Algorithms for Communications Systems and their Applications - Nevio Benvenuto - E-Book

Algorithms for Communications Systems and their Applications E-Book

Nevio Benvenuto

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The definitive guide to problem-solving in the design of communications systems In Algorithms for Communications Systems and their Applications, 2nd Edition, authors Benvenuto, Cherubini, and Tomasin have delivered the ultimate and practical guide to applying algorithms in communications systems. Written for researchers and professionals in the areas of digital communications, signal processing, and computer engineering, Algorithms for Communications Systems presents algorithmic and computational procedures within communications systems that overcome a wide range of problems facing system designers. New material in this fully updated edition includes: * MIMO systems (Space-time block coding/Spatial multiplexing /Beamforming and interference management/Channel Estimation) * OFDM and SC-FDMA (Synchronization/Resource allocation (bit and power loading)/Filtered OFDM) * Improved radio channel model (Doppler and shadowing/mmWave) * Polar codes (including practical decoding methods) * 5G systems (New Radio architecture/initial access for mmWave/physical channels) The book retains the essential coding and signal processing theoretical and operative elements expected from a classic text, further adopting the new radio of 5G systems as a case study to create the definitive guide to modern communications systems.

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Table of Contents

Cover

Title Page

Copyright

Dedication

Preface

Acknowledgements

Chapter 1: Elements of signal theory

1.1 Continuous‐time linear systems

1.2 Discrete‐time linear systems

1.3 Signal bandwidth

1.4 Passband signals and systems

1.5 Second‐order analysis of random processes

1.6 The autocorrelation matrix

1.7 Examples of random processes

1.8 Matched filter

1.9 Ergodic random processes

1.10 Parametric models of random processes

1.11 Guide to the bibliography

Bibliography

Appendix 1.A Multirate systems

Appendix 1.B Generation of a complex Gaussian noise

Appendix 1.C Pseudo‐noise sequences

Notes

Chapter 2: The Wiener filter

2.1 The Wiener filter

2.2 Linear prediction

2.3 The least squares method

2.4 The estimation problem

2.5 Examples of application

Bibliography

Appendix 2.A The Levinson–Durbin algorithm

Notes

Chapter 3: Adaptive transversal filters

3.1 The MSE design criterion

3.2 The recursive least squares algorithm

3.3 Fast recursive algorithms

3.4 Examples of application

Bibliography

Notes

Chapter 4: Transmission channels

4.1 Radio channel

4.2 Telephone channel

Bibliography

Appendix 4.A Discrete‐time NB model for mmWave channels

Notes

Chapter 5: Vector quantization

5.1 Basic concept

5.2 Characterization of VQ

5.3 Optimum quantization

5.4 The Linde, Buzo, and Gray algorithm

5.5 Variants of VQ

5.6 VQ of channel state information

5.7 Principal component analysis

Bibliography

Notes

Chapter 6: Digital transmission model and channel capacity

6.1 Digital transmission model

6.2 Detection

6.3 Relevant parameters of the digital transmission model

6.4 Error probability

6.5 Capacity

6.6 Achievable rates of modulations in AWGN channels

Bibliography

Appendix 6.A Gray labelling

Appendix 6.B The Gaussian distribution and Marcum functions

Notes

Chapter 7: Single‐carrier modulation

7.1 Signals and systems

7.2 Intersymbol interference

7.3 Performance analysis

7.4 Channel equalization

7.5 Optimum methods for data detection

7.6 Numerical results obtained by simulations

7.7 Precoding for dispersive channels

7.8 Channel estimation

7.9 Faster‐than‐Nyquist Signalling

Bibliography

Appendix 7.A Simulation of a QAM system

Appendix 7.B Description of a finite-state machine

Appendix 7.C Line codes for PAM systems

Appendix 7.D

Notes

Chapter 8: Multicarrier modulation

8.1 MC systems

