MODERN DIGITAL RADIO COMMUNICATION SIGNALS AND SYSTEMS.

New Edition Preface
Preface of the First Edition
Contents
Author Bio
Chapter 1: Overview of Radio Communication Signals and Systems
	1.1 Examples of Wireless Communication Systems
	1.2 Overview of Wireless Communication Systems
		1.2.1 Continuous Wave (CW) Signals
		1.2.2 Complex Envelope and Quadrature Modulation
		1.2.3 Digital Modulations
		1.2.4 Pulse Shaping Filter
		1.2.5 Channel Coding
		1.2.6 Demodulation and Receiver Signal Processing
			1.2.6.1 CW Signal to Complex Envelope (D - C)
			1.2.6.2 Analog Complex Envelope (AI and AQ) Is Sampled (C - B)
			1.2.6.3 Digital Demodulation and Decision (B - B1)
		1.2.7 Synchronization and Channel Estimation
		1.2.8 More Modulation and Demodulation Processing
			1.2.8.1 DS Spread Spectrum System
			1.2.8.2 OFDM and FH Spread Spectrum
			1.2.8.3 Diversity Channels (Frequency, Time, Space)
		1.2.9 Radio Propagation Channels
		1.2.10 Extension to Optical Fiber, and Other Systems
		1.2.11 Summary of the Overview
	1.3 The Layered Approach
	1.4 Historical Notes
	1.5 Organization of the Book
	1.6 Reference Example and its Sources
	1.7 Problems
Chapter 2: Digital Modulations
	2.1 Constellation, Complex Envelope, and CW
		2.1.1 OOK, BPSK, and Orthogonal (M = 2)
	2.2 Power of Digitally Modulated Signals and SNR
		2.2.1 Discrete Symbol Average Power  Computation
		2.2.2 Power Spectral Density
		2.2.3 Signal Power and Noise Power Ratio (SNR)
	2.3 MAP and ML Detectors
		2.3.1 Symbol Error Rate of BPSK Under AWGN Channel
		2.3.2 SER of OOK and Orthogonal signaling (M = 2) Under AWGN Channel
	2.4 PAM, QAM, and PSK
		2.4.1 M-PAM
			2.4.1.1 SER of M-PAM Under AWGN Channel
		2.4.2 Square M- QAM
			2.4.2.1 SER of Square QAM
			2.4.2.2 Double Square (DSQ) constellations
		2.4.3 PSK, APSK, and DPSK
			2.4.3.1 APSK
			2.4.3.2 Partially Coherent Detection (of DPSK) and Non-coherent Detection (of FSK)
	2.5 BER and Different forms of SNR
		2.5.1 BER Requires a Specific Bit to Symbol Mapping
		2.5.2 A Quick Approximation of SER to BER conversion
		2.5.3 Numerical Simulations of BER with LLR
		2.5.4 SNR in Different Forms
	2.6 Offset QAM (or Staggered QAM)
		2.6.1 SER vs.  Performance of Staggered QAM
		2.6.2 CCDF of Staggered QAM vs. of `Regular´ QAM
		2.6.3 Other Issues
	2.7 Digital Processing and Spectrum Shaping
		2.7.1 Scrambler
			2.7.1.1 Properties of PN Sequence
			2.7.1.2 Primitive Polynomials for PN Sequence
			2.7.1.3 Another Type of Scrambler
		2.7.2 Differential Coding or phase invariance coding
			2.7.2.1 180o Phase Invariance Coding
			2.7.2.2 Multi Bit Extension of 180o Phase Invariance Coding
			2.7.2.3 90o Rotation Invariance
			2.7.2.4 Rotational Invariance of 16-QAM
		2.7.3 Partial Response Signaling
			2.7.3.1 1+D Duo-Binary digital filter
			2.7.3.2 Performance of 1+D System with Symbol by Symbol Detection
			2.7.3.3 Performance of 1+D System with an Analog (1+D) Matched Filter
			2.7.3.4 QPRS
			2.7.3.5 (1-D2) Modified Duo-Binary
			2.7.3.6 Additional Example of PRS: 1+2D +D2
	2.8 Frequency Modulation - FSK, MSK, CPFSK
		2.8.1 Examples of FSK Signal Generation
		2.8.2 Non-coherent Demodulation of FSK
