一种面向应用的mSCTP垂直切换决策方法

在泛在的无线异构网络中,垂直切换是用户实现无缝接入首要解决的问题.本文基于多参数,提出一种面向应用,基于IAHP-GRA的垂直切换决策方法.该决策方法基于传输层协议mSCTP,综合考虑当前应用特性、网络状况甚至用户个人偏好等多因素,采用改进的层次分析法IAHP与灰关联分析法GRA相结合,选择最佳目标网络进行切换.仿真结...     

基于区间标记判决的稳健垂直切换算法研究

在异构5G网络中,针对切换算法稳健性差引起的切换准确率低的问题,提出一种基于区间标记判决的稳健垂直切换算法.首先,引入中位值平均滤波法,获取更准确的网络参数.其次,基于参数波动特征分析,提出区间标记判决算法,保证候选网络筛选通过率和准确率的同时,提高区间标记判决算法的稳健性.再次,根据移动终端传输层需求,结合终端运动趋势,分别使用不同权值的效用函数获得最佳目标网络.最后,仿真结果表明,该算法能够有效提升切换触发和网络筛选的准确率,降低切换失败率和乒乓效应,提高系统吞吐量,并能够根据移动终端的需求选择最佳目标网络.     

下一代移动通信网中的一种复合垂直切换策略

本文分析了移动通信异构网络的组成及垂直切换的特性及目标,在此基础上,以实际网络为模型提出了一种新的复合垂直切换策略,并对其中的关键参数进行了推导验证。这一策略综合考虑了异构网切换过程中的主要因素,为保障无缝切换和业务连续提供了有力支持。     

异构网络切换判决算法的研究

随着移动通信技术的发展,不同接入技术的融合是通信行业的发展趋势,因此异构网络的的切换以及网络的选择已经成为了研究的重点.传统的异构网络切换算法仅仅考虑信号质量（RSS）的比较,不适用于复杂的异构网络.针对传统的切换算法进行改进,改进的新算法综合考虑目标网络信号强度（RSS）和目标网络负载,将网络移入和移出门限作为切换判决的首要条件,将网络负载作为切换判决的次要条件.通过建模仿真对传统切换算法和改进算法进行对比,分析结果得出改进切换算法在切换成功率和切换次数上都有所改善,能够有效地减少业务中断及乒乓效应,同时并未过度地提高算法的复杂度.     

基于模糊逻辑的自适应网络选择切换策略

针对目前异构无线网络紧耦合方式中的网络选择切换问题,研究了一种基于模糊逻辑的自适应网络选择切换策略,主要包含网络上下文感知、切换判决触发、网络选择三个阶段。通过设计网络过滤,提出一个动态的上下文感知解决方案,设计相应的上下文感知架构,在保障网络选择能够根据多种属性进行决策的同时,针对网络选择过程中动态网络参数无法具体量化的问题,在当前邻居网络上下文信息基础之上,引入模糊逻辑切换判决(强制切换/自愿切换),该机制使网络选择切换策略更加灵活,一方面符合多目标决策的网络选择切换特点,另一方面针对某些特殊业务,有助于其快速接入目标网络。通过Matlab仿真分析表明,自愿切换和强迫切换相比基于RSS切换均能够确保移动节点选择一个更好的接入网络,也证明了该切换策略具有更好的有效性。     

LTE-Advanced系统中的移动顽健性优化技术研究

网络自优化技术目前成为移动通信网络性能研究的热点.随着移动通信技术和业务的飞速发展,移动顽健性日益成为用户体验关注的重点,尤其是移动蜂窝通信网络中的切换失败、用户掉话、通信质量差等一系列问题.为解决此类切换带来的用户体验和系统移动顽健性下降问题,针对一种面向切换事件和切换场景的移动顽健性优化算法(MRO算法),以用户掉话率作为性能评价标准,分别在同构和异构网络下,综合考虑切换事件和不同切换失败场景(过早切换、过晚切换、乒乓切换)的特点优化调整切换参数,并采用系统级仿真进行了性能比较.仿真结果表明,加入MRO算法后,同构场景的掉话率从10.9％下降到6.2％,异构场景的掉话率从11.3％下降到6.3％,整体性能得到大幅提升.     

一种基于移动趋势量化的多属性垂直切换判决算法

由于对终端移动趋势的不明确,基站容易盲目发起切换,并导致较高的切换失败率。该文在LTE-WiMAX网络构成的异构无线网络环境下对现有的垂直切换算法进行了优化。该优化算法考虑了终端移动趋势,利用趋势量化参数来推断终端最终的目标区域,解决已有判决算法中存在的不必要切换过多的问题,提高切换成功率。在衰落信道下的计算机仿真结果表明,该优化算法可以减小切换中的切换失败率,从而提高网络的切换性能。     

基于层次分析法的异构网络切换技术研究

异构网络是移动互联网的热门发展方向,切换技术是其研究的重要内容.基于异构网络,对其垂直切换技术进行研究.采用系统研究中的层次分析方法,解决目标代价函数中不同属性的加权系数计算问题,为多个因素共同影响网络状态时进行网络切换选择提供了参考依据.     

