数字通信(第五版 英文精简版) pdf epub mobi txt 电子书 下载 2025

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[美] 普罗科斯，[美] 萨利希，张力军 等改编 著

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出版社： 电子工业出版社

ISBN：9787121153259

商品编码：29667733288

包装：平装

出版时间：2012-01-01

基本信息

书名：数字通信(第五版 英文精简版)

定价：59.00元

作者：(美)普罗科斯,(美)萨利希,张力军 等改编

出版社：电子工业出版社

出版日期：2012-01-01

ISBN：9787121153259

字数：

页码：

版次：1

装帧：平装

开本：

商品重量：0.4kg

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内容提要

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　　本书是在《数字通信（第五版）》的基础上，根据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*信号分析；数字调制方法；AWGN信道的*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

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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 Systems / 9.2–5Generation of PN Sequences
　9.3 Frequency-Hopped Spread SpectrumSignals
　9.3–1 Performance of FH Spread Spectrum Signals in an
　AWGN Channel / 9.3–2 Performance of FH Spread Spectrum
　Signals in Partial-Band Interference / 9.3–3 A CDMA System
　Based on FH Spread Spectrum Signals
　9.4 Other Types of Spread SpectrumSignals
　Problems
Chapter 10 Fading Channels : Characterization and
　Signaling
　10.1 Characterization of Fading MultipathChannels
　10.1–1 Channel Correlation Functions and Power Spectra /
　10.1–2 Statistical Models for Fading Channels
　10.2 The Effect of Signal Characteristics on the Choice of aChannelModel
　10.3 Frequency-Nonselective, Slowly FadingChannel
　10.4 Diversity Techniques for Fading MultipathChannels
　10.4–1 Binary Signals / 10.4–2 Multiphase Signals /10.4–3

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