頻譜資源是無線網(wǎng)絡(luò)中的一個主要組成部分,對這種有限的資源持續(xù)且固定的分配會導致頻帶的耗盡。因此,這種資源的共享能力將持續(xù)作為一個主要的研究方向,對研究人員有莫大的吸引力。近來,新興的對現(xiàn)有資源的擴展、應用和服務(wù)例如運載性自組織網(wǎng)絡(luò),在大多數(shù)情況下對可利用頻帶的需求越來越大。因此,對頻譜資源低效的利用以及其匱乏的現(xiàn)狀促生了一個新的無線通信范例,在這個范例中可用的頻譜資源能被機會性地調(diào)用。且在該范例中,可靠通信將在需要時被提供,這時,無線電頻譜能得到更有效率的利用,這確保了未來可能出現(xiàn)的服務(wù)能得到符合其要求的頻譜。在認知無線電的循環(huán)中,一個認知無線電的監(jiān)聽器會捕捉到頻帶信息并探測到可用的頻譜空間,頻譜空間通過頻譜感知泄露信息的特點可以被忽略。作為認知無線電的一個關(guān)鍵階段,頻譜探測的目的在于判斷一個頻譜的特定成分是否被占用--即區(qū)分PU（主用戶）的存在或者缺失。在認知無線電系統(tǒng)中的認知用戶,也叫次級用戶,將被要求傳輸不會妨害主用戶傳輸?shù)男畔�。這主要涉及到PU（主用戶）通過利用其中一個頻譜探測技術(shù)來識別。由此主用戶在使用自己的頻譜的時候,其使用權(quán)能得到保護,同時調(diào)用沒有主用戶的頻帶。當前,認知... 

【文章來源】：湖南大學湖南省 211工程院校 985工程院校 教育部直屬院校

【文章頁數(shù)】：110 頁

【學位級別】：碩士

【文章目錄】：
ABSTRACT
中文摘要
ABREVIATIONS
CHAPTER1:INTRODUCTION
    1.1 Background
    1.2 Spectrum Scarcity in VANETs
    1.3 Motivation
    1.4 Related work
    1.5 Contribution
    1.6 Organization of thesis
CHAPTER2:VEHICULAR AD HOC NETWORK AND COGNAITIVE RADIO OVERVIEW
    2.1 Introduction
    2.2 Mobile Wireless Ad-hoc Networks（MANETs）
    2.3 Vehicular Ad hoc NETworks（VANETs）
        2.3.1 VANET Architecture
        2.3.2 VANET applications
        2.3.3 VANET Regulation
        2.3.4 Routing Protocol
        2.3.5 VANET security
    2.4 Cognitive Radio Overview
        2.4.1 Introduction
        2.4.2 Cognitive radio fundamentals
        2.4.3 Spectrum Access Model
            2.4.3.1 Dynamic Spectrum Access
        2.4.4 Cognitive Radio Functions
        2.4.5 Spectrum Sensing in Cognitive Radio
        2.4.6 Spectrum Sensing Techniques
            2.4.6.1 Non-cooperative detection
                2.4.6.1.1 Energy Detection
                2.4.6.1.2 Matched Filter Detection
                2.4.6.1.3 Cyclostationary Feature Detection
    2.5 Conclusion
CHAPTER3:COGNITIVE RADIO IN VEHICULAR AD HOC NETWORK AND COOPERATIVE SENSING
    3.1 Introduction
    3.2 Cognitive radio in Vehicular ad-hoc network Motivation
        3.2.1 More spectrum holes on rural and highway
        3.2.2 Resiliency
        3.2.3 Sufficient Resources in vehicles
        3.2.4 Data Offloading
    3.3 CR-VANET Spectrum Sensing
        3.3.1 Per-vehicle Sensing Scheme
        3.3.2 Geo-location Based Sensing
        3.3.3 Cooperative Based sensing scheme
    3.4 Cooperative Spectrum Sensing
        3.4.1 Cooperative spectrum sensing topologies
        3.4.2 Centralized cooperative spectrum sensing
        3.4.3 Reporting schemes
            3.4.3.1 Hard Fusion
            3.4.3.2 Soft Fusion
    3.5 CSS Selection
        3.5.1 The proposed algorithm
    3.6 Conclusions
CHAPTER4:SIMULATION
    4.1 Introduction
    4.2 Model
        4.2.1 Signal Detection Probability
        4.2.2 Influence of spatial correlation on detection probabilities
    4.3 Simulation Results
    4.4 Simulation Results for CCSV selection algorithm
CHAPTER5:CONCLUSION AND FUTURE WORK
    5.1 Conclusion
    5.2 Future work
ACKNOWLEDGEMENTS
REFERENCES



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