiency, MS speed and SIR. The efficacy of the methodology has been proved by imitating the proposed model using MATLAB software.

Hybrid Fuzzy Logic Engine for Ping-Pong Effect Reduction in Cognitive Radio Network

The spectrum is a scarce resource and shall be used efficiently. It is observed that fixed spectrum allocation techniques, currently in use, may not be able to accommodate increased number of users trying simultaneously to access the network. Researches suggest that this problem of spectrum scarcity can be addressed by cognitive radio networks; which permits the dynamic use of spectrum. One of the basic requirements of dynamic spectrum access in cognitive radio network is spectrum handoff. There is an associated issue with frequent spectrum handoffs and that is of the ping-pong ect. The ping-pong ect is caused due to the motion of mobile users between the adjacent cells, thus, initiating unnecessary spectrum handoffs. The purpose of this study is to develop and analyse a system that has the ability to perform cient decision about the execution of spectrum handoffs and in turn reduce the chances of ping-pong ect. Therefore, a fuzzy logic based system has been developed in a cognitive radio WLAN and UMTS environment and handoff is investigated between primary and secondary users. Our proposed hybrid system uses a two-stage fuzzy logic controller to reduce the number of ping-pong handoffs. In the rst stage, the system is designed to control the power of SU and to avoid any interference to PU. In the second stage, the system is designed to take the decision to execute handoff.

Inter Radio Access Technology [IRAT] Handover Algorithms for Heterogeneous Wireless Networks

Inter-system handover is important for 4G/5G networks as these heterogeneous wireless networks (HWNs) have integrated different radio access technologies with diverse levels of performance. One of the major challenges is to make cell reselection and handover between these technologies. In this paper, we considered convergence of HWNs such as an integrated 3rd generation partnership project long term evaluation with legacy networks like WCDMA, GSM and a wireless local area network. We propose inter-radio access technology hand off or inter-system handoff (ISHO) algorithms to evaluate the performance of integrated network model. Three different realistic handoff scenarios have been investigated in the proposed integrated HWN. The aim of this paper is to evaluate the inter-system handover performance for the network model proposed. The performance of our proposed network model has been carried out using proposed ISHO-algorithms in terms of the average number of handoffs and decision delay. To reduce the unnecessary handoffs, to stave off the ping-pong effect and to lessen the decision delay, additional parameters such as time to trigger and hysteresis values are considered.

Multi-criteria vertical handoff decision algorithm for overlaid heterogeneous mobile IP networks

One of the key challenges to improving the quality of service (QoS) in integrated heterogeneous mobile Internet protocol networks is the design of an intelligent decision engine for accessing various services anywhere and at any time. The multi-criteria decision making algorithm plays a significant role in ensuring universal and seamless connection. In this study, a multi-criteria vertical handoff decision algorithm plus dwell time is developed to achieve a satisfactory quality of service using the best access network selection in an integrated wireless local area network (WLAN), a worldwide interoperability for microwave access (WiMAX), and a universal mobile telecommunications system (UMTS). Handoffs are divided into two schemes: the UMTS originating handoff (downward) and the WLAN/WiMAX originating handoff (upward/intrasystem). The initial criteria for real-time and non-real-time services are presented. The metrics that are required to trigger a handoff are the predictive received signal strength (PRSS) of neighbor networks and the received signal strength obtained from the current network. The back propagation neural network is learned for the prediction. The dwell time is used as a counter to avoid the unnecessary handoffs that may occur in the overlapping areas. The quantitative network selection is the largest merit value and is based on the available bandwidth, cost, user preference, and the criteria to eliminate inappropriate candidate networks. The importance of using the PRSS, dwell time, and merit function is evaluated. To illustrate the QoS satisfaction, the multi-criteria vertical handoff decision algorithm outperforms the single-criteria using the hysteresis and Mamdani fuzzy method.