		2.8.3 FSK Signal Generations Using Quadrature Modulator
		2.8.4 Binary CPFSK Example
		2.8.5 M-Level CPFSK
		2.8.6 MSK
		2.8.7 FSK with Gaussian Pulse
		2.8.8 Power Spectral Density of CPFSK, MSK, and GMSK
		2.8.9 Partial Response CPFSK
		2.8.10 SER Performance Analysis of CPFSK
	2.9 PSD of Digitally Modulated Signals
		2.9.1 Power Spectral Density of PAM Signal
		2.9.2 PSD of Quadrature Modulated Signals
		2.9.3 PSD of FDM and OFDM Signals
		2.9.4 PSD Numerical Computations and Measurements
		2.9.5 Numerical Computation of PSD Using FFT
		2.9.6 Example of PSD Computation by Using FFT
		2.9.7 PSD of Digital FM Signals -FSK, CPFSK
		2.9.8 PSD Computation Using Correlation
	2.10 Chapter Summary and References
		2.10.1 Summary
		2.10.2 References
	2.11 Problems
Chapter 3: Matched Filter & Nyquist Pulse
	3.1 Matched Filters
		3.1.1 Matched Filter Defined and Justified
		3.1.2 Examples of Matched Filters
		3.1.3 Characteristic of Matched Filters
		3.1.4 SNR Loss Due to Pulse Mismatch
		3.1.5 A Mismatch Loss Due to Receive Noise Bandwidth
	3.2 Nyquist Criterion - ISI Free Pulse
		3.2.1 Nyquist Criterion - ISI Free End-To-End Pulse
		3.2.2 Frequency Domain Expression of Nyquist Criterion
		3.2.3 Band Edge Vestigial Symmetry and Excess Bandwidth
		3.2.4 Raised Cosine Filter
	3.3 Shaping Pulse (Filter) Design
		3.3.1 Practical Design Considerations
		3.3.2 A Practical Design Example of Analog Filter
		3.3.3 Design of Digital Matched Filters
			3.3.3.1 Windowing Method
			3.3.3.2 Frequency Domain Optimization Method
	3.4 Performance Degradation Due to ISI
		3.4.1 A Design Case to Simplify the Shaping Filters
		3.4.2 A Quick Analysis of the Suggestion of Using a Rectangular Pulse
			3.4.2.1 Mismatch Loss
			3.4.2.2 SNR Loss Due to ISI:
			3.4.2.3 Peak Distortion Estimation Method
			3.4.2.4 Eye Pattern
		3.4.3 A Discrete in Time Model for ISI Analysis in General
		3.4.4 A Discrete in Time Model for Simulation
		3.4.5 Summary for ISI Analysis Methods
	3.5 Extension to Linear Channel and Non-White Noise
		3.5.1 Linear Channels with White Noise
		3.5.2 Non- White Noise
	3.6 References
	3.7 Problems
Chapter 4: Radio Propagation and RF Channels
	4.1 Path Loss of Radio Channels
		4.1.1 Free Space Loss
		4.1.2 Pathloss Exponent
	4.2 Antenna Basic and Antenna Gain
		4.2.1 Antenna Basics
		4.2.2 Antenna Pattern
		4.2.3 Directivity and Antenna Gain
		4.2.4 Aperture Concept and Antenna Beam Angle
	4.3 Path Loss Due to Reflection, Diffraction and Scattering
		4.3.1 Ground Reflection (2-Ray Model)
		4.3.2 Diffraction, Fresnel Zone and Line of Sight Clearance
		4.3.3 Examples of Empirical Path Loss Model
		4.3.4 Simplified Pathloss Model
		4.3.5 Shadow Fading: Variance of Path Loss
			4.3.5.1 Fade Margin and Reliability
		4.3.6 Range Estimation and Net Link Budget
			4.3.6.1 Thermal Noise
			4.3.6.2 Example of Range Estimation
			4.3.6.3 Range Comparison with Different Pathloss Exponent
	4.4 Multipath Fading and Statistical Models
		4.4.1 Intuitive Understanding of Multi-Path Fading
			4.4.1.1 Doppler Frequency
		4.4.2 Rayleigh Fading Channels
			4.4.2.1 Doppler Spectrum with Uniform Scattering - Jakes Spectrum
