matlab 实现线性调频信号以及分析处理
里面有关于实现matlab的算法以及分析处理山国科技记文在线分布的时频平面作直线积分投影的变换,统称对信号作变换在分布的时频平面里惯用轴的截距和斜率为参数表小直线。因此,当需要沿作直线积分时,可将积分路径(直线)的参数(u,a)替换成()日两对参数之间的关系为:m=-cot,w=! sina。若求信号的变换,并以参数表示积分路径,则有:D.a=PQ线w, (t, wB u-u du∫r(,n)ma(w-mn-m)nh∫m(,w[一(m+motcw lt, wo +mt dt/sinaWo=u/sina上式表明,若是参数为和的信号,则积分值最大;而当参数偏离与或时,积分值迅速减小,即对‘定的信号,其变换会在对应的参数处呈现尖峰。我们自然会想到:多分量的信号的特性在平面里更加突出。即表现为各个尖峰,因而更有利于区别交叉项和噪声。利用变换一定能够获得更好的性能。作为时频分析方法之一,分数阶傅里叶变换ˉ与分布()变换()分别有着一定的数学关系,借助它们的联系,可进一步说明分数阶傅里叶变换的物理意义。信号的分布函数的定义为t+=xtde作为能量型时频表示满足许多期望的数学性质,这里给出其边缘特性X tt wdvXw=wtwat对WD旋转C角度,即对分布实施变换,其结果是RWIW=∫f山国技记文在线而信号的阶分薮阶傅里叶变换X。t的就是将信号的旋转c角度,即对于分数阶傅里叶变换只有旋转不变性,所以有X u= wtP可以看出,对时间轴与频率轴的积分分别是信号在时刻的瞬时功率和信号在频率的谱密度,而信号的对与时间成c角度的轴的积分投影对应着角度为a的分数阶傅里叶变换的幅度平方,这进步从能量的角度说明分数阶傅里叶变换作为广义傅里叶变换的含义。正弦信号在时频平面是一条平行于时间轴的直线,即它的频率不随时间变化,可视为旋转角度为°的完全时间域表示;冲击朕数在时频平面是一条平行于频率轴的直线可视为旋转角度为°的完全频率域表示;信号在时频平面是一条斜率为调频率的直线,当该信号的某一角度的分数阶傅里叶变换与其调频率一致时,在无限长度的理想情况下,表现为幅度为无穷大的冲击,在信号长度有限的情况下,其分数阶傅里卟变换呈现极大值这就是信号在分数阶傅里叶变换域的特点。离散 Chirp fourier变换是最近提出的一种有效的线性调频信号检测技术,它 Fourier变换的一种推广形式,可同时匹配 chirp信号的中心频率和调频率。本文利用修正离散Chirp- Fourie交换( MDCFT)实现干扰信号的检测和参数估计,从而实现对干扰的自适应抑制。分析和仿真表明,该方法可对FM干扰有着极好的抑制效果;同时,由于 Chirp- Fourie变换是维的线性变换,可借助快速傅里叶变换(FFT〕实现,与基于WVD的算法相比,不仅避免了交叉项十扰,而且降低了计算的复杂度,其实现更为简使3.基于Mat1ab的上机仿真过程及结果分析3.1对单分量信号的仿真及结果分析():输入解析信号为x()=eb的分布:40,图单分量信号的分布山国科技论文在线在上述解析信号中加入噪声后,用分布分析其性能图加入噪声的单分量信号的分布由图可以看出实际结果与前面的理论推导致。在实际应用中,信号长度总是有限长的,此时分布呈背鳍状。由图可以得到变换对噪声不太敏感,时频变换后信噪比较高。但当干扰的幅度大到一定程度时,变换的结果会严重变差,甚至分析不出结果。():前两个图是输入解析信号为x(t)=em的变换,后两个图是在这个解析信号中加入噪声以后用变换对其进行的分析:400C501m01501020100150图单分量信号的变换由理论分析可知,当旋转角度与线性调频信号的斜率相這应时,变换将出现一个峰值。这个分析在图中得到了证实。():图前两个图是输入解析信号为x()=e的分数阶傅里叶变换,后两个图是在山国科技论文在线这个解析信号中加入噪声以后用分数阶傅甲叶变换对其进行的分析:分数阶傅甲叶变换变换与变换的紧密联系在图和图的仿真中也可以得到证实HOD50图单分量信号的分数阶傅里叶变换():图的前两个图是输入中心频率是,调频率是的单分量线性调频信号后的Chirp- Fourier变换,后两个图是在这个信号中加入噪声以后用 Chirp-Fourier变换对其进行的分析。通过这个仿真,还将证明一个重要性质: Chirp- Fourier变换可同时匹配线性调频信号的中心频率和调频率的82a图单分量信号的 Chirp fourier变换比较结论:从以上几个仿真图形可以看出,对单分量的信号而言,上述几个变换山国科技论文在线都有非常好的时频聚集性,特别是分布与理论结果完仝一致。在抗噪声方面,对比几个图可知,变换和 Chirp- Fourier变换要比分布和分数阶傅里叶变换吏好。而对于分数阶傅里叶变换和分布,分数阶傅里叶变换的抗噪声性能要好3.2对多分量信号的仿真及结果分析个多分量的线性调频信号的D15020心Dm图多分量信号的一个多分量的线性调频信号的变换50.540多分量信号的变换山国科技论文在线个多分量的线性调频信号的分数阶傅甲叶变换:图多分量信号的分数阶傅里叶变换个多分量的线性调频信号(含两个分量,中心频率和调频率分别为k=)的 Chirp- Fourier变换50299,Q图多分量信号的 Chirp-fourier变换比较结论:从以上四个图可以看出,对于多分量信号,分布由于存在交叉项,时频面模糊不清,而其他三种变换则可以检测到两个信号。从图中还可以看到,Chirp- Fourier变换的效果是最好的。而且我们从图中还可以清楚地看到线性调频信号的中心频率和调频率。4LFM信号的应用线性词频)信号广泛地应用于雷达、声纳和通信等信息系统中。在这类系统中,信号的检测与参数估计是个重要的研究课题,受到特别的关注。下面给出一个基于FRT的MTD雷达信号处理过程的防真实例。假设有一个运动目标,回波信号为Stjn∫t-jwt+nt,其中nt为杂波信号,信号参数为nt是均值为零,方差为的高斯白噪声,信噪比为,观测时间为,采样频率为采样点数为N采用分数阶域的扫描上算法对该冋波信号作计算机仿真,仿真结果如图所从图中可以清楚看到一个LFM信号的存在,而闬目标的峰值非常突出,受杂波的影响相对较小。因此采用FRT的MTD雷达的抗干扰能力较强。