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数字通信 第五版(英文精简版)

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  • 大小:209.97 MB
  • 语言:中文版
  • 格式: PDF文档
  • 类别:电子信息
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关键词:精简   英文   普罗   数字通信   2012
资源简介
数字通信 第五版(英文精简版)
作 者: (美)普罗科斯,(美)萨利希 著,张力军 等改编
出版时间: 2012
内容简介
  《数字通信(第5版·英文精简版)》是在《数字通信(第5版)》的基础上,根据国内的实际教学情况进行精简和改编的。主要的精简原则为:保留信号传输理论内容,舍去信息传输理论内容,并以传统而经典的数字传输理论为主,无线通信为辅。改编的部分主要是根据国内实际教学的常用习惯来进行的。精简后的内容主要涵盖:确定与随机信号分析;数字调制方法;AWGN信道的最佳接收机;载波和符号同步;通过带限信道的数字通信;自适应均衡;多信道和多载波系统;数字通信用扩频信号;衰落信道:信道特征与信号传输;多天线系统。
目录
Chapter 1Introduction
 1.1 Elements of a Digital CommunicationSystem
 1.2 Communication Channels and TheirCharacteristics
 1.3 Mathematical Models for CommunicationChannels
 1.4 A Historical Perspective in the Development of
 Digitalommunications
Chapter 2 Deterministic and Random SignalAnalysis
 2.1 Representation of Bandpass Signals andSystems
 2.1–1 Representation of Bandpass Signals/ 2.1–2 Response of aBandpass System to a Bandpass Signal
 2.2 Signal Space Representation ofWaveforms
 2.2–1 Vector Space Concepts / 2.2–2 Signal Space Concepts / 2.2–3Orthogonal Expansions of Signals /2.2–4 Gram-SchmidtProcedure
 2.3 Some Useful RandomVariables
 2.4 RandomProcesses
 2.4–1 Wide-Sense Stationary Random Processes /2.4–2Cyclostationary Random Processes
 2.5 Series Expansion of RandomProcesses
 2.5–1 Sampling Theorem for Band-Limited RandomProcesses /2.5–2 TheKarhunen-Lo`eve Expansion
 2.6 Bandpass Stationary StochasticProcesses
 Problems
Chapter 3 Digital ModulationSchemes
 3.1 Representation of Digitally ModulatedSignals
 3.2 Memoryless ModulationMethods
 3.2–1 Pulse Amplitude Modulation (PAM) / 3.2–2 Phase Modulation /3.2–3 Quadrature Amplitude Modulation /3.2–4 MultidimensionalSignaling
 3.3 Signaling Schemes withMemory
 3.3–1 Continuous-Phase Frequency-Shift Keying(CPFSK) /
 3.3–2 Continuous-Phase Modulation (CPM)
 3.4 Power Spectrum of Digitally ModulatedSignals
 3.4–1 Power Spectral Density of a Digitally ModulatedSignalwith
 Memory / 3.4–2 Power Spectral Density of LinearlyModulated
 Signals / 3.4–3 Power Spectral Density ofDigitally Modulated
 Signals with Finite Memory / 3.4–4Power Spectral Density of
 Modulation Schemes with a MarkovStructure / 3.4–5 Power
 Spectral Densities of CPFSK and CPM Signals
 Problems
Chapter 4 Optimum Receivers for AWGNChannels
 4.1 Waveform and Vector ChannelModels
 4.1–1 Optimal Detection for a General Vector Channel
 4.2 Waveform and Vector AWGNChannels
 4.2–1 Optimal Detection for the Vector AWGN Channel /4.2–2Implementation of the Optimal Receiver for AWGN Channels / 4.2–3 AUnion Bound on the Probability of Error of Maximum LikelihoodDetection
 4.3 Optimal Detection and Error Probability for Band-Limited
 Signaling
 4.3–1 Optimal Detection and Error Probability for ASK or
 PAM Signaling / 4.3–2 Optimal Detection and ErrorProbability
 for PSK Signaling / 4.3–3 Optimal Detection and ErrorProbability
 for QAM Signaling / 4.3–4 Demodulation and Detection
 4.4 Optimal Detection and Error Probability forPower-Limited
 Signaling
 4.4–1 Optimal Detection and Error Probability for Orthogonal
 Signaling / 4.4–2 Optimal Detection and Error Probabilityfor
 Biorthogonal Signaling / 4.4–3 Optimal Detection and Error
 Probability for Simplex Signaling
 4.5 Optimal Detection in Presence of Uncertainty:Noncoherent
 Detection
 4.5–1 Noncoherent Detection of Carrier Modulated Signals /4.5–2Optimal Noncoherent Detection of FSK Modulated Signals / 4.5–3Error Probability of Orthogonal Signaling with NoncoherentDetection / 4.5–4 Probability of Error for Envelope Detection ofCorrelated Binary Signals /4.5–5 Differential PSK (DPSK)
 4.6 A Comparison of Digital SignalingMethods
 4.6–1 Bandwidth and Dimensionality
 4.7 Lattices and Constellations Based onLattices