Vertical handoff model in next generation wireless networks

The purpose of this research is to propose a scheme for making handoff decisions effectively. We propose a handoff decision strategy through a fuzzy logic system to perform a seamless handoff. We combine four types of determinants, namely, RSS (received signal strength), data rate, network latency, and user preferences as input metrics to our fuzzy inference engine. RSS is pre-processed first by the Kalman filter to get rid of noise. The logic of the inference engine is realized on the User Equipment side as a faster reaction to network dynamics. Our scheme performance is evaluated by simulating mobility scenarios through the context of move-out and move-in scenarios. Simulation results show that our scheme outperforms other approaches in terms of reducing unnecessary handoff for all cases.

Enhancing the Structural Strength of an ODD Laptop via Six Sigma Approach

The conventional design of notebook PCs configured with an optical disk drive suffers from structural durability problems that are indicative of potentially high defect rates. Companies have been attempting to reduce the size of assembly parts to pursue compactness, but the elimination of these materials might negatively affect structural stability, which is fundamentally important to all high-technology products. The Six Sigma methodology applied in this paper aims to improve quality performance and eliminate redesign waste and unnecessary handoffs according to customer requirements. This paper presents a case study using the define, measure, analyze, improve, and control (DMAIC) procedure. Several optimization techniques, such as response surface method (RSM) and computational intelligence, are adopted to optimize the significant factors that affect the module design and structural strength index during compression. Implementation results demonstrate that computational intelligence outperforms RSM. It shows computational intelligence reveals a good ability to solve the parameter optimization problems.

Algorithms for Handoff Minimization in Wireless Networks

This study focuses on the problem of handoff minimization for a set of users moving in a wireless network. This problem is analyzed by considering two cases for the user’s movement under access point capacity constraints: 1) all users move together, and 2) each user can have their chosen path within the network. In the first case, we propose an optimal competitive ratio algorithm for the problem. However, in the second case, having the connectivity assumption, that is, “if a user is connected to an access point so long that the received signal strength of the access point is not less than a specified threshold, the user should continue his/her connection”, we prove that no approach can reduce the number of unnecessary handoffs in an offline setting. However, without connectivity assumption, we present an optimal deterministic algorithm with the competitive ratio of nΔ for this problem under online setting, where n is the number of users and Δ is the maximum number of access points which cover any single point in the environment. Also, we prove that the randomized version of the algorithm achieves an expected competitive ratio of O(log Δ).

Traveling distance estimation to mitigate unnecessary handoff in mobile wireless networks

Amidst the factors that degrade the performance of a mobile wireless network (MWN), unnecessary handoff is considered to be one of the premier culprits since it aimlessly consumes the network resources. Most of the existing handoff algorithms proposed for MWN suffer from frequent unnecessary handoff as the primary decision of switching network cells is solely based on a single contributing factor, namely the received signal strength (RSS) that approximates the distance between a mobile node and access points. In practice, the RSS may not provide accurate approximation of the true distance as it fluctuates with wireless propagation impairments (such as shadowing, scattering, and reflection), leading to potential incorrect handoff decision within neighboring cells. In this paper, an improved estimation model for instantaneous distance between the mobile node and access point is formulated. Building upon this model, a new handoff technique is proposed by introducing two RSS thresholds and estimated distance verification, anticipating RSS fluctuations that may lead to handoff decision errors. The performance of the proposed handoff mechanism is thoroughly examined using numerical simulations and the acquired results demonstrate promising advantages of this proposed technique.

A novel approach to improve handover performance

Nowadays, mobile communications have heterogeneous wireless networks offering variable coverage and quality of service (QoS). The availability of alternatives generates a problem of occurrence of unnecessary handoff that results in wastage of network resources. In order to maintain seamless mobility, service continuity and optimise usage of network resources, it is desirable to minimise handover failures and unnecessary handovers. In this paper, a handover necessity estimation algorithm is introduced. This algorithm is made up of two modules. The first module estimates handoff necessity. It involves received signal strength (RSS) prediction, travelling distance estimation and velocity estimation. In a second module, candidate networks are discovered from the available networks. Based upon the predicted future values of RSS and travelling distance inside the wireless local area network (WLAN), the proposed algorithm improves the probability of unnecessary handoff and handover failures.