8.2 Orthogonality conditions

8.3 Efficient implementation of MC systems

8.4 Non‐critically sampled filter banks

8.5 Examples of MC systems

8.6 Analog signal processing requirements in MC systems

8.7 Equalization

8.8 Orthogonal time frequency space modulation

8.9 Channel estimation in OFDM

8.10 Multiuser access schemes

8.11 Comparison between MC and SC systems

8.12 Other MC waveforms

Bibliography

Notes

Chapter 9: Transmission over multiple input multiple output channels

9.1 The MIMO NB channel

9.2 CSI only at the receiver

9.3 CSI only at the transmitter

9.4 CSI at both the transmitter and the receiver

9.5 Hybrid beamforming

9.6 Multiuser MIMO: broadcast channel

9.7 Multiuser MIMO: multiple‐access channel

9.8 Massive MIMO

Bibliography

Notes

Chapter 10: Spread‐spectrum systems

10.1 Spread‐spectrum techniques

10.2 Applications of spread‐spectrum systems

10.3 Chip matched filter and rake receiver

10.4 Interference

10.5 Single‐user detection

10.6 Multiuser detection

10.7 Multicarrier CDMA systems

Bibliography

Appendix 10.A Walsh Codes

Notes

Chapter 11: Channel codes

11.1 System model

11.2 Block codes

11.3 Convolutional codes

11.4 Puncturing

11.5 Concatenated codes

11.6 Turbo codes

11.7 Iterative detection and decoding

11.8 Low‐density parity check codes

11.9 Polar codes

11.10 Milestones in channel coding

Bibliography

Appendix 11.A Non‐binary parity check codes

Notes

Chapter 12: Trellis coded modulation

12.1 Linear TCM for one‐ and two‐dimensional signal sets

12.2 Multidimensional TCM

12.3 Rotationally invariant TCM schemes

Bibliography

Notes

Chapter 13: Techniques to achieve capacity

13.1 Capacity achieving solutions for multicarrier systems

13.2 Capacity achieving solutions for single carrier systems

Bibliography

Notes

Chapter 14: Synchronization

14.1 The problem of synchronization for QAM systems

14.2 The phase‐locked loop

14.3 Costas loop

14.4 The optimum receiver

14.5 Algorithms for timing and carrier phase recovery

14.6 Algorithms for carrier frequency recovery

14.7 Second‐order digital PLL

14.8 Synchronization in spread‐spectrum systems

14.9 Synchronization in OFDM

14.10 Synchronization in SC‐FDMA

Bibliography

Notes

Chapter 15: Self‐training equalization

15.1 Problem definition and fundamentals

15.2 Three algorithms for PAM systems

15.3 The contour algorithm for PAM systems

15.4 Self‐training equalization for partial response systems

15.5 Self‐training equalization for QAM systems

15.6 Examples of applications

Bibliography

Appendix 15.A On the convergence of the contour algorithm

Notes

Chapter 16: Low‐complexity demodulators

16.1 Phase‐shift keying

16.2 (D)PSK non‐coherent receivers

16.3 Optimum receivers for signals with random phase

16.4 Frequency‐based modulations

16.5 Gaussian MSK

Bibliography

Appendix 16.A Continuous phase modulation

Notes

Chapter 17: Applications of interference cancellation

17.1 Echo and near‐end crosstalk cancellation for PAM systems

17.2 Echo cancellation for QAM systems

17.3 Echo cancellation for OFDM systems

17.4 Multiuser detection for VDSL

Bibliography

Note

Chapter 18: Examples of communication systems

18.1 The 5G cellular system

18.2 GSM

18.3 Wireless local area networks

18.4 DECT

18.5 Bluetooth

18.6 Transmission over unshielded twisted pairs

18.7 Hybrid fibre/coaxial cable networks

Bibliography

Appendix 18.A Duplexing

Appendix 18.B Deterministic access methods

Notes

Chapter 19: High‐speed communications over twisted‐pair cables

19.1 Quaternary partial response class‐IV system

19.2 Dual‐duplex system

Bibliography

Appendix 19.A Interference suppression

Index

End User License Agreement

List of Tables

Chapter 1

Table 1.1 Some general properties of the Fourier transform.

Table 1.2 Examples of Fourier transform signal pairs.

Table 1.3 Properties of the z‐transform.

Table 1.4 Impulse responses of systems having the same magnitude of the frequ...

Table 1.5 Some properties of the Hilbert transform.

