基于多业务的移动性垂直切换算法

针对异构网络环境下紧耦合方式中的网络切换问题,提出一种结合通信业务和运动感知的切换算法。根据终端移动性初步筛选出候选网络集,依据终端多业务特性从候选网络集中选择出最优网络进行切换。在不同业务下与基于运动感知的切换算法进行实验对比,结果表明,该算法既能避免不必要的切换,又能降低切换阻塞率。     

基于对数交叉熵的CDMA软切换性能分析

针对3G及B3GCDMA移动通信系统软切换关键技术,在假设通过功率控制解决远近效应问题的基础上,引入对数交叉熵概念,对宏小区和微小区重迭小区的软切换性能进行了分析。同时对该系统的重要性能指标：微小区中软切换用户可切换到宏小区的概率进行了定量分析和性能仿真。通过分析可看出：该系统可合理地降低CDMA系统微小区软切换呼叫阻塞率,改善CDMA系统的通信质量。     

基于模糊逻辑技术的切换策略

下一代宽带无线通信网在为用户提供高速率语音服务以及图像、视频信息的传输和高速接入Internet服务等丰富的业务类型的同时,也给系统的切换策略带来新的挑战。以往仅考虑单一因素对系统影响的切换策略已不适用于具有丰富业务类型的下一代宽带无线通信网络。该文利用模糊逻辑技术进行切换过程中的目标小区选取。相比传统方案,模糊逻辑技术可以兼顾多种因素,使得选取结果更加合理,并且可以均衡系统负载、减少切换的拒绝率。     

5G 超密集网络虚拟化解决方案

密集部署传输节点,减少小区半径,获得更大的小区分裂增益是5G超密集网络实现容量提升目标的关键手 段。本文首先介绍了5G超密集网络的含义、典型覆盖场景和面临的挑战;其次,分析了5G虚拟化网络架构;最后介绍了5G移 动通信系统以用户为中心的虚拟化技术,重点介绍了小区虚拟化和终端虚拟化技术在解决移动性和干扰问题方面的优势。     

一种TD-LTE与eHRPD系统重叠覆盖下的负载均衡算法

 针对3G的eHRPD和4G的TD-LTE移动通信系统进行混合组网时,每种网络制式下的小区在用户增多时都有可能过载,除了传统的与邻近小区进行基站的切换,还可以在不同制式之间进行垂直切换。本文以网络资源利用率为参考,对系统内的用户进行异系统垂直切换,从而使混合组网后的系统负载得到均衡。通过该整合系统的仿真,在保证无线链路丢失率不受显著影响前提下,该方法使得蜂窝小区的平均吞吐率有所提高,并能找到使得吞吐率最大时的最佳切换阈值。     

3G网络的移动视频监控系统

移动流媒体应用是基于3G独特高数据带宽的业务应用,是3G业务网络中最具市场潜力的增值业务类型。为了进一步推广移动流媒体技术的应用,该文将3G移动网络和固网视频监控结合起来,实现两者优势互补,提出了一种基于3G网络的移动视频监控系统模型,此模型能够弥补传统移动网络和固网的不足对移动视频监控系统的设计具有一定的指导意义。     

VANET中基于移动IPv6的快速切换策略研究

针对车载自组织网络在城市道路车流量大的情况,车辆在不同的路边基站之间频繁地进行上下文切换,从而导致IPv6的移动性支持协议切换时延过长的问题,提出了一种基于代理移动路由的快速切换方案。采用代理移动路由在3G/WiMAX通信域的切换触发其它802.11p通信域内的车辆发生切换的方法,来达到宏切换与微切换相结合的目的,从而实现批量式快速切换。分析结果表明,该方案较现有方案提高了切换效率,减小了切换时延。     

基于用户无感知的5G 移动性管理

5G移动通信系统将提供独立于无线技术的移动性管理,无论用户位置如何改变,都能确保业务和通信质量的 连续性。本文首先分析了5G移动通信系统在移动性管理的设计目标：低时延、低功耗、高可靠性和灵活性;其次,分析了5G移 动性管理的三个主要场景,分别是分布式移动性管理场景、集中式移动性管理场景、分布集中混合式场景;最后,对5G移动性 管理的网络控制切换和终端自动控制切换两种解决方案进行了对比分析。     

基于SDN架构的5G通信网络中的切换算法

针对传统的移动性管理基站在5G超密集网络部署的特定场景中所面临的信令开销大、数据传输效率低等问题,本文研究基于SDN架构的5G通信网络中的垂直切换算法,充分利用SDN控制器中的全局化的网络状态信息,计算最优的切换决策结果,尽可能的减少移动节点收集网络状态信息所带来的时延以及网络开销.利用Matlab对提出的切换管理策略进行了仿真,相对于LTE系统的切换管理机制,在切换时延以及平均切换次数上都有优势.     

