接触可预测的认知自组织网络机会路由跨层优化及其波动性评价

发布时间：2018-05-25 19:04

本文选题：认知无线电 + 自组织网络　；参考：《河北工程大学》2017年硕士论文

【摘要】：随着无线通信技术的飞速发展,频谱资源日趋紧张。而共享频谱资源的认知无线电技术(Cognitive Radio,CR)的应用很大程度上解决了频谱资源短缺的问题。由于传统的自组织网络(Ad Hoc Networks)路由协议未考虑频谱资源的约束以及频谱资源的时变性,为了更准确有效地选路,必须考虑动态变化的频谱资源信息。为了解决上述问题,将认知无线电技术与自组织网络相结合,形成了认知自组织网络(Cognitive Radio Ad Hoc Networks,CRANET)。由于CRANET中,认知用户(Cognitive Users,CUs)间的通信机会是动态变化的,当这种机会出现时,就称CUs间接触,且这种接触如果是可预测的,那么就将这种CRANET称为接触可预测的CRANET。由于接触可预测的CRANET中频谱具有动态性,CUs占用的频段是随主用户(Primary Users,PUs)的活动而动态改变,且频谱资源管理是媒体访问控制层(Medium Access Control,MAC)的功能。为合理利用频谱资源,提高接触可预测CRANET端到端吞吐量,引入跨层优化方法。然而,在接触可预测的CRANET中,CUs间的接触度、信噪比(Signal Noise Ratio,SNR)、CUs队列长度是影响到端到端吞吐量的主要因素。本文在此背景下,深入研究了接触可预测的CRANET中接触度、SNR等多参数约束的机会路由和信道分配问题,并提出了机会路由波动性的评价指标。本文的主要研究成果如下:(1)提出了一种基于接触度和连续有效接触时间度量尺度的可预测接触分析模型。定义了接触、非接触以及有效接触,旨在描述CUs间的接触关系,并定义了接触度,旨在估计CUs间连续有效接触的概率。提出了连续有效接触时间度量尺度,用以量化CUs间通信的持续时间。借助微积分原理和概率论,计算出了CUs间连续有效接触时间的平均值。仿真结果表明,可预测接触分析模型可有效预测CUs间的接触关系。(2)提出了一种转发角自调节机会路由和信道分配联合优化策略。为了确定转发候选CUs的集合,提出了一种基于CUs队列长度和接触度约束的选择算法。设计了转发角自调节的机会路由策略,用以确定转发候选CUs以及动态计算和更新转发角。考虑了转发角、SNR和信道中断次数等参数约束,提出了信道分配和转发角自调节的机会路由联合优化算法。基于数据包转发概率约束算法,实现了端到端吞吐量的最大化,并通过波动率度量尺度对机会路由波动性进行了评估。
[Abstract]:With the rapid development of wireless communication technology, spectrum resources are becoming increasingly scarce. The application of Cognitive Radio (CR), a cognitive radio technology for sharing spectrum resources, solves the problem of spectrum resource shortage to a great extent. Since the traditional Ad Hoc Networks) routing protocols do not take into account the constraints of spectrum resources and the temporal variability of spectrum resources, dynamic spectrum resource information must be considered for more accurate and effective routing. In order to solve the above problems, cognitive Radio Ad Hoc networks are formed by combining cognitive radio technology with ad hoc networks. Because of the dynamic change of communication opportunities among cognitive users in CRANET, when such opportunities arise, they are called CUs contacts, and if such contacts are predictable, then the CRANET is called contact predictable CRANET. Because the frequency band occupied by CRANET is dynamic and dynamic, it changes dynamically with the activity of primary users in CRANET, and the management of spectrum resource is the function of medium Access Control (MAC) layer of media access control. In order to make rational use of spectrum resources and improve the end-to-end throughput of CRANET, a cross-layer optimization method is introduced. However, the signal-to-noise ratio (SNR) and signal-to-noise ratio (SNR) queue length are the main factors affecting the throughput of CRANET. In this paper, the opportunistic routing and channel assignment problem with multi-parameter constraints such as degree of contact (SNR) in CRANET with contact predictability is studied in depth, and the evaluation index of opportunistic routing volatility is proposed. The main research results of this paper are as follows: (1) A predictive contact analysis model based on the metric of contact degree and continuous effective contact time is proposed. Contact, non-contact and effective contact are defined to describe the contact relationship between CUs and to define the degree of contact. The purpose of this paper is to estimate the probability of continuous effective contact between CUs. A continuous effective contact time metric is proposed to quantify the duration of communication between CUs. With the help of calculus principle and probability theory, the average continuous effective contact time between CUs is calculated. Simulation results show that the predictive contact analysis model can effectively predict the contact relationship between CUs. In order to determine the set of forwarding candidate CUs, a selection algorithm based on CUs queue length and contact degree constraints is proposed. An opportunistic routing strategy is designed to determine the forwarding candidate CUs and dynamically calculate and update the forwarding angle. Considering the parameters constraints such as the forwarding angle SNR and the number of channel interruptions, a joint opportunistic routing optimization algorithm for channel assignment and forwarding angle self-regulation is proposed. Based on the packet forwarding probabilistic constraint algorithm, the end-to-end throughput is maximized, and the volatility of opportunistic routing is evaluated by the volatility metric.
【学位授予单位】：河北工程大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN925

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