			4.4.2.2 Rayleigh Fading Channel Implementation
			4.4.2.3 Rayleigh Fading of Power Distribution
			4.4.2.4 Raleigh Envelope Distribution
			4.4.2.5 Rice (LOS Component)
			4.4.2.6 Two Independent Zero Mean Gaussian Sample Generation
		4.4.3 Wideband Frequency Selective Fading
			4.4.3.1 A Sampled (Discrete Time) Channel Model
			4.4.3.2 Finding the Channel Coefficients of a Sampled Model
			4.4.3.3 Frequency Selective Channel Example
			4.4.3.4 On the Computation of Ai(kDeltat)
		4.4.4 Alternative Approach to Fading Channel Models
			4.4.4.1 A Channel Model with Scattering Description
			4.4.4.2 A Channel Model with Transmit and Receive Filters
			4.4.4.3 A Simplification when a Delay Profile Is Discrete in Time
			4.4.4.4 A Sampled Channel Model - Monte Carlo Method
			4.4.4.5 How to Incorporate Rician Fading Case
			4.4.4.6 Further Development of Monte Carlo Method
	4.5 Channel Sounding and Measurements
		4.5.1 Direct RF Pulse
		4.5.2 Spread Spectrum Signal (Time Domain)
			4.5.2.1 Test Signal Design Problem
		4.5.3 Chirp Signal (Frequency Sweep Signal) for Channel Sounding
		4.5.4 Synchronization and Location
		4.5.5 Directionally Resolved Measurements (Angle Spread Measurements)
			4.5.5.1 Measurement with an Antenna Array
			4.5.5.2 More Topics with Multiple Antenna Channel Measurement Not Covered
	4.6 Channel Model Examples
		4.6.1 Empirical Path Loss Models
		4.6.2 M1225 of ITU-R Path Loss Models
		4.6.3 Multipath Fading Models in Cellular Standards
			4.6.3.1 GSM Channels
		4.6.4 Cellular Concept and Interference Limited Channels
			4.6.4.1 Cellular Frequency Reuse
			4.6.4.2 Cluster Size (K) and Co-Channel Interference Distance (D)
			4.6.4.3 Cluster Size with Hexagons
			4.6.4.4 Co-channel Interference
			4.6.4.5 Use of Repeaters and Distributed Antennas:
		4.6.5 Channel Models of Low Earth Orbit (LEO) Satellite
			4.6.5.1 Geometry of LEO
			4.6.5.2 Fading Channel Model Due to Satellite Orbiting
			4.6.5.3 Cosine Loss of Phased Array Antenna
	4.7 Summary of Fading Countermeasures
	4.8 References with Comments
	4.9 Problems
Chapter 5: OFDM Signals and Systems
	5.1 DMT with CP - Block Transmission
		5.1.1 IDFT - DFT Pair as a Transmission System
		5.1.2 Cyclic Prefix Added to IDFT- DFT Pair
		5.1.3 Transmit Spectrum
		5.1.4 OFDM Symbol Boundary with CP
		5.1.5 Receiver Processing When the Channel Dispersion < CP
			5.1.5.1 Gain and Phase Adjustment - ``1-Tap Equalizer´´
			5.1.5.2 System Degradation if Delay Spread Is Bigger than CP
		5.1.6 SNR Penalty of the Use of CP
	5.2 CP Generalized OFDM - Serial Transmission
		5.2.1 OFDM - Analog Representation
		5.2.2 Discrete Signal Generation of Analog OFDM
		5.2.3 Discrete Signal Reception
		5.2.4 Pulse Shape of DMT and its End to End Pulse
		5.2.5 Windowing
		5.2.6 Filter Method Compares with DMT with CP
	5.3 Filtered OFDM
		5.3.1 Filtered OFDM Signal Generation
			5.3.1.1 Transmit Spectrum of Filtered OFDM
		5.3.2 Filtered OFDM Signal Reception
		5.3.3 Common Platform
		5.3.4 Impulse Response and Eye Pattern
		5.3.5 1-Tap Equalizer, Sample Timing and Carrier Phase Recovery, and Channel Estimation
