Efnisyfirlit

• Cover
• Half-title page
• Title page
• Copyright page
• Dedication
• Contents
• Preface
• Acknowledgements
• 1. Introduction
  • Chapter plan
  • 1.1 Analog or digital?
    • 1.1.1 Analog communication
    • 1.1.2 Digital communication
    • 1.1.3 Why digital?
    • 1.1.4 Why analog design remains important
  • 1.2 A technology perspective
  • 1.3 The scope of this textbook
  • 1.4 Why study communication systems?
  • 1.5 Concept summary
  • 1.6 Notes
• 2. Signals and systems
  • Chapter plan
  • 2.1 Complex numbers
  • 2.2 Signals
  • 2.3 Linear time-invariant systems
    • 2.3.1 Discrete-time convolution
    • 2.3.2 Multi-rate systems
  • 2.4 Fourier series
    • 2.4.1 Fourier-series properties and applications
  • 2.5 The Fourier transform
    • 2.5.1 Fourier-transform properties
    • 2.5.2 Numerical computation using DFT
  • 2.6 Energy spectral density and bandwidth
  • 2.7 Baseband and passband signals
  • 2.8 The structure of a passband signal
    • 2.8.1 Time-domain relationships
    • 2.8.2 Frequency-domain relationships
    • 2.8.3 The complex-baseband equivalent of passband filtering
    • 2.8.4 General comments on complex baseband
  • 2.9 Wireless-channel modeling in complex baseband
  • 2.10 Concept summary
  • 2.11 Notes
  • 2.12 Problems
  • Software Lab 2.1: signals and systems computations using MATLAB
  • Software Lab 2.2: modeling carrier-phase uncertainty
  • Software Lab 2.3: modeling a lamppost-based broadband network
• 3. Analog communication techniques
  • Chapter plan
  • 3.1 Terminology and notation
  • 3.2 Amplitude modulation
    • 3.2.1 Double-sideband (DSB) suppressed carrier (SC)
    • 3.2.2 Conventional AM
    • 3.2.3 Single-sideband modulation (SSB)
    • 3.2.4 Vestigial-sideband (VSB) modulation
    • 3.2.5 Quadrature amplitude modulation
    • 3.2.6 Concept synthesis for AM
  • 3.3 Angle modulation
    • 3.3.1 Limiter–discriminator demodulation
    • 3.3.2 FM spectrum
    • 3.3.3 Concept synthesis for FM
  • 3.4 The superheterodyne receiver
  • 3.5 The phase-locked loop
    • 3.5.1 PLL applications
    • 3.5.2 A mathematical model for the PLL
    • 3.5.3 PLL analysis
  • 3.6 Some analog communication systems
    • 3.6.1 FM radio
    • 3.6.2 Analog broadcast TV
  • 3.7 Concept summary
  • 3.8 Notes
  • 3.9 Problems
  • Software Lab 3.1: amplitude modulation and envelope detection
  • Software Lab 3.2: frequency-modulation basics
• 4. Digital modulation
  • Chapter plan
  • 4.1 Signal constellations
  • 4.2 Bandwidth occupancy
    • 4.2.1 Power spectral density
    • 4.2.2 The PSD of a linearly modulated signal
  • 4.3 Design for bandlimited channels
    • 4.3.1 Nyquist’s sampling theorem and the sinc pulse
    • 4.3.2 The Nyquist criterion for ISI avoidance
    • 4.3.3 Bandwidth efficiency
    • 4.3.4 Power–bandwidth tradeoffs: a sneak preview
    • 4.3.5 The Nyquist criterion at the link level
    • 4.3.6 Linear modulation as a building block
  • 4.4 Orthogonal and biorthogonal modulation
  • 4.5 Proofs of the Nyquist theorems
  • 4.6 Concept summary
  • 4.7 Notes
  • 4.8 Problems
  • Software Lab 4.1: linear modulation over a noiseless ideal channel
  • Appendix 4.A Power spectral density of a linearly modulated signal
  • Appendix 4.B Simulation resource: bandlimited pulses and upsampling
• 5. Probability and random processes
  • Chapter plan
  • 5.1 Probability basics
  • 5.2 Random variables