基于运动趋势的模糊逻辑垂直切换算法

随着无线异构网络的融合,移动性管理技术成为其关键问题,而切换管理又是移动性管理的重要部分。针对垂直切换管理提出了一种基于运动趋势的模糊逻辑垂直切换算法。算法分为预判定、模糊逻辑控制及切换判决3个过程。首先,在预判定阶段根据MN的运动趋势及接收信号强度滤除掉不适宜接入WLAN的网络信息,从而有效减少不必要的数据量和系统开销;其次,将接收信号强度、网络的可用带宽和网络开销送入模糊逻辑控制器,通过参数的归一量化最终得到网络综合性能值(VCPN);最后,通过综合考虑VCPN和驻留时间来进行网络切换判决。仿真结果显示,该算法能够有针对性地做出切换判决,有效消除乒乓效应,提高网络切换性能。     

切换参数优化技术研究

本篇论文在分析新一代网络架构的基础上,研究切换优化参数对切换的影响,说明了各参数在切换过程中的作用。     

Spectrum handoff scheme with multiple attributes decision making for optimal network selection in cognitive radio networks

It is envisaged that in future Cognitive Radio (CR) networks deployment, multiple radio access networks may coexist. The networks may have different characteristics in terms of multiple attributes. CRs will have choices of selecting the optimal network out of the available networks. Optimal network selection is a challenging task that can be performed by spectrum handoff with Multiple Attribute Decision Making (MADM). The spectrum handoff decision with MADM provides wider and optimal choice with quality of service. This motivates the devolopment of a spectrum handoff scheme with MADM methods such as simple additive weighting, a technique for order preference by similarity to the ideal solution, a grey relational analysis and a cost function based method, which is the objective of this study. The CR preferences are based on voice, video and data services, called triple play services. The numerical results show that all MADM methods are effective for selecting the optimal network for spectrum handoff with a reduced complexity for the spectrum handoff decision. The paper shows that the proposed spectrum handoff scheme can be effectively implemented to select the optimal network according to triple play services in CR networks.     

无线异构网络中带有动态权值的新型垂直切换算法

In order to enhance the quality of vertical handoff in an overlay wireless network, multiple attributes are taken into account when optimizing the vertical handoff decision including user-based and network-based QoS factors. In this paper, we develop a novel vertical handoff algorithm in an integrated 3G cellular and Wireless LAN networks. The proposed algorithm can adjust the weight of each QoS attribute dynamically as the networks change, trace the network condition and choose the optimal access point at transient regions. Simulation results show that this algorithm is able to provide accurate handoff decision, resulting in small unnecessary handoff numbers, good performance of throughput and handoff delay in heterogeneous environments.     

Heterogeneous Wireless Networks: Configuration and Vertical Handoff Management

Vertical handoff is one of the most important issues for the next generation heterogeneous wireless networks. However, in many situations, unbeneficial vertical handoffs occur across intersystem heterogeneous networks cause network performance degradation. Therefore, we propose a novel configuration architecture that can be deployed in the next generation of wireless networks. Second, we propose a predictive and adaptive Vertical Handoff Decision Scheme that optimizes the handoff initiation time as well as selection of the most optimal network. The proposed vertical handoff decision algorithm considers the technology type as well as the Signal to Interference Ratio (SIR), the Mobile Station (MS) velocity, the user preferences, the applications requirements and the terminal capabilities as the most important factors to make vertical handoff decision. In order to minimize handoff costs, the proposed decision algorithm uses the dwell timer concept. The handoff costs are analyzed in terms of unnecessary and unbeneficial handoffs rate.The simulation results show that the reduction of unnecessary handoffs proposed in our vertical handoff decision scheme reduces the handoff blocking probability, the packets loss rate and the handoff overhead     

一种基于上下文感知的垂直切换技术研究

未来网络的发展趋势是各种无线接入网络共存的异构网络环境,而垂直切换技术是融合多个异构接入网络的关键技术之一,垂直切换包括三个阶段,即系统发现、切换决策和切换执行。文中主要研究了基于上下文感知的垂直切换判决策略,并与移动垂直切换技术相结合,实现了WLAN/UMTS网络间的垂直切换,通过仿真表明该方法在吞吐量和切换时延方面都得到改善。     

Adaptive vertical handoff algorithm in heterogeneous networks

The integration of cellular network (CN) and wireless local area network (WLAN) is the trend of the next generation mobile communication systems, and nodes will handoff between the two kinds of networks. The received signal strength (RSS) is the dominant factor considered when handoff occurs. In order to improve the handoff efficiency, this study proposes an adaptive decision algorithm for vertical handoff on the basis of fast Fourier transform (FFT). The algorithm makes handoff decision after analyzing the signal strength fluctuation which is caused by slow fading through FFT. Simulations show that the algorithm reduces the number of handoff by 35%, shortens the areas influenced by slow fading, and enables the nodes to make full use of WLAN in communication compared with traditional algorithms.     

