车联网中基于贝叶斯决策的垂直切换方法研究

车辆需要在车联网的异构无线网络环境下进行垂直切换,针对垂直切换技术普遍不能支持 WAVE, WiMAX和3G cellular间的垂直切换这一问题,提出了一种基于贝叶斯决策的垂直切换算法。首先,根据接入网络的信号强度、传输速率、误码率和网络阻塞率以及车辆终端的速度和运动趋势建立多条件相关的切换概率分布,计算出切换先验概率;然后通过贝叶斯决策算法计算后验概率并进行决策分类,从而选取最优网络接入。仿真实验结果表明,该算法不仅有效地实现WAVE,WiMAX和3G cellular无线接入技术之间的垂直切换,而且避免了乒乓效应,保证了网络及时更新。     

代价函数权值可变的速度自适应的异构无线网络垂直切换算法

利用移动车载终端的测速功能,针对移动WiMAX网络支持高速移动的特点,本文提出了一种在异构无线网络中的基于车载终端的代价函数权值可变的速度自适应垂直切换算法.该算法使用速度自适应策略克服了网络发现阶段采用测量网络的接收信号强度这种固定且单一的网络发现方式带来的缺点,提高了候选网络集更新速度,改进了高速移动用户网络发现的...     

异构无线网络中的共享载波垂直网络转换算法

为了提高异构无线网络的频谱利用率,将认知无线电中合作动态频谱分配(DSA)的思想应用于以基站和用户为基本单元的异构无线网络,将多模终端用户垂直切换的思想引入基站侧,提出了异构无线网络中的共享载波垂直网络转换(SCVNT)算法。理论分析与仿真实验表明,SCVNT算法可有效提高异构无线网络的总体信道利用率,改善资源分配的公平性,并可实现平滑升级,具有较高的应用价值。     

一种基于业务切换的垂直切换判决算法

在下一代异构无线网络环境中,为满足在异构无线网络架构下采用不同切换方式的垂直切换请求,我们提出一种基于业务切换的垂直切换判决算法,并设计了一种基于业务切换的代价函数。通过数学分析和在UMTS,WLAN融合的网络环境下对该方案的切换失败率的仿真分析,证明了该方案在支持终端的移动性、保障用户业务请求满意度以及缓解网络负载压力上相比传统基于代价函数的垂直切换判决算法更具优势。     

基于模糊逻辑的多终端协同的垂直切换决策算法

针对异构网下多终端协同的垂直切换决策问题,提出一种基于模糊逻辑和层次分析法的垂直切换决策算法,它分为2部分:切换时机的判断和虚拟终端的构建.首先采用模糊逻辑判断切换的时机,然后采用层次分析算法与简单加权求和结合的方法选择虚拟终端的最优构成方式.仿真结果表明,算法能够降低切换次数和不必要切换率,并且能够充分体现应用需求和用户偏好.     

超密集异构无线网络中基于位置预测的切换算法

在密集异构蜂窝网络和无线局域网络构成的超密集异构无线网络中, 变速移动的车辆终端会面临更加频繁的切换,导致用户服务质量(QoS)变差。该文针对上述问题,首先,利用高斯马尔可夫移动模型,预测车辆下一时刻的位置,筛选出满足终端服务质量的候选网络集,与当前的候选网络集做交运算,其次,当前接入网络不在交集中,则使用变步长的萤火虫算法寻找最佳网络;再次,对因预测误差导致的切换失效,则把终端用户迁移到宏蜂窝,以保证通信的持续性。仿真结果表明,在超密集异构无线网络中,使用该文所提算法能够减少乒乓切换等频繁切换现象,同时,提升了用户的服务质量和网络吞吐量。

     

基于异构网络上下文感知垂直切换判决策略的研究

为了解决车载移动终端在异构网络环境下无缝切换的问题,采用层次分析法和简单加权法,分析了垂直切换过程中目标发现、切换决策和切换执行三个关键阶段存在的问题,并提出了一种基于上下文感知的垂直切换判决策略。通过实验验证,表明了该方法能有效地改善异构网络环境中切换时延和吞吐量等方面的问题。     

基于混合决策值的异构无线网络选择算法

针对异构网络环境下网络选择算法中决策值归一化或模糊化中存在的问题,提出了基于混合决策值的异构无线网络接入选择算法。该算法根据用户需求建立垂直切换算法评价指标体系,在此基础上建立混合型决策矩阵和计算一级指标、二级指标的权重,TOPSIS算法选择最优的网络。仿真分析表明,该算法在网络选择的过程中能够综合备选网络的各项指标,选择最优的网络接入,同时也能够满足具有特殊需求的移动台,提高网络吞吐量或减少传输延迟时间。     