  • 5.3 Multiple random variables, or random vectors
  • 5.4 Functions of random variables
  • 5.5 Expectation
    • 5.5.1 Expectation for random vectors
  • 5.6 Gaussian random variables
    • 5.6.1 Joint Gaussianity
  • 5.7 Random processes
    • 5.7.1 Running example: a sinusoid with random amplitude and phase
    • 5.7.2 Basic definitions
    • 5.7.3 Second-order statistics
    • 5.7.4 Wide-sense stationarity and stationarity
    • 5.7.5 Power spectral density
    • 5.7.6 Gaussian random processes
  • 5.8 Noise modeling
  • 5.9 Linear operations on random processes
    • 5.9.1 Filtering
    • 5.9.2 Correlation
  • 5.10 Concept summary
  • 5.11 Notes
  • 5.12 Problems
  • Appendix 5.A Q function bounds and asymptotics
  • Appendix 5.B Approximations using limit theorems
  • Appendix 5.C Noise mechanisms
  • Appendix 5.D The structure of passband random processes
    • Appendix 5.D.1 Baseband representation of passband white noise
  • Appendix 5.E SNR computations for analog modulation
    • Appendix 5.E.1 Noise model and SNR benchmark
    • Appendix 5.E.2 SNR for amplitude modulation
    • Appendix 5.E.3 SNR for angle modulation
• 6. Optimal demodulation
  • Chapter plan
  • 6.1 Hypothesis testing
    • 6.1.1 Error probabilities
    • 6.1.2 ML and MAP decision rules
    • 6.1.3 Soft decisions
  • 6.2 Signal-space concepts
    • 6.2.1 Representing signals as vectors
    • 6.2.2 Modeling WGN in signal space
    • 6.2.3 Hypothesis testing in signal space
    • 6.2.4 Optimal reception in AWGN
    • 6.2.5 Geometry of the ML decision rule
  • 6.3 Performance analysis of ML reception
    • 6.3.1 The geometry of errors
    • 6.3.2 Performance with binary signaling
    • 6.3.3 M-ary signaling: scale-invariance and SNR
    • 6.3.4 Performance analysis for M-ary signaling
    • 6.3.5 Performance analysis for M-ary orthogonal modulation
  • 6.4 Bit error probability
  • 6.5 Link-budget analysis
  • 6.6 Concept summary
  • 6.7 Notes
  • 6.8 Problems
  • Software Lab 6.1: linear modulation with two-dimensional constellations
  • Software Lab 6.2: modeling and performance evaluation on a wireless fading channel
  • Appendix 6.A The irrelevance of the component orthogonal to the signal space
• 7. Channel coding
  • Chapter plan
  • 7.1 Motivation
  • 7.2 Model for channel coding
  • 7.3 Shannon’s promise
    • 7.3.1 Design implications of Shannon limits
  • 7.4 Introducing linear codes
  • 7.5 Soft decisions and belief propagation
  • 7.6 Concept summary
  • 7.7 Notes
  • 7.8 Problems
  • Software Lab 7.1: belief propagation
• 8. Dispersive channels and MIMO
  • Chapter plan
  • 8.1 The single-carrier system model
    • 8.1.1 The signal model
    • 8.1.2 The noise model and SNR
  • 8.2 Linear equalization
    • 8.2.1 Adaptive MMSE equalization
    • 8.2.2 Geometric interpretation and analytical computations
  • 8.3 Orthogonal frequency-division multiplexing
    • 8.3.1 DSP-centric implementation
  • 8.4 MIMO
    • 8.4.1 The linear array
    • 8.4.2 Beamsteering
    • 8.4.3 Rich scattering and MIMO-OFDM
    • 8.4.4 Diversity
    • 8.4.5 Spatial multiplexing
  • 8.5 Concept summary
  • 8.6 Notes
  • 8.7 Problems
  • Software Lab 8.1: introduction to equalization in single-carrier systems
  • Software Lab 8.2: simplified simulation model for an OFDM link
  • Software Lab 8.3: MIMO signal processing
• Epilogue
• References
• Index

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