Table 1.6 Relations between ACS and PSD for discrete‐time processes through a...

Table 1.7 Correspondence between eigenvalues and eigenvectors of four matrice...

Table 1.8 Recursive equations to generate PN sequences of length

, for differ...

Chapter 3

Table 3.1 The RLS algorithm.

Table 3.2 Comparison of three adaptive algorithms in terms of computational c...

Chapter 4

Table 4.1 Values of

(in dB) and

(in ns) for three typical channels. In ord...

Table 4.2 Parameters of an IIR filter which implements a classical Doppler sp...

Chapter 5

Table 5.1 Comparison between full search and tree search.

Chapter 6

Table 6.1 Example of quaternary bit map (Gray labelling).

Table 6.2 Complementary Gaussian distribution.

Chapter 7

Table 7.1 Properties of several minimum bandwidth systems

Table 7.2 Precoding for the dicode filter

Chapter 11

Table 11.1 Coset leaders and respective syndromes for Example 11.2.5.

Table 11.2 Multiplication table for 3 elements (modulo‐3 arithmetic).

Table 11.3 Multiplication table for an alphabet with four elements (modulo‐4 ...

Table 11.4 Multiplication table for an alphabet with four elements.

Table 11.5 Modulo

addition table for

.

Table 11.6 Modulo

multiplication table for

.

Table 11.7 List of primitive polynomials

of degree

for the ground field

....

Table 11.8 Three equivalent representations of the elements of

.

Table 11.9 Addition table for the elements of

.

Table 11.10 Multiplication table for the elements of

.

Table 11.11 Powers of a primitive element in

with the same minimum function....

Table 11.12 (7,4) binary cyclic code, generated by

.

Table 11.13 (7,4) binary cyclic code in canonical form, generated by

.

Table 11.14 Parameters of some simplex binary codes.

Table 11.15 Minimum functions and orders of elements

,

,

,

, in

.

Table 11.16 Minimum functions of the elements of

.

Table 11.17 Roots and generator polynomials of BCH codes of length

for diffe...

Table 11.18 Parameters of BCH codes of length

.

Table 11.19 Addition table for the elements of

.

Table 11.20 Multiplication table for the elements of

.

Table 11.21 Three equivalent representations of the elements of

, obtained ap...

Table 11.22 LDPC codes considered for the simulation and coding gains achieve...

Chapter 12

Table 12.1 Codes for one‐dimensional modulation.

Table 12.2 Codes for two‐dimensional modulation.

Table 12.3 Codes for 8‐PSK.

Table 12.4 Codes for four‐dimensional modulation.

Chapter 13

Table 13.1 Example of transmission modes.

Table 13.2 Comparison between four loading algorithms.

Chapter 14

Table 14.1 Three expressions of

and corresponding Laplace transforms.

Table 14.2 Expressions of

for different choices of the loop filter

.

Table 14.3 Illustration of use of PN sequences for training [72].

Chapter 16

Table 16.1 Bit map for a BPSK system

Table 16.2 Bit map for a differentially encoded BPSK system

Table 16.3 Gray coding for

Table 16.4 Bit map for the differential encoder 2B1Q

Table 16.5 Increment of

(in dB) for an MSK scheme with respect to a coherent...

Table 16.6 Digital filter coefficients obtained by windowing

;

Table 16.7 Values of coefficient

as a function of the modulation system

Table 16.8 Required values of

, in dB, to achieve a

for various modulation ...

Table 16.9 Power delay profiles for the analysed channels

Chapter 18

Table 18.1 Radio frame configurations.

Table 18.2 DFT size for transform‐precoding.

Table 18.3 Table summarizing the main characteristics of DECT.

Table 18.4 Summary of characteristics of the standards GSM and DECT.

Table 18.5 Characteristics of DSL technologies.

Table 18.6 Scheme summarizing characteristics of standards for high‐speed tra...

Chapter 19

Table 19.1 Complexities of filtering for two transmission schemes.

List of Illustrations

Chapter 1

Figure 1.1 Analog filter as a time‐invariant linear system with continuous d...

Figure 1.2 Example of signal and Fourier transform pair.

Figure 1.3 Discrete‐time linear system (filter).