另外由于日标的特征非常明显,可以通过适当提高杂波门限的方法来减小虚警概率山国科技论文在线图基于ⅣRFT的MTD雷达信号处理过程的防真5结束语非平稳信号是现代信号处理的主要研究对象之一,对其有很多种理论分析方法。本文介绍的分布,变换,分数阶傅里叶变换,变换是其中比较常用和重要的几种。本文对这几种变换做了初步的介绍,进而对它们进行了一些比较这有助于进一步了解各种变换的性能和作信号分析时选择合适的变换。时频分布之所以受到很多研究人员和信号处理领域的工程人员的重视,是因为它有很多传统傅立叶变换所不具备的性质。由时频分析的定义可知时频表示能给出信号在时域和频域的信息。经过儿年的发展,时频分析理论趋于成熟,并遂渐在实际应用中崭露头角,近年来已在实际的非平稳信号处理中获得了十分广泛的应用。如:信号检测与分类,吋频域滤波,信号综合,系统辩识和谱估计等。在的期刊和国际会议上发表的与采用时频工具处理非平稳干扰有关的论文及研究报告共有余篇,其中以美国大学教授的成果最为显著。时频分析是一个前景很广阔的研究方向,虽然取得了一定的成就,但理论体系尚不十分完备,需要进一步的发展。参考文献[1ˉ张贤达,保铮《非平稳信号分析与处理》[M1998年9月第1版国防工业出版社[2ˉ沈民奋,孙丽莎《现代随机信号与系统分析》M年月第版科学出版社[3丁凤芹,曹家麟《基丁分数阶傅里叶变换的多分量 Chirp信号的检测与参数估计》《语音技术》2004年第1期[4_孙泓波,郭欣,顾红,苏上民,刘国岁《修正 Chirp- Flourier变换及其在SAR运动目标检测中的应用》《电子学报》2003年第1期山国技记文在线[5董永强,陶然,思永,王越《基丁分数阶傅里叶变换的SAR运动目标检测与成像》《兵工学报》1999年第2期L6_陶然,齐林,王越《分数阶 Fourier变奂的原理与应用》LM」2004年8月第1版清华大学出版社[7董永强,陶然,周思永,王越《含未知参数的多分量 chirp信号的分数阶傅里叶分析》《北京理工大学学报》1999年第5期[8ˉ陈辉,王永良《利用离散 Chirp- Flourier变换技术估计调频信号参数》《空军雷达学院学报》2001年第1期[9ˉ齐林,穆晓敏,朱春华《系统中基于 Chirp- Fourier变换的扫频干扰抑制算》《电讯技术》年第期[10]李勇,徐震等《 MATLAB辅助现代工程数字信号处理》[M2002年10月鷥1版西安电子科技人学出版社「111胡昌华,周淘,夏启兵,张伟《基于 MATLAB的系统分析与设计—时频分析》「M12001年7月第1[2]干小宁,许家栋《离散调频-傅里叶变换及其作雷达成像中的应用》《系统工稈与电子技术》2002年第3期
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Key Technologies for 5G Wireless Systems
5G无线通信系统关键技术（剑桥大学出版社） 2017年出版 对于5G所有最新技术进行了详细说明 很全的工具书Key Technologies for5G Wireless SystemsVINCENT W. S, WONGUniversity of British ColumbiaROBERT SCHOBERUniversity of Erlangen-NurembergDERRICK WING KWAN NGUniversity of New South WalesLI-CHUN WANGNational Chiao-Tung University即CAMBRIDGEUNIVERSITY PRESSCAMBRIDGEUNIVERSITY PRESSUniversity Printing House. Cambridge CB2 SBS. United KindomOne Liberty Plaza, 20h Floor New York, NY I(H0X, USA477 williamstown Road, port Melbourne, yic 3207 australia48424, 2nd Floor, Ansar Rod, Daryaganj. Delhi- I l4XH2, India79 Anson Road, #o6-(/ 00, Singapore 079%MCambridge University Press is part of the Lniversity of CambridgeIt furthers the University s mission by disseminating knowledge in the pursuit ofeducation, leaming and research at the highest international levels of excellence.www.cermbrid吧eInformtiononthistitlewww.cambridgeorg/978110713241810,1017③781316771655C Cambridge University Press 2017This puhlication is in copyright. Subjcct to sututonry exceptionand to the provisions of relewant collective licensing agreementsno reproduction of any part may take place without the writtenpermission of Cutmbridgre University Press.First published 2(117Printed in the United Kingdom by TJ International Ltd. Padstow, CornwallA catalogue recor for this pudlieafiove is aailable fromm the British LibraryLibrary of Congress Cataloging- in Pi hlicaiomz dataNames: Wong, Vincent W.S., editorTitle: Key technologies for 5G wireless systems/edited