面向终端个性化服务的模糊垂直切换算法

在异构无线网络中,针对终端不同类型的应用在服务质量(QoS)需求上的差异,该文提出一种面向终端个性化服务的模糊垂直切换算法。该算法从以下两个方面提高切换性能：首先在网络发现阶段,通过预测候选网络在切换时刻的负载状态,对候选网络进行筛选;然后在切换判决阶段,根据每类应用对QoS参数的不同需求范围设计不同的隶属度函数。仿真结果表明,该算法能有效降低切换阻塞率,提高系统吞吐量,并能根据终端的应用类型合理地选择切换网络,满足了终端的个性化服务需求。     

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。     

Immune optimization algorithm for solving vertical handoff decision problem in heterogeneous wireless network

In heterogeneous wireless network environment, wireless local area network (WLAN) is usually deployed within the coverage of a cellular network to provide users with the convenience of seamless roaming among heterogeneous wireless access networks. Vertical handoffs between the WLAN and the cellular network maybe occur frequently. As for the vertical handoff performance, there is a critical requirement for developing algorithms for connection management and optimal resource allocation for seamless mobility. In this paper, we develop a mathematical model for vertical handoff decision problem, and propose a multi-objective optimization immune algorithm-based vertical handoff decision scheme. The proposed scheme can enable a wireless access network not only to balance the overall load among all base stations and access points but also maximize the collective battery lifetime of mobile terminals. Results based on a detailed performance evaluation study are also presented here to demonstrate the efficacy of the proposed scheme.     

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     

A Simple and Robust Vertical Handoff Algorithm for Heterogeneous Wireless Mobile Networks

Wireless networking is becoming an increasingly important and popular way of providing global information access to users on the move. One of the main challenges for seamless mobility is the availability of simple and robust vertical handoff algorithms, which allow a mobile node to roam among heterogeneous wireless networks. In this paper, motivated by the facts that vertical handoff procedure is done on mobile nodes and battery power may be one crucial parameter for certain mobile nodes, a simple and robust two-step vertical handoff decision algorithm is proposed for heterogeneous wireless mobile networks. To the best of our knowledge, this is the first vertical handoff algorithm that takes the classification of mobile nodes into consideration, one is resource-poor mobile nodes, and the other is resource-rich mobile nodes. This new feature makes it more applicable in the real world. In addition, dynamic new call blocking probability is firstly introduced by this paper to make handoff decision for wireless networks. The experiment results have shown that the proposed algorithm outperforms traditional algorithms in bandwidth utilization, handoff dropping rate and handoff rate.     

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.     

考虑负载均衡和用户体验的垂直切换算法

在超密集异构无线网络中,针对城区交通高峰期,大规模车载终端短时间聚集性移动引起的网络拥塞问题,该文提出一种考虑负载均衡和用户体验(LBUE)的垂直切换算法。首先,引入网络环境感知模型预测网络未来的拥塞程度,并提出一个融合自组织网络的网络架构,缓解网络拥塞。其次,定义业务适应度和负收益因子,并提出一种基于秩和比(RSR)的自适应切换判决算法,为用户筛选出当前环境下满意度最高的目标网络。实验结果表明,该算法能够有效降低终端接入网络的阻塞率和掉话率,实现网络间负载均衡并提升用户体验。     

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。     

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.     

Effect of mobile terminal heterogeneity on call blocking/dropping probability in cooperative heterogeneous cellular networks

It is envisaged that next generation wireless networks (NGWN) will be heterogeneous, consisting of multiple radio access technologies (RATs) coexisting in the same geographical area. In these heterogeneous wireless networks, mobile terminals of different capabilities (heterogeneous terminals) will be used by subscribers to access network services. We investigate the effect of using heterogeneous mobile terminals (e.g. single-mode, dual-mode, triple-mode, etc.) on call blocking and call dropping probabilities in cooperative heterogeneous wireless networks. We develop analytical models for heterogeneous mobile terminals and joint radio resource management in heterogeneous wireless networks. Using a two-class three-RAT heterogeneous wireless network as an example, the effect of using heterogeneous terminals in the network is evaluated. Results show the overall call blocking/dropping probability experienced by subscribers in heterogeneous wireless networks depends on the capabilities of mobile terminals used by the subscribers. In the worst case scenario, when all subscribers use single-mode mobile terminals, each subscriber is confined to a single RAT and consequently, joint radio resource management in heterogeneous wireless network has no improvement on new call blocking and handoff call dropping probabilities. However, in the best case scenario, when all subscribers use three-mode terminals, new class-1 call blocking probability decreases from 0.37 (for 100% single-mode terminals) to 0.05, at the arrival rate of 6 calls per minute. New class-2 call blocking probability also decreases from 0.8 to 0.52. Similarly, handoff class-1 call dropping probability decreases from 0.14 to 0.003, and handoff class-2 call dropping probability decreases from 0.44 to 0.09.