Figure 1.4 Time‐limited signals:

,

, and

,

.

Figure 1.5 Illustration of the

circular convolution

operation between

,

, ...

Figure 1.6 Impulse response magnitudes and zero locations for three systems ...

Figure 1.7 Classification of real valued analog filters on the basis of the ...

Figure 1.8 Classification of complex‐valued analog filters on the basis of s...

Figure 1.9 The real signal bandwidth following the definitions of (1) bandwi...

Figure 1.10 Operation of (a) sampling and (b) interpolation.

Figure 1.11 Characteristics of a filter satisfying the conditions for the ab...

Figure 1.12 Transformations to obtain the baseband equivalent signal

aroun...

Figure 1.13 Transformations to obtain the baseband equivalent signal

aroun...

Figure 1.14 Illustration of transformations to obtain the baseband equivalen...

Figure 1.15 Transformations to obtain the baseband equivalent signal

aroun...

Figure 1.16 Relation between a signal, its complex envelope and the analytic...

Figure 1.17 Relation between a signal and its baseband components.

Figure 1.18 Relations to derive the baseband signal components. (a) Implemen...

Figure 1.19 Magnitude and phase responses of the ideal Hilbert filter.

Figure 1.20 Frequency response of a PB signal and corresponding complex enve...

Figure 1.21 Passband transformations and their baseband equivalent. (a) Modu...

Figure 1.22 Reference scheme of PSD computations.

Figure 1.23 Spectral representation of a PB process and its BB components.

Figure 1.24 Coherent DSB demodulator and baseband‐equivalent scheme. (a) Coh...

Figure 1.25 (a) Coherent SSB demodulator and (b) baseband‐equivalent scheme....

Figure 1.26 Modulator of a PAM system as interpolator filter.

Figure 1.27 Reference scheme for the matched filter.

Figure 1.28 Matched filter for an input pulse in the presence of white noise...

Figure 1.29 Various pulse shapes related to a matched filter.

Figure 1.30 Relation between ergodic processes and their statistical descrip...

Figure 1.31 (a) Time average as output of a narrow band lowpass filter. (b) ...

Figure 1.32 Comparison between spectral estimates obtained with Welch period...

Figure 1.33 Comparison between spectral estimates obtained with the correlog...

Figure 1.34 Comparison of spectral estimates obtained with the Welch periodo...

Figure 1.35 ARMA model of a process

.

Figure 1.36 PSD of a MA process with

.

Figure 1.37 AR model of a process

.

Figure 1.38 PSD of an AR process with

.

Figure 1.39 Two examples of possible choices of the zeros (

) of

, among th...

Figure 1.40 Whitening filter for an AR process of order

.

Figure 1.41 Comparison between the spectral estimate obtained by an AR(12) p...

Figure 1.42 PSD of an AR(1) process.

Figure 1.43 PSD of an AR(2) process.

Figure 1.44 Discrete‐time linear transformation.

Figure 1.45 Decimation or downsampling transformation by a factor

.

Figure 1.46 Decimation by a factor

: (a) in the time domain, and (b) in the...

Figure 1.47 Effect of decimation in the frequency domain.

Figure 1.48 Interpolation or upsampling transformation by a factor

.

Figure 1.49 Interpolation by a factor

: (a) in the time domain, (b) in the ...

Figure 1.50 Effect of interpolation in the frequency domain.

Figure 1.51 Decimator filter.

Figure 1.52 Frequency responses related to the transformations in a decimato...

Figure 1.53 Interpolator filter.

Figure 1.54 Time and frequency responses related to the transformations in a...

Figure 1.55 Sampling frequency conversion by a rational factor.

Figure 1.56 Decomposition of the system of Figure 1.55.

Figure 1.57 Rate conversion by a rational factor

, where

.

Figure 1.58 Rate conversion by a rational factor

, where

.

Figure 1.59 Linear interpolation in time by a factor

.

Figure 1.60 Noble identities.

Figure 1.61 Polyphase representation of the impulse response

,

, for

.

Figure 1.62 Implementation of a decimator filter using the type‐1 polyphase ...

Figure 1.63 Optimized implementation of a decimator filter using the type‐1 ...