by Vincent W.S. Wong [and 3 otherOther titles key technologies for five g wireless svstemsDescription: Carmbrisige: New York, NY: Cambridge Lniversity Press, 2017.Identifiers: l CCN 2016045220)1 ISBN 9781 172418 (hardback)Subjects: LCSH: Wireless communication systems, I Machine-to-machinecommunications. Internet of things.Classitication: LCC TKs1032K49 2(17 DDC 621.38450-dc23LcrecordavailaBleathttps://lccnioc-gov/2016m5220)ISBN 978-1-107-17241- HardbackCambridge University Press has no responsibility for the persistence or accuracy ofURLs for extermal or third-party Internet websites referred to in this puhlication,and does not guarantee that any content on such websites is, or will remainaccurate of appropriateContentsList of Contributorspage xvIPrefaceKXIOverview of New Technolog ies for 5G SystemsVincent W S, Wong, Robert Schober, Derrick Wing Kwan Ng, and Li-Chun Wang1.1 Introduction1.2 Cloud Radio Access Networks1.3 Cloud Computing and Fog Computing1. 4 Non-orthogonal Multiple Access1. 5 Flexible Physical Layer Design334.4671. 6 Massive MIMo1. 7 Full-Duplex Communications1. 8 Millimeter wave1.9 Mobile Data Offloading, LTE-Unlicensed, and Smart Data Pricing131. 10 IoT M2M. and D2D1. I1 Radio Resource Management, Interference Mitigation, and Caching61. 12 Energy Harvesting Communications1. 13 Visible Light Communication19Acknowledgments20ReferencesPart I Communication Network Architectures for 5G Systems25Cloud Radio Access Networks for 5G Systems27Chih-Lin I, Jinn Huang, Xueyan Husang, Rongwved Ren, and Yami. Chen2.1 Rethinking the Fundamentals for 5G Systems272 User- Centric Networks2923 C-RAN Basics292.3.1 C-RAN Challenges Toward SGI302.4 Next Generation Fronthaul Interface (NGFI: The FH Solutionfor SGC-RAN312. 4.1 Proof-of-Concept Development of NGFI33Contents2.5 Proof-of-Concept Verification of Virtualized C-RAN2.5.1 Data packets3725.2 Test Procedure382.5.3 Test Results392. 6 Rethinking the Protocol Stack for C-RAN2.6.1 Motivation402.6.2 Multilevel Centralized and Distributed Protocol Stack402.7 Conclusion45AcknowledgmentsReferencesFronthaul-Aware Design for Cloud Radio Access Networks48Liang Liu, Wei Yu, and Osvaldo Simeone3. 1 Introduction483.2 Fronthaul-Aware Cooperative Transmission and Reception493. 2.1 Uplink513.2.2 Downlink573.3 Fronthaul-Aware Data Link and Physical layers61.3. I Uplink633.3.2 Downlink693.4 Conclusion73Acknowledgments74References74MobEdge computing76Ben Liang4.1 Introduction764.2 Mobile Edge Computing774.3 Reference architecture794.4 Benefits and Application Scenarios804 4.1 User-Oriented Use cases4. 