		5.3.6 Regular FDM Processing with Filtered OFDM
	5.4 OFDM with Staggered QAM
		5.4.1 Common Platform Structure for OFDM with Staggering
		5.4.2 Receiver Side of OFDM with Staggered QAM
		5.4.3 T/2 Base Implementation of Transmit Side
		5.4.4 Impulse Response, Eye Pattern, and Constellation of Staggered OFDM
	5.5 Practical Issues
		5.5.1 Performance When a Channel Delay Spread > CP
			5.5.1.1 Performance Analysis with a Linear Channel
		5.5.2 Digital Quadrature Modulation to IF and IF Sampling
			5.5.2.1 IF Sampling at Receive Side
		5.5.3 Modern FH Implementation with OFDM
		5.5.4 Naming of OFDM Signals
	5.6 OFDM with Coding
		5.6.1 Coded Modulations for Static Frequency Selective Channels
		5.6.2 Coding for Doubly Selective Fading Channels
			5.6.2.1 Subchannel Permutation (pi5)
			5.6.2.2 Coded Modulation (CMR) for Rayleigh Fading Channels
			5.6.2.3 Binary FECb
	5.7 Chapter Summary
	5.8 References and Appendix
	5.9 Problems
Chapter 6: Channel Coding
	6.1 Code Examples and Introduction to Coding
		6.1.1 Code Examples - Repetition and Parity Bit
		6.1.2 Analytical WER Performance
			6.1.2.1 Independence and Mutually Exclusive Assumptions
			6.1.2.2 Analytical Performance with HD
		6.1.3 Section Summary
	6.2 Linear Binary Block Codes
		6.2.1 Generator and Parity Check Matrices
			6.2.1.1 Dual Code
			6.2.1.2 Weight and Distance of Linear Block Codes
		6.2.2 Hamming Codes and Reed-Muller Codes
			6.2.2.1 Hamming Codes
			6.2.2.2 Hard Decision Decoding
			6.2.2.3 HD Decoding Performance of (7, 4) Hamming
			6.2.2.4 Dual of Hamming Code is Maximal Length Code
			6.2.2.5 Reed-Muller Code
		6.2.3 Code Performance Analysis of Linear Block Codes*
			6.2.3.1 Correlation Metric (CM) Decoding
			6.2.3.2 Computation of WER of Linear Block Codes
			6.2.3.3 Additional Comments on the WER Computation for Linear Block Codes
		6.2.4 Cyclic Codes and CRC
			6.2.4.1 Cyclic Codes
			6.2.4.2 Generator Polynomial
			6.2.4.3 Transmission Sequence of a Codeword and its Code Polynomial
			6.2.4.4 Remainder Computation with Shift Register Circuits
			6.2.4.5 Syndrome Computation with the Shift Register Circuits
			6.2.4.6 CRC
			6.2.4.7 Decoding Cyclic Codes
		6.2.5 BCH and RS Codes
			6.2.5.1 BCH Codes
			6.2.5.2 RS Codes
		6.2.6 Algebraic Decoding of BCH
			6.2.6.1 A Block Diagram of Algebraic Decoding Process
			6.2.6.2 Syndrome Computation From r(X) - Method A
			6.2.6.3 Find Error Location Polynomial Degree t or Less σ(X)
			6.2.6.4 Find Zeros of σ(X) an Error Location Polynomial
		6.2.7 Code Modifications - Shortening, Puncturing and Extending
	6.3 Convolutional Codes
		6.3.1 Understanding Convolutional Code
			6.3.1.1 Example of G=15/13 RSC
			6.3.1.2 G =7 |5 Nonsystematic Convolutional code Example
			6.3.1.3 Recursive form of G=7/5 convolutional Code
			6.3.1.4 Optimum Convolutional Code Tables
			6.3.1.5 Block Codes from Convolutional Codes
			6.3.1.6 Input Weight and Output Distance of Convolutional Codes
			6.3.1.7 Optimized Computation of A (w, d)
		6.3.2 Viterbi Decoding of Convolutional Codes
			6.3.2.1 Review of CM and its Use as Branch Metric
			6.3.2.2 Viterbi Decoding Explained With an Example of HD