Figure 1.64 Implementation of a decimator filter using the type‐1 polyphase ...

Figure 1.65 Implementation of an interpolator filter using the type‐1 polyph...

Figure 1.66 Optimized implementation of an interpolator filter using the typ...

Figure 1.67 Implementation of an interpolator filter using the type‐1 polyph...

Figure 1.68 Implementation of an interpolator filter using the type‐2 polyph...

Figure 1.69 Interpolator‐decimator filter.

Figure 1.70 Polyphase implementation of an interpolator‐decimator filter wit...

Figure 1.71 Implementation of an interpolator‐decimator filter with timing p...

Figure 1.72 Generation of an MLS with period

.

Chapter 2

Figure 2.1 The Wiener filter with

coefficients.

Figure 2.2

as a function of

for the cases

and

. (a)

versus

for

,...

Figure 2.3 Orthogonality of signals for an optimum filter.

Figure 2.4 Loci of points with constant

(contour plots). (a) Case

and (b...

Figure 2.5 An application of the Wiener filter theory.

Figure 2.6 Magnitude of

given by (2.63) for

,

,

dB, and

.

Figure 2.7 Linear predictor of order

.

Figure 2.8 Forward prediction error filter.

Figure 2.9 (a) Analysis and (b) synthesis of AR

processes.

Figure 2.10 Relations among vectors in the LS minimization.

Figure 2.11 Singular value decomposition of matrix

.

Figure 2.12 Scheme to estimate the impulse response of an unknown system.

Figure 2.13 Basic scheme to measure the impulse response of an unknown syste...

Figure 2.14 Autocorrelation function of

.

Figure 2.15 Sliding window method to measure the impulse response of an unkn...

Figure 2.16 General configuration of an interference canceller.

Figure 2.17 Block diagram of an interference canceller.

Figure 2.18 Specific configuration of an interference canceller.

Figure 2.19 Transmission between two users in the public network.

Figure 2.20 Configuration to remove the echo of signal

caused by the hybri...

Figure 2.21 Scheme to remove a sinusoidal interferer from a wideband signal....

Figure 2.22 Lattice filter.

Chapter 3

Figure 3.1 Structure of an adaptive transversal filter at instant

.

Figure 3.2 Behaviour of

and sign of the gradient vector

in the scalar ca...

Figure 3.3 Loci of points with constant

and trajectory of

in the two dim...

Figure 3.4

as a function of

for

and

. In the case

and

,

is still...

Figure 3.5

and

as a function of

for different values of

:

.

Figure 3.6

as a function of the eigenvalue spread

.

Figure 3.7 Block diagram of an adaptive transversal filter adapted according...

Figure 3.8 Realizations of (a) input

, (b) coefficient

, and (c) square er...

Figure 3.9

as a function of

.

Figure 3.10 Behaviour of

obtained by using two values of

.

Figure 3.11 Predictor of order

.

Figure 3.12 Convergence curves for the predictor of order

, obtained by the...

Figure 3.13 Comparison among curves of convergence of the mean obtained by t...

Figure 3.14 Convergence curves for the predictor of order

, obtained by the...

Figure 3.15 Convergence curves for the predictor of order

, obtained by the...

Figure 3.16 Comparison of convergence curves for the predictor of order

, o...

Figure 3.17 Comparison of convergence curves obtained by three versions of t...

Figure 3.18 Reference system for a RLS adaptive algorithm.

Figure 3.19 Convergence curves for the predictor of order

, obtained by the...

Figure 3.20 Convergence curves of the MSE for system identification using (a...

Figure 3.21 Adaptive scheme to estimate the input–output relation of a syste...

Figure 3.22 Frequency response of a notch filter.

Figure 3.23 Configuration to cancel a sinusoidal interferer of known frequen...

Chapter 4

Figure 4.1 Radio channel model.

Figure 4.2 Radiation mask of the GSM system with a bandwidth of 200 kHz arou...

Figure 4.3 Conventional superheterodyne receiver.

Figure 4.4 Direct conversion receiver.

Figure 4.5 Double conversion with wideband IF.

Figure 4.6 Baseband equivalent model of a transmission channel including a n...