4.2 Operator-Oriented Use Ca814 5 Research challenges824.5.1 Computation Offloading824.5.2 Communication Access to Computational Resources834.5.3 Multi-resource Schedulin844.5 4 Mobility Management854.5.5 Resource Allocation and Pricing4.5.6 Network functions virtualization864.5, 7 Security and Pri864.5.8 Integration with Emerging Technologies874.6 Conclusion88ReferencesContentsDecentralized Radio Resource Management for Dense HeterogeneousWireless networksAbolfazl Mehhodniya and Fumiyuki Adach5.1 Introduction925.2 System Model935.2.1 SINR Expression5.2.2 Load and Cost Function Expressions955.3 Joint BSCSA/UECSA ON/OFF Switching Scheme965.3.1 StrateTy Selection and Beacon Transmission53.2 UE AssocIation5.3.3 Proposed Channel Segregation Algorithms985.3.4 Mixed-Strategy Update3.4 Computer Simulation5.5 Conclusion104Acknowledgments04References105Part ll Physical Layer Communication Techniques107Non-Orthogonal Multiple Access(NOMA)for 5G Systems109Wei Llang, Zhiguo Ding, and H. Vincent Poor6.1 Introduction1106.2 NOMA in Single-Input Single-Output(SISO)Systems1126.2.1 The basics of nomaI126. 2. 2 Impact of User Pairing on NOMA136.2,3 Cognitive Radio Inspired NOMA6. 3 NOMA in MIMO Systems1206.3.1 System Model for MIMO-NOMA Schemes1216.3.2 Design of Precoding and Detection Matrices with Limited CSIT 1236.3.3 Design of Precoding and Detection Matrices with Perfect CSIT 1266.4 Summary and Future Directions128ReferencesFlexible Physical Layer Design133Maximilian Matthe, Martin Danneberg, Dan Zhang, and Gerhard Fettweis7.1 Introduction1337. 2 Generalized Frequency Division Multiplexing357.3 Software-Defined waveform1377. 3. 1 Time Domain Processing1387.3.2 Implementation Architecture1387.4 GFDM Receiver Design14174 Synchronization unit1427. 4.2 Channel Estimation Unit1474.3 MIMo-GFDM Detection Unit145Contents7.5 Summary and Outlook147Acknowledgments148References488Distributed Massive MIMO in Cellular Networks15IMichail Matthaiou and Shi Jin8. I Introduction15l8. 2 Massive MIMO: Basic Principles1528.2.1 Uplink Downlink Channel Models1538.2.2Favorable Propagation1548.3 Performance of Linear Receivers in a Massive MIMO Uplink1548.4 performance of linear precoders in a massive mimo downlink1578. s Channel estimation in massive mimo systems1588.5.1 Uplink Transmission1598.5.2 Downlink Transmission1608.6 Applications of Massive MIMO Technology1618.6.1 Full-Duplex Relaying with Massive Antenna Arrays1618.6.2 Joint Wireless Information Transfer and Energy Transfer forDistributed massive mimo1638.7 Open Future Research Directions1678. 8 Conclusionl68References169Full-Duplex Protocol Design for 5G Networks172Tanelf Ahonen and Risto wichman9.1 Introduction1729. 