RSVP协议在移动IPv6网络中的扩展性研究

针对无线移动通信的特点,提出了一种在移动IPv6网络中保障用户通信服务质量的资源预留新方案Fast RSVP.该方案采用跨层设计的思想,将两个不同层次的模块:移动IPv6模块和RSVP模块结合起来,通过在两个模块之间增加一些原语使得二者配合工作以保证移动用户的通信业务质量.Fast RSVP方案引入了邻居隧道提前资源预留、优化路径资源预留、切换预留、路径融合等一系列新机制.仿真实验结果表明,与其他移动环境中的RSVP扩展方案相比,该Fast RSVP方案在支持无线移动通信方面具有如下优势:(1)能够实现移动节点带有服务质量保证的快速切换;(2)能够避免移动IP切换过程中三角路由和重复预留造成的资源浪费;(3)能够区分不同类型的切换预留请求,在保证网络整体性能的前提下显著降低因为切换而导致的服务中断率.     

Decision-level fusion in fingerprint verification

A scheme is proposed for classifier combination at decision level which stresses the importance of classifier selection during combination. The proposed scheme is optimal (in the Neyman-Pearson sense) when sufficient data are available to obtain reasonable estimates of the join densities of classifier outputs. Four different fingerprint matching algorithms are combined using the proposed scheme to improve the accuracy of a fingerprint verification system. Experiments conducted on a large fingerprint database (∼2700 fingerprints) confirm the effectiveness of the proposed integration scheme. An overall matching performance increase of ∼3% is achieved. We further show that a combination of multiple impressions or multiple fingers improves the verification performance by more than 4% and 5%, respectively. Analysis of the results provide some insight into the various decision-level classifier combination strategies.     

Clustering and group selection of multiple criteria alternatives with application to space-based networks

In many real-world problems, the range of consequences of different alternatives are considerably different. In addition, sometimes, selection of a group of alternatives (instead of only one best alternative) is necessary. Traditional decision making approaches treat the set of alternatives with the same method of analysis and selection. In this paper, we propose clustering alternatives into different groups so that different methods of analysis, selection, and implementation for each group can be applied. As an example, consider the selection of a group of functions (or tasks) to be processed by a group of processors. The set of tasks can be grouped according to their similar criteria, and hence, each cluster of tasks to be processed by a processor. The selection of the best alternative for each clustered group can be performed using existing methods; however, the process of selecting groups is different than the process of selecting alternatives within a group. We develop theories and procedures for clustering discrete multiple criteria alternatives. We also demonstrate how the set of alternatives is clustered into mutually exclusive groups based on 1) similar features among alternatives; 2) ideal (or most representative) alternatives given by the decision maker; and 3) other preferential information of the decision maker. The clustering of multiple criteria alternatives also has the following advantages. 1) It decreases the set of alternatives to be considered by the decision maker (for example, different decision makers are assigned to different groups of alternatives). 2) It decreases the number of criteria. 3) It may provide a different approach for analyzing multiple decision makers problems. Each decision maker may cluster alternatives differently, and hence, clustering of alternatives may provide a basis for negotiation. The developed approach is applicable for solving a class of telecommunication networks problems where a set of objects (such as routers, processors, or intelligent autonomous vehicles) are to be clustered into similar groups. Objects are clustered based on several criteria and the decision maker's preferences.     

集成特征选择的广义粗集方法与多分类器融合

为改善多分类器系统的分类性能, 提出了基于广义粗集的集成特征选择方法. 为在集成特征选择的同时获取各特征空间中的多类模式可分性信息, 研究并提出了关于多决策表的相对优势决策约简, 给出了关于集成特征选择的集成属性约简 (Ensemble attribute reduction,EAR) 方法, 结合基于知识发现的 KD-DWV 算法进行了高光谱遥感图像植被分类比较实验. 结果表明, EAR 方法与合适的多分类器融合算法结合可有效提高多分类器融合的推广性.     

Enhanced uplink non-orthogonal multiple access for 5G and beyond systems

Uplink non-orthogonal multiple access (NOMA) is a promising technique to meet the requirements of the fifth generation (5G) and beyond systems. Various NOMA schemes have been proposed in both academia and industry. However, most existing schemes assume equal average received power, which limits the performance. We propose three enhancements of uplink NOMA to achieve the requirements of massive connectivity and high reliability in 5G, where unequal average received power is exploited as part of the multiple access signature. First, the optimal sequences targeting to generalized Welch-bound equality (GWBE) are obtained for unequal average received power. Then user grouping with multi-level received powers is proposed for better successive interference cancellation (SIC) at the receiver. Finally, sequence grouping based on the cross-correlation properties of sequences is proposed to reduce inter- and intra-group interference. Simulation results show that by incorporating multi-level received powers and sequence grouping into existing NOMA schemes, for an NOMA system with 400% overloading and fixed signature allocation, 3 dB and 10 dB signal-to-noise ratio (SNR) gains at 0.1 block error rate (BLER) target can be achieved compared with existing NOMA schemes and orthogonal multiple access (OMA), respectively. Besides, 0.01 BLER target can be achieved while an error floor exists in existing NOMA schemes. Under random sequence selection, collision probability is reduced by multi-level powers. In addition, GWBE sequences achieve lower BLER than existing sequences and the gain is large especially for low BLER requirements. This shows that the proposed scheme can support larger connectivity and higher reliability.     