Figure 4.7 AM/AM and AM/PM characteristics of a TWT for

,

,

, and

.

Figure 4.8 AM/AM characteristic of an SSPA.

Figure 4.9 AM/AM experimental characteristic of two amplifiers operating at ...

Figure 4.10 Simplified model of the phase‐noise power spectral density.

Figure 4.11 Electrical equivalent circuit at the receiver.

Figure 4.12 Representation of

in the complex plane.

Figure 4.13 Ground reflection model.

Figure 4.14 Example of propagation in indoor environment.

Figure 4.15 Attenuation fluctuation as function of distance in wireless chan...

Figure 4.16 Illustration of the Doppler shift.

Figure 4.17 Physical representation (a) and model in time (b) and frequency ...

Figure 4.18 The Rice probability density function for various values of

. T...

Figure 4.19 Classical Doppler spectrum.

Figure 4.20 Discrete time model of a radio channel.

Figure 4.21 Model to generate the

‐th coefficient of a time‐varying channel...

Figure 4.22 Nine realizations of

for a Rayleigh channel with an exponentia...

Figure 4.23 Propagation model for an LOS scenario.

Figure 4.24 Channel correlation (4.139) at adjacent antennas in a fading MIM...

Figure 4.25 (a) Attenuation and (b) envelope delay distortion for two typica...

Figure 4.26 Signal to quantization noise ratio as a function of the input si...

Figure 4.27 Three of the many signal paths in a simplified telephone channel...

Figure 4.28 Example of mmWave channel in the angular domain.

Chapter 5

Figure 5.1 Block diagram of a vector quantizer.

Figure 5.2 Partition of the source space

in four subsets or Voronoi region...

Figure 5.3 Example of partition for

and

.

Figure 5.4 Generalized Lloyd algorithm for designing a vector quantizer.

Figure 5.5 LBG algorithm with splitting procedure.

Figure 5.6 Operations of the LBG algorithm with splitting procedure.

Figure 5.7 Values of the distortion as a function of the number of vectors

Figure 5.8 Comparison between full search and tree search.

Figure 5.9 Multistage (two‐stage) VQ.

Figure 5.10 Product code VQ.

Chapter 6

Figure 6.1 Simplified model of a transmission system.

Figure 6.2 Two rectangular QAM constellations and corresponding bit map (Gra...

Figure 6.3 8‐PSK constellation and decision regions.

Figure 6.4 Decision regions for (a) QPSK and (b) 16‐QAM constellations.

Figure 6.5 Partitions of the 16‐QAM constellation.

Figure 6.6 Approximate versus exact metrics.

Figure 6.7 Memoryless binary symmetric channel.

Figure 6.8 Bit error probability as a function of

for

‐PAM.

Figure 6.9 Bit error probability as a function of

for

‐QAM with a rectang...

Figure 6.10 Bit error probability as a function of

for

‐PSK.

Figure 6.11 Illustration of

for a typical behaviour of the function

.

Figure 6.12

required for a given rate

, for different uncoded modulation ...

Figure 6.13 Bit error probability as a function of

for an uncoded 2‐PAM sy...

Figure 6.14 Capacity

of an ideal AWGN channel for Gaussian for

‐PAM input...

Figure 6.15 The

function and relative bounds.

Chapter 7

Figure 7.1 Block diagram of a baseband digital transmission system.

Figure 7.2 Signals at various points of a quaternary PAM transmission system...

Figure 7.3 Characteristic of a threshold detector for quaternary symbols wit...

Figure 7.4 The PAM signal as output of an interpolator filter.

Figure 7.5 Block diagram of a passband digital transmission system.

Figure 7.6 Fourier transforms of baseband signal and modulated signal.

Figure 7.7 QAM transmitter: complex‐valued representation.

Figure 7.8 QAM receiver: complex‐valued representation.

Figure 7.9 Frequency responses of channel and signals at various points of t...

Figure 7.10 Baseband equivalent model of a QAM transmission system.

Figure 7.11 Baseband equivalent model of PAM and QAM transmission systems.

Figure 7.12 Two examples of transmit pulse

. (a) Wideband. (b) Narrowband....

Figure 7.13 Frequency response of the transmission channel. (a) Channel. (b)...