2 Basics of Full-Duplex Systems1739.2.1 In-Band Full-Duplex Operation Mode1739.2.2 Self-Interference and Co-channel Interference1749.2.3 Full-Duplex Transceivers in Communication Links1759. 2. 4 Other Applications of Full-Duplex Transceivers1789.3 Design of Full-Duplex Protocols1799.3, 1 Challenges and Opportunities in Full-Duplex Operation1799.3.2 Full-Duplex Communication Scenarios in 5G NetworksR9.4 Analysis of Full-Duplex Protocols1829.4.1 Operation Modes in Wideband Fading Channels1829. 4, 2 Full- Duplex Versus Half-Duplex in Wideband Transmission1849.5 Conclusion1849.5.1 Prospective Scientific Research DirectionsI849.5.2 Full-Duplex in Commercial 5G Networks185RLItrtncekl8610Millimeter Wave Communications for 5G Networks188Jiho Song, Miguel R Castellanos, and David J. LoweContentsⅸx10.1 Motivations and Opportunities18810.2 Millimeter Wave Radio Propagation18910. 2.1 Radio Attenuation1890. 2. 2. Free-Space Path LOSs19I10.2.3 Severe shadow19310.2 4 Millimeter Wave Channel model19310.2.5 Link Budget Analysis19410.3 Beamforming Architectures19510.3, Analog beamforming solutions19610.3.2 Hybrid Beamforming Solutions20010.3.3 Low-Resolution Receiver Architecture2010.4 Channel Acquisition Techniques20110.4.1 Subspace Sampling for Beam Alignment20210.4.2 Compressed Channel estimation Techniques20510.5 Deployment Challenges and Applications20710.5.1 EM Exposure at Millimeter Wave Frequencies20710.5.2 Heterogeneous and Small-Cell Networks208Acknowledgments209References209Interference Mitigation Techniques for Wireless Networks214Koralia N Pappi and George K, Karag annidis1 1.1 Introduction21411.2 The Interference Management Challenge in the 5G vision21411. 2. 1 The 5G Primary Goals and Their Impact on Interference2141 1.2.2 Enabling Technologies for Improving Network Efficiencyand Mitigating Interference21611.3 Improving the Cell-Edge User Experience: Coordinated Multipoint218I 1.3.1 Deployment Scenarios and Network Architecture2181 13. 2 CoMP Techniques for the Uplink22011.3.3 CoMP Techniques for the Downlink2211 1.4 Interference Alignment: Exploiting Signal Space Dimensions2231 1.4.1 The Concept of Linear Interference Alignment224L1. 4.2 The Example of the X-Channel225I 1. 4.3 The K-User Interference Channel and Cellular NetworksAsymptotic Interference Alignment22611.4.4 Cooperative Interferenee Networks22711.4.5 Insight from IA into the Capacity Limits of Wireless Networks 22711.5 Compute-and-Forward Protocol: Cooperation at the ReceiverSide for the Uplink22811.5.1 Encoding and Decoding of the CoF Protocol22811.5.2 Achievable-Rate Region and Integer Equation Selection23011.5.3 Advantages and Challenges of the CoF Protocol232IL6 Conclusion233References233
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