Network Selection Decisions for Multiple Calls Based on Consensus Level

Next generation multimode terminals have the capability to support different classes of calls simultaneously as well as the ability to connect to two or more radio access technologies (RATs), at the same time, in a heterogeneous wireless network. For a mobile terminal having multiple classes of simultaneous handoff calls (such as file download and video sessions), RAT selection decisions can be made independently for individual calls in the group or jointly for the entire group of calls. Both independent and group RAT selection decisions for multiple calls have advantages and disadvantages. Existing RAT selection algorithms have focused on RAT selection decisions for single calls. Therefore, this paper investigates independent call and group call RAT selection decisions for multiple calls in heterogeneous wireless networks, and proposes a scheme that makes RAT selection decisions for multiple calls based on a consensus level among the multiple calls to be admitted. When this consensus level is among multiple calls to be admitted into a particular RAT and is equal to or above a certain threshold value, a group decision is used. Otherwise, independent decisions are made. The performance of the proposed RAT selection scheme is evaluated in a three service three RAT heterogeneous network, supporting multihomed terminals. Simulation results are given to show the effectiveness of the proposed scheme.     

基于多维标度的动态网络选择算法

异构无线网络的网络选择问题中,除了考虑多属性的网络参数外,还需考虑无线信道的时变性特征。针对这两个考虑因素,提出了一种基于多维标度的新的动态网络选择算法,可将多属性判决的网络选择问题近似转化为一个低维的拟合构图,并能反映不同时刻同个网络的变化。仿真结果表明,在不考虑负载的情况下,提出的算法能有效地选择出适合于移动终端当前业务的网络,并能在低维坐标系中直观地观察网络间的区别。     

具有一跳前向安全性的X2切换密钥更新协议

长期演进系统LTE是下一代移动通信系统的主要标准之一,其安全性对于系统的成功部署至关重要。研究LTE中本地信号切换也即X2切换时的密钥管理,并关注当前方案仅具备两跳前向安全性这一缺陷。我们提出一个改进的密钥更新方案,以达到更强的一跳前向安全性。新方案弥补了上述安全缺陷,且在不增加通信开销的情况下,最大限度地保留了现有的密钥材料及参数形式,因而当前标准可顺利升级到改进方案。     

Supervisory multiple regime control

The objective of this work is to identify a control algorithm that is capable of handling nonlinear behaviour (operating point dependent) witnessed in most industrial processes. To this end, the proposed solution is that of a supervisory multiple model control scheme, SMMC. This work demonstrates that the multiple model methodology can be recast into a Supervisory approach, whereby the supervisor is employed as a selector. This selector (supervisor) identifies the appropriate local-controller from a fixed family set. Unlike other supervisory techniques a multiple model observer (MMO) is proposed for the selection mechanism. Switching between local-controllers is accomplished bumplessly through a multiple model bumpless transfer scheme. Consequently, producing a continuous control signal as the process transverses between different operating regimes. The key issue in this application is the unique interaction between the local-controllers and the supervisor. This interaction is necessary to ensure global stability is maintained at all times, especially during switching. In short, the SMMC scheme enables the implementation of linear control theory, which is well accepted in industry, to standard nonlinear processes. The SMMC approach warrants the control design to extend beyond normal operating conditions that breakdown when standard linear control techniques are applied. The above notion is applied to a pilot-scale binary distillation column. In this example the column's distinct operating points describe the nonlinear behaviour. The results illustrate that as the distillation column shifted between different operating points the SMMC self-regulates accordingly. This self-regulation ensures that global stability and performance are maintained at an optimum. The entire SMMC design was implemented within a PC Windows-NT environment that was interfaced to an industrial DCS system.     

A comparative study of combining multiple enrolled samples for fingerprint verification

In fingerprint verification systems, there are usually multiple (from two to four) enrolled impressions for a same finger. The performance of the systems can be improved by combining these impressions through feature fusion or decision fusion strategy. In this paper, different schemes to combine multiple enrolled impressions are comparatively studied. Experimental results show that a larger improvement can be obtained by using decision fusion scheme than feature fusion. In all decision fusion rules, sum rule outperforms voting rule a little whether using similarity or Neyman-Pearson rule. Based on the observation that the performance of these two strategies can complement each other, we also propose a novel fusion scheme to further combine feature fusion and decision fusion, which can produce an even better result.     

Tying up loose ends: a method for constructing and evaluating decision aids that meet blunt and sharp-end goals

We present a methodological framework for constructing and evaluating decision aids – fast and frugal trees (FFTs) – ideally suited to the front line of an organisation. Their performance can be analysed in signal detection theory, allowing for transparent selection of FFTs given managerial-level trade-offs among type I and II errors. We extend FFTs from binary classification to selection from multiple actions (FFT multiple) as well as performance analysis to organisational goal states beyond type I and II error reduction. Concepts and framework are introduced and a tutorial-style example application (threat assessment at military checkpoints) is provided. Throughout, we discuss ways to deal with missing or incomplete data and show that the performance of decision aids may be overestimated if the effectiveness of actions is not heeded. The methodology can be used to construct and evaluate decision aids in any area characterised by dichotomised cues and a one-to-many mapping between categorisation outcomes and actions.