Application Specific Performance Evaluation of Vertical Handoff in UMTS-WLAN Network

The next generation of wireless system is expected to provide multimedia, multi class services any time anywhere with seamless mobility and Quality of Service (QoS). In such environment, vertical handoff management plays an important and challenging role. Some of the main functions of vertical handoff management are: to implement appropriate vertical handoff decision to minimize number of unnecessary handoff, to maintain minimum vertical handoff latency for seamless mobility and to provide guaranteed acceptable QoS required for user satisfaction. Thus, in this paper to avoid unnecessary handoff in integrated heterogeneous network we have proposed that the vertical handoff decision depends on coverage area of the network and the speed of the Mobile Node. Application specific cut-off speed for particular coverage range of network during which handoff is beneficial has been determined. Real time applications like HDTV, MPEG-4, and H.261 are considered in integrated heterogeneous network of UMTS (Universal Mobile Telecommunication System) and WLAN. Vertical handoff latency is analyzed for varied network traffic load, types of application and varied speed of Mobile Node. Effect of Mobile Node speed on packet loss is also analyzed. Finally, to satisfy user with acceptable end to end QoS, especially in the presence of heterogeneous integrated networks where every network has individual QoS, an end to end QoS mapping scheme between UMTS and WLAN integrated network has been proposed. The simulation is performed using Network Simulator NS-2 with NIST (National Institute of Standards and Technology) add on module.

A Novel Handoff Necessity Estimation Approach Based on Travelling Distance

<p><em>Mobility management is one of the most important challenges in Next Generation Wireless Networks (NGWNs) as it enables users to move across geographic boundaries of wireless networks. Nowadays, mobile communications have heterogeneous wireless networks offering variable coverage and Quality of Service (QoS). The availability of alternatives generates a problem of occurrence of unnecessary handoff that results in wastage of network resources. To avoid this, an efficient algorithm needs to be developed to minimize the unnecessary handoffs. Conventionally, whenever Wireless Local Area Network (WLAN) connectivity is available, the mobile node switch from cellular network to wireless local area network to gain maximum use of high bandwidth and low cost of wireless local area network as much as possible. But to maintain call quality and minimum number of call failure, a considerable proportion of these handovers should be determined. Our algorithm makes the handoff to wireless local area network only when the Predicted Received Signal Strength (PRSS) falls below a threshold value and travelling distance inside the wireless local area network is larger than a threshold distance.Through MATLAB simulation, we show that our algorithm is able to improve handover performance.<strong> </strong></em></p>

Cell Selection for Load Balancing in Heterogeneous Networks

The vision of advanced long-term evolution (LTE-A) project is set to ultimate increase of network capacity in heterogeneous networks (HetNets). In HetNets with small cell configuration, a considerable majority of user devices is eventually connected to the macrocell base station (MBS), while small base stations (BSs), such as femtocell access points (FAPs), are still without any user. This results in unbalanced load and reduces the data rate of macrocell user equipment (MUE). In this paper, a method is proposed for load balancing among FAPs, while desired throughput is achieved. The proposed method uses the estimated received signal strength from different BSs and adjusted pilot signals. Under the critical signal to interference plus noise ratio (SINR) condition, a list of candidate FAPs is prepared. The updated candidate list henceforth does not include the least visited FAPs, which in turn leads to lower unnecessary handoffs. Once the BS with the highest number of free RBs and the highest pilot signal power is selected, FAP allocates the RBs with higher SINRs (qualified RBs) to user. In the case of FAP unavailability, the algorithm compels users to connect to the MBS with adequate qualified RBs. The performance of the proposed method was evaluated under a variety of FAPs density, and the number and velocity of users in terms of throughput and Jain’s fairness index. The results evidence affordable improvements in the throughput and Jain’s index in comparison with other methods.