發(fā)布時間：2018-05-25 19:04

  本文選題：認知無線電 + 自組織網(wǎng)絡(luò)�。� 參考：《河北工程大學(xué)》2017年碩士論文

【摘要】：隨著無線通信技術(shù)的飛速發(fā)展,頻譜資源日趨緊張。而共享頻譜資源的認知無線電技術(shù)(Cognitive Radio,CR)的應(yīng)用很大程度上解決了頻譜資源短缺的問題。由于傳統(tǒng)的自組織網(wǎng)絡(luò)(Ad Hoc Networks)路由協(xié)議未考慮頻譜資源的約束以及頻譜資源的時變性,為了更準確有效地選路,必須考慮動態(tài)變化的頻譜資源信息。為了解決上述問題,將認知無線電技術(shù)與自組織網(wǎng)絡(luò)相結(jié)合,形成了認知自組織網(wǎng)絡(luò)(Cognitive Radio Ad Hoc Networks,CRANET)。由于CRANET中,認知用戶(Cognitive Users,CUs)間的通信機會是動態(tài)變化的,當這種機會出現(xiàn)時,就稱CUs間接觸,且這種接觸如果是可預(yù)測的,那么就將這種CRANET稱為接觸可預(yù)測的CRANET。由于接觸可預(yù)測的CRANET中頻譜具有動態(tài)性,CUs占用的頻段是隨主用戶(Primary Users,PUs)的活動而動態(tài)改變,且頻譜資源管理是媒體訪問控制層(Medium Access Control,MAC)的功能。為合理利用頻譜資源,提高接觸可預(yù)測CRANET端到端吞吐量,引入跨層優(yōu)化方法。然而,在接觸可預(yù)測的CRANET中,CUs間的接觸度、信噪比(Signal Noise Ratio,SNR)、CUs隊列長度是影響到端到端吞吐量的主要因素。本文在此背景下,深入研究了接觸可預(yù)測的CRANET中接觸度、SNR等多參數(shù)約束的機會路由和信道分配問題,并提出了機會路由波動性的評價指標。本文的主要研究成果如下:(1)提出了一種基于接觸度和連續(xù)有效接觸時間度量尺度的可預(yù)測接觸分析模型。定義了接觸、非接觸以及有效接觸,旨在描述CUs間的接觸關(guān)系,并定義了接觸度,旨在估計CUs間連續(xù)有效接觸的概率。提出了連續(xù)有效接觸時間度量尺度,用以量化CUs間通信的持續(xù)時間。借助微積分原理和概率論,計算出了CUs間連續(xù)有效接觸時間的平均值。仿真結(jié)果表明,可預(yù)測接觸分析模型可有效預(yù)測CUs間的接觸關(guān)系。(2)提出了一種轉(zhuǎn)發(fā)角自調(diào)節(jié)機會路由和信道分配聯(lián)合優(yōu)化策略。為了確定轉(zhuǎn)發(fā)候選CUs的集合,提出了一種基于CUs隊列長度和接觸度約束的選擇算法。設(shè)計了轉(zhuǎn)發(fā)角自調(diào)節(jié)的機會路由策略,用以確定轉(zhuǎn)發(fā)候選CUs以及動態(tài)計算和更新轉(zhuǎn)發(fā)角�？紤]了轉(zhuǎn)發(fā)角、SNR和信道中斷次數(shù)等參數(shù)約束,提出了信道分配和轉(zhuǎn)發(fā)角自調(diào)節(jié)的機會路由聯(lián)合優(yōu)化算法�；跀�(shù)據(jù)包轉(zhuǎn)發(fā)概率約束算法,實現(xiàn)了端到端吞吐量的最大化,并通過波動率度量尺度對機會路由波動性進行了評估。
[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.
【學(xué)位授予單位】：河北工程大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN925

【參考文獻】

相關(guān)期刊論文 前3條

1 李云;張智慧;黃巍;王勇;曹儐;;基于信道分配的多跳認知無線電網(wǎng)絡(luò)路由算法[J];系統(tǒng)工程與電子技術(shù);2013年04期

2 宋化;林小拉;;認知無線電網(wǎng)絡(luò)備份路由協(xié)議研究[J];小型微型計算機系統(tǒng);2010年11期

3 程賡;李昀照;劉威;程文青;楊宗凱;;認知無線電網(wǎng)絡(luò)路由及頻譜分配聯(lián)合策略研究[J];電子與信息學(xué)報;2008年03期

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本文編號：1934321