			6.3.2.3 Viterbi Decoding Explained With an Example of SD
			6.3.2.4 Viterbi Decoding with Quantized SD
			6.3.2.5 Why Viterbi Decoding is Effective?
			6.3.2.6 Summary of Viterbi Decoding Algorithm
			6.3.2.7 Branch Metric Revisited
		6.3.3 BCJR Decoding of Convolutional Codes
			6.3.3.1 Notations
			6.3.3.2 BCJR Algorithm (Forward - Backward Algorithm)
			6.3.3.3 Computation of APP of Information and Transmit Digits
			6.3.3.4 Channel Model and Branch Metric
			6.3.3.5 Numerical Example of BCJR Decoding of Figure 6-34
			6.3.3.6 Summary of BCJR Algorithm
		6.3.4 Other Topics Related with Convolutional Codes
			6.3.4.1 Trellis Representation of Block Codes
			6.3.4.2 Other Decoding Techniques of Convolutional Codes
	6.4 LDPC
		6.4.1 Introduction to LDPC Code
			6.4.1.1 Graphical Representation of LDPC Code
			6.4.1.2 A numerical Example of Tanner Graph as a Decoder
		6.4.2 LDPC Decoder
		6.4.3 Bit Node Updating Computation
			6.4.3.1 Check Node Updating Computation
			6.4.3.2 Updating qi; Computation of APP of pi
			6.4.3.3 The Computational Organization with H  edge tables
		6.4.4 LDPC Encoder
			6.4.4.1 Encoder with a Special Form of H - Band Diagonal
			6.4.4.2 Different Encoder Implementation of RA Form
		6.4.5 Useful Rules and Heuristics for LDPC Code Construction
			6.4.5.1 Definition of Cycle, Trapping (stopping) Set
			6.4.5.2 Properties of H Related with and Useful to Code Construction
		6.4.6 LDPC in Standards
	6.5 Turbo Codes
		6.5.1 Turbo Encoding with G=15/13 RSC and Permutation
		6.5.2 G=15/13 Code Tables for BCJR Computation Organization
		6.5.3 The generation of `extrinsic´ information (E1, E2)
		6.5.4 Numerical Computations of Iterative Turbo Decoding
		6.5.5 Additional Practical Issues
			6.5.5.1 Decoding Computation in Log Domain
			6.5.5.2 Permutations (Interleaver)
			6.5.5.3 Constituent Convolution Codes
	6.6 Coding Applications
		6.6.1 Coded Modulations
			6.6.1.1 LLR Computations of Multi-Level Constellations
			6.6.1.2 Performance of 8-DSQ and 8-PSK with LDPC Code
			6.6.1.3 More Coded Modulation Examples with 16QAM and 64QAM
			6.6.1.4 Gray Bit Assignment
			6.6.1.5 On Permutation, Interleaver, and Scrambler
		6.6.2 MLCM, TCM and BICM
			6.6.2.1 A Brief History of MLCM, TCM and BICM
			6.6.2.2 MLCM Idea
			6.6.2.3 MLCM Mapper (64QAM Example)
			6.6.2.4 MLCM Implementation with N=1944 LDPC
			6.6.2.5 Performance Comparison of MLCM with BICM
			6.6.2.6 An Extension to 5.5 Bits/Symbol, 5.25 and 5.75 Bits/Symbol
			6.6.2.7 An Example of MLCM to 128 DSQ
			6.6.2.8 An MLCM Mapper with 128 Points and its Extensions
		6.6.3 Channel Capacity of AWGN and of QAM Constellations
		6.6.4 PAPR Reduction with Coding
		6.6.5 Fading Channels
			6.6.5.1 Degradation of SER Performance Due to Rayleigh Fading
			6.6.5.2 Fading as a Random Fluctuation of SNR
			6.6.5.3 Channel Capacity of Rayleigh Fading Channel
			6.6.5.4 Channel Capacity of Frequency Selective Fading Channel
			6.6.5.5 Evaluate (6-57) When peEsNoAWGNis Available as Numerical Data
	6.7 References with Comments and Appendix
	Appendix 6
		A.1 CM Decoding Example of Figure 6-36