Seamless vertical handoff using modified weed optimization algorithm for heterogeneous wireless networks

In the global scenario, a variety of wireless access networks are available. Different types of applications such as real time, nonreal time, and high bandwidth availability are used for heterogeneous wireless networks. Therefore, it is necessary for a service provider to make an appropriate connection support. For better performance, connections are to be exchanged among the different networks using seamless vertical handoff (VHO). The proposed algorithm shows the effect of optimization technique, which involves handoff decision process using vertical handoff triggering and selection of the network. The handoff triggering is initiated by using the received signal strength (RSS). In traditional method, handoff triggering is initiated by using RSS only. This method, modified weed optimization (M-WO) algorithm, reduces the unnecessary handoff by considering both RSS and velocity of the mobile node in handoff triggering. The parameters such as battery lifetime, handoff call dropping rate, load, dynamic weights adaptation and so on are to be considered individually or combined to make an effective network selection process. This paper highlights a novel effect ofM-WOalgorithm for decision making during the VHO. Our effort is to essentially optimize the system load, so that it reduces the handoff call dropping rate and the battery power consumption of the mobile node (MN). Weight of each QoS metrics is adjusted along with the networks changing conditions to trace the M-WO. Therefore, the novel VHO decision-making algorithm is superior to the existing SSF and OPTG methods. The simulation results show that the performance ofM-WOalgorithm is far better than SSF andOPTGmethods in terms of load, handoff call dropping rate and battery lifetime of MN.     

Artificial Neural Network Based Vertical Handoff Algorithm for Reducing Handoff Latency

One of the most challenging topics for next generation wireless networks is vertical handoff concept since several wireless technologies are assumed to cooperate. Plenty of parameters related to user preferences, application requirements, and network conditions, such as; data rate, service cost, network latency, speed of mobile, battery level, interference ratio and etc. must be considered in vertical handoff process along with traditional RSSI information. In this study, a new artificial neural network based handoff decision algorithm is proposed in order to reduce the handoff latency of smart terminal deployed in aforementioned wireless heterogeneous infrastructures. The prominent parameters data rate, monetary cost and RSSI information are taken as inputs of the developed vertical handoff decision system. Performance results of the proposed system are also compared with those of classical Multiple Attribute Decision Making method Simple Additive Weighting, and of some other artificial intelligence based algorithms. According to the results obtained, the proposed neural network based vertical handoff decision algorithm is able to determine whether a handoff is necessary or not properly, and selects the best candidate access network considering the abovementioned parameters. The results also show that, the neural network based algorithm developed significantly reduces the handoff latency while the number of handoffs, which is another vital performance metric, is still reasonable.     

异构网络垂直切换技术

下一代无线网络(Next Generation Wireless Networks,NGWN)将融合多种不同的网络体系结构与无线技术,NGWN的异构性要求向用户提供无缝切换。为此文章引入了异构无线网络垂直切换策略,并深入论述了其中的关键细节——网络发现、切换判决和切换信息交互流程等。     

车辆异构网络中预测垂直切换算法

在车辆异构网络中,针对垂直切换决策时刻之后网络状态的动态变化,提高切换性能问题,提出一种基于马尔可夫过程的预测垂直切换(M-VHO)算法。算法考虑了切换决策后网络状态的动态变化对车辆终端服务质量(QoS)的影响。其基本思路是:在需要垂直切换时,利用马尔可夫过程的转移概率预测未来网络状态的变化;另外,采用模糊逻辑方法确定评价属性参数权重;最后,比较切换决策、切换执行和切换之后时刻的总收益来优化选择最佳切换网络。仿真结果证明,该算法在确保较高负载均衡的情况下,可有效改进车辆终端的平均阻塞率及丢包率,降低乒乓效应,确保了车辆终端的QoS。     

异构无线网络垂直切换技术综述

垂直切换是多网融合的基础,是实现异构网络互通、支持不同接入方式无缝衔接的核心技术,目前正在受到业界的重点关注,并成为学术界研究的热点问题。随着无线移动通信技术向接入多元化、网络一体化和应用综合化的方向发展,各种蜂窝移动接入、宽带无线接入和固定接入将共同接入基于IP的统一核心网络,通过网络间的垂直切换,支持用户的移动性和移动过程中业务的连续性。首先给出了垂直切换的定义和基本概念,介绍了垂直切换的分类和基本流程,随后详细论述垂直切换的切换判决和切换执行2个环节。针对切换判决,总结了现有判决算法,重点评述各代表算法工作原理并剖析论其特点和存在的不足。针对切换执行,详述了现有垂直切换执行机制的工作原理和适用场景,并分析其优缺点。最后,对未来垂直切换技术的研究方向进行了展望。