 4.7–1 An Introduction to Lattices / 4.7–2 Signal Constellationsfrom Lattices
 4.8 Detection of Signaling Schemes withMemory
 4.8–1 The Maximum Likelihood Sequence Detector
 4.9 Optimum Receiver for CPMSignals
 4.9–1 Optimum Demodulation and Detection of CPM /4.9–2 Performanceof CPM Signals / 4.9–3 Suboptimum Demodulation and Detection of CPMSignals
 Problems
Chapter 5 Carrier and SymbolSynchronization
 5.1 Signal ParameterEstimation
 5.1–1 The Likelihood Function / 5.1–2 Carrier Recovery and
 Symbol Synchronization in Signal Demodulation
 5.2 Carrier PhaseEstimation
 5.2–1 Maximum-Likelihood Carrier Phase Estimation /5.2–2 ThePhase-Locked Loop / 5.2–3 Effect of AdditiveNoise on the PhaseEstimate / 5.2–4 Decision-Directed Loops / 5.2–5Non-Decision-Directed Loops
 5.3 Symbol TimingEstimation
 5.3–1 Maximum-Likelihood Timing Estimation /5.3–2Non-Decision-Directed Timing Estimation
 5.4 Joint Estimation of Carrier Phase and SymbolTiming
 5.5 Performance Characteristics of MLEstimators
 Problems
Chapter 6 Digital Communication Through Band-LimitedChannels
 6.1 Characterization of Band-LimitedChannels
 6.2 Signal Design for Band-LimitedChannels
 6.2–1 Design of Band-Limited Signals for No Intersymbol
 Interference—The Nyquist Criterion / 6.2–2 Design of Band-LimitedSignals with Controlled ISI—Partial-Response Signals / 6.2–3 DataDetection for Controlled ISI /6.2–4 Signal Design for Channels withDistortion
 6.3 Optimum Receiver for Channels with ISI andAWGN
 6.3–1 Optimum Maximum-Likelihood Receiver /6.3–2 A Discrete-TimeModel for a Channel with ISI /6.3–3 Maximum-Likelihood SequenceEstimation (MLSE)
 for the Discrete-Time White Noise Filter Model
 6.4 LinearEqualization
 6.4–1 Peak Distortion Criterion /6.4–2 Mean-Square-Error (MSE)Criterion /
 6.4–3 Performance Characteristics of the MSE Equalizer /6.4–4Fractionally Spaced Equalizers /6.4–5 Baseband and Passband LinearEqualizers
 6.5 Decision-FeedbackEqualization
 6.5–1 Coefficient Optimization /6.5–2 Performance Characteristicsof DFE
 6.6 Reduced Complexity MLDetectors
 Problems
Chapter 7 AdaptiveEqualization
 7.1 Adaptive LinearEqualizer
 7.1–1 The Zero-Forcing Algorithm /7.1–2 The LMS Algorithm /7.1–3Convergence Properties of the LMS Algorithm /7.1–4 Excess MSE dueto Noisy Gradient Estimates /7.1–5 Accelerating the InitialConvergence Rate
 in the LMS Algorithm / 7.1–6 Adaptive Fractionally SpacedEqualizer—The Tap Leakage Algorithm /7.1–7 An Adaptive ChannelEstimator for ML
 Sequence Detection
 7.2 Adaptive Decision-FeedbackEqualizer
 7.3 Recursive Least-Squares Algorithms for AdaptiveEqualization
 7.3–1 Recursive Least-Squares (Kalman) Algorithm /7.3–2 LinearPrediction and the Lattice Filter
 Problems
Chapter 8 Multichannel and MulticarrierSystems
 8.1 Multichannel Digital Communications in AWGNChannels
 8.1–1 Binary Signals / 8.1–2 M-ary Orthogonal Signals
 8.2 MulticarrierCommunications
 8.2–1 Single-Carrier Versus Multicarrier Modulation /8.2–2Capacity of a Nonideal Linear Filter Channel /8.2–3 OrthogonalFrequency Division Multiplexing (OFDM) /8.2–4 Modulation andDemodulation in an OFDM System /
 8.2–5 An FFT Algorithm Implementation of an OFDM System /8.2–6Spectral Characteristics of Multicarrier Signals /8.2–7 Bit andPower Allocation in Multicarrier Modulation /8.2–8 Peak-to-AverageRatio in Multicarrier Modulation /8.2–9 Channel CodingConsiderations in Multicarrier Modulation
 Problems
Chapter 9 Spread Spectrum Signals for DigitalCommunications
 9.1 Model of Spread Spectrum Digital CommunicationSystem
 9.2 Direct Sequence Spread SpectrumSignals
 9.2–1 Error Rate Performance of the Decoder /9.2–2 SomeApplications of DS Spread Spectrum Signals /9.2–3 Effect of PulsedInterference on DS Spread Spectrum Systems / 9.2–4 Excision ofNarrowband Interference in DS Spread Spectrum S
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