		A.2 The Computation of p0 (p1), and LLR for BPSK
		A.3 Different Expressions of Check Node LLR of LDPC
		A.4 Computation of Channel Capacity
		A.5 SER Performance of Binary PSK, DPSK, FSK
	6.8 Problems
Chapter 7: Synchronization of Frame, Symbol Timing and Carrier
	7.1 Packet Synchronization Examples
		7.1.1 PLCP Preamble Format of IEEE 802.11a
			7.1.1.1 Short-Term Training Sequence (STS)
			7.1.1.2 Long-Term Training Sequence (LTS)
		7.1.2 RCV Processing of STS and LTS
			7.1.2.1 Matched Filter Algorithm
			7.1.2.2 STS Processing Detail
			7.1.2.3 LTS Processing Detail
		7.1.3 802.11a Synchronization Performance
			7.1.3.1 Overall Performance Target
			7.1.3.2 STS and LTS Performance for Flat Channel
			7.1.3.3 STS and LTS Performance for Frequency Selective Channel
		7.1.4 DS Spread Spectrum Synchronization Example
			7.1.4.1 Acquisition and Tracking with Analog Matched Filter
			7.1.4.2 Digital Matched Filter Implementation
			7.1.4.3 Weak Signal Initial Code Phase Synchronization
	7.2 Symbol Timing Synchronization
		7.2.1 Symbol Timing Error Detector for PAM/QAM
			7.2.1.1 Closed Form Expression of Timing Detector for Band-Limited Signals
		7.2.2 Known Digital Timing Error Detectors
			7.2.2.1 Extensions of Known Timing Detectors
			7.2.2.2 Timing Detectors Related with One in Figure 7-26
			7.2.2.3 Gardner´s Timing Detector and its Extension
		7.2.3 Numerical Confirmation of S-Curve of Timing Error Detectors
		7.2.4 Timing Detectors with Differentiation or with Hilbert Transform
		7.2.5 Intuitive Understanding of Timing Detectors
		7.2.6 Carrier Frequency Offset Estimation
		7.2.7 Embedding Digital TED Into Timing Recovery Loop
		7.2.8 Resampling and Resampling Control
		7.2.9 Simulations of Doppler Clock Frequency Shift
			7.2.9.1 Doppler Frequency Shift
			7.2.9.2 Simulation Model of Doppler Clock Frequency Shift
	7.3 Carrier Phase Synchronization
		7.3.1 Carrier Recovery Loop and Its Components
		7.3.2 Phase Locked Loop Review
		7.3.3 Understanding Costas Loop for QPSK
		7.3.4 Carrier Phase Detectors
		7.3.5 All Digital Implementations of Carrier Recovery Loop
	7.4 Quadrature Phase Imbalance Correction
		7.4.1 IQ Imbalance Model
		7.4.2 , φi , and φd Measurements
		7.4.3 2-Step Approach for the Estimation of, φi, and φd
		7.4.4 Additional Practical Issues
		7.4.5 Summary of IQ Phase Imbalance Digital Correction
	7.5 References with Comments
	Appendix 7
		A.1 Raised Cosine Pulse and its Pre-filtered RC Pulse
		A.2 Poisson Sum Formula for a Correlated Signal
		A.3 Review of Phase Locked Loops
		A.4 FIR Interpolation Filter Design and Coefficient Computation
	7.6 Problems
Chapter 8: Practical Implementation Issues
	8.1 Transceiver Architecture
		8.1.1 Direct Conversion Transceiver
		8.1.2 Heterodyne Conversion Transceiver
		8.1.3 Implementation Issues of Quadrature Up-Conversion
		8.1.4 Implementation Issues of Quadrature Down-Conversion
		8.1.5 SSB Signals and Image Cancellation Schemes
		8.1.6 Transceiver of Low Digital IF with Image-Cancelling
			8.1.6.1 TX Signal Generation of Digital Image-Cancelling Transceiver
			8.1.6.2 RX Signal Processing of Digital Image-Cancelling Transceiver
			8.1.6.3 Filtering Considerations for Digital Image Cancelling Transceiver
			8.1.6.4 Digital IF Modulation and Demodulation
			8.1.6.5 Interpolation and Decimation Digital Filters
			8.1.6.6 Implementation Example of Digital IF Image Cancelling Blocks
			8.1.6.7 Effects of Quadrature Amplitude and Phase Imbalance to Image Cancellation
			8.1.6.8 DC Offset - Filtering and Cancellation
			8.1.6.9 Different Transceiver Architectures with Digital IF
			8.1.6.10 Alternative Form of Interpolation and Decimation of OFDM Signals
			8.1.6.11 Multi-channel Processing with Digital IF
			8.1.6.12 Summary of Digital Image Cancelling Transceiver
		8.1.7 Calibration of Quadrature Modulator | Demodulator
		8.1.8 Summary of Transceiver Architectures
	8.2 Practical Issues of RF Transmit Signal Generation
		8.2.1 DAC
		8.2.2 Transmit Filters and Complex Baseband Equivalence
		8.2.3 TX Signal Level Distribution and TX Power Control
		8.2.4 PA and Non-linearity
		8.2.5 Generation of Symbol Clock and Carrier Frequency
		8.2.6 Summary of RF Transmit Signal Generation
	8.3 Practical Issues of RF Receive Signal Processing
		8.3.1 ADC
		8.3.2 RX Filters and Complex Baseband Representation
		8.3.3 RCV Dynamic Range and AGC
		8.3.4 LNA, NF, and Receiver Sensitivity Threshold
		8.3.5 Re-generation of Symbol Clock and Carrier Frequency
		8.3.6 Summary of RF Receive Signal Processing
	8.4 Chapter Summary and References with Comments
		8.4.1 Chapter Summary
		8.4.2 References with Comments
	8.5 Problems
Chapter 9: Review of Signals and Systems, and of Probability and Random Process
	9.1 Continuous-Time Signals and Systems
		9.1.1 Impulse Response and Convolution Integral - Time Domain
		9.1.2 Frequency Response and Fourier Transform
		9.1.3 Signal Power and Noise Power
			9.1.3.1 Computation of CW Signal Power from Baseband Signal
			9.1.3.2 Computation of Signal Power from Complex Envelope
			9.1.3.3 Power Gain Through a Filter and Spectral Density
			9.1.3.4 Noise Power and Noise Power Spectral Density
			9.1.3.5 Noise Power After Passing Through a Receive Filter
	9.2 Review of Discrete-Time Signals and Systems
		9.2.1 Discrete-Time Convolution Sum and Discrete-Time Unit Impulse
		9.2.2 Discrete Fourier Transform Properties and Pairs
	9.3 Conversion Between Discrete-Time Signals and Continuous-Time Signals
		9.3.1 Discrete-Time Signal from Continuous-Time Signal by Sampling
		9.3.2 Continuous-Time Signals from Discrete-Time Signal by De-sampling (Interpolation)
	9.4 Probability, Random Variable and Process
		9.4.1 Basics of Probability
		9.4.2 Conditional Probability
		9.4.3 Probability of Independent Events
		9.4.4 Random Variable and CDF and PDF
		9.4.5 Expected Value (Average)
		9.4.6 Some Useful Probability Distributions
		9.4.7 Q(x) and Related Functions and Different Representations
		9.4.8 Stochastic Process
		9.4.9 Stationary Process, Correlation and Power Density Spectrum
		9.4.10 Processes Through Linear Systems
		9.4.11 Periodically Stationary Process
	9.5 Chapter Summary and References with Comments
		9.5.1 Chapter Summary
		9.5.2 References with Comments
	9.6 Problems
Index