Figure 7.14 Receiver structure with analog and discrete‐time filters.

Figure 7.15 Discrete‐time equivalent scheme, with period

, of a QAM system....

Figure 7.16 Time and frequency plots of (a)

raised cosine

and (b)

square roo

...

Figure 7.17 Pulse shape for the computation of the eye diagram.

Figure 7.18 Desired component

as a function of

,

.

Figure 7.19 Eye diagram for quaternary transmission and pulse

of Figure 7....

Figure 7.20 Eye diagram for quaternary transmission and raised cosine pulse

Figure 7.21 Height

and width

of the

pupil

of an eye diagram.

Figure 7.22 Optimum receiver structure for a channel with additive white noi...

Figure 7.23 Linear equalizer as a Wiener filter. (a) Continuous‐time model. ...

Figure 7.24 Receiver implementation by an analog matched filter followed by ...

Figure 7.25 Receiver implementation by discrete‐time filters.

Figure 7.26 Discrete‐time equivalent channel model and linear equalizer.

Figure 7.27 Fractionally spaced linear equalizer.

Figure 7.28 Discrete‐time Nyquist pulses and relative Fourier transforms. (a...

Figure 7.29 Discrete‐time pulses in a DFE. (a) Before the FF filter. (b) Aft...

Figure 7.30 Simplified scheme of a DFE, where only the feedback filter is in...

Figure 7.31 General structure of the DFE.

Figure 7.32 FS‐DFE structure.

Figure 7.33 Block diagram of a DFE with FF in the FD. To simplify notation t...

Figure 7.34 DFE zero‐forcing.

Figure 7.35 DFE‐ZF as whitened matched filter followed by a canceller of ISI...

Figure 7.36 Predictive DFE: the FF filter is a linear equalizer zero forcing...

Figure 7.37 Predictive DFE with the FF filter as a minimum‐MSE linear equali...

Figure 7.38 Passband modulation scheme with phase offset introduced by the c...

Figure 7.39 Frequency response of a passband matched filter.

Figure 7.40 QAM passband receiver.

Figure 7.41 QAM passband receiver for transmission over telephone channels....

Figure 7.42 Portion of the trellis diagram showing the possible transitions ...

Figure 7.43 Trellis diagram and determination of the survivor sequences. (a)...

Figure 7.44 Two receiver structures with i.i.d. noise samples at the decisio...

Figure 7.45 Error events of length (a) two and (b) three in a trellis diagra...

Figure 7.46 PR‐IV (modified duobinary) transmission system.

Figure 7.47 Input and output sequences for an ideal PR‐IV system.

Figure 7.48 Trellis diagrams for detection of interlaced sequences.

Figure 7.49 Survivor sequences at successive iterations of the VA for a dico...

Figure 7.50 Examples of (a) trellis diagram to compute the minimum distance ...

Figure 7.51 Ungerboeck's partitioning of the symbol set associated with a 16...

Figure 7.52 Reduced‐state trellis diagrams.

Figure 7.53 Bit error probability,

, as a function of

for

quadrature phas

...

Figure 7.54 Bit error probability,

, as a function of

for QPSK transmissi...

Figure 7.55 Bit probability error,

, as a function of

for 8‐PSK transmiss...

Figure 7.56 Bit probability error rate,

, as a function of

for 8‐PSK tran...

Figure 7.57 Block diagram of a system with TH precoding.

Figure 7.58 Illustration of the efficient extension of a two‐dimensional 16‐...

Figure 7.59 Block diagram of a system with flexible precoding.

Figure 7.60 System model (see also the front‐end of Figure 7.26).

Figure 7.61 LS channel estimate.

vs.

for CAZAC sequences (solid line) an...

Figure 7.62 Multirate system.

Figure 7.63 Polyphase decomposition of a multirate system.

Figure 7.64 Baseband equivalent model of a QAM system with discrete‐time fil...

Figure 7.65 Magnitude of the transmit filter frequency response, for a windo...

Figure 7.66 Transmit filter impulse response,

,

, for a windowed

square ro

...

Figure 7.67 General block diagram of a finite state sequential machine.

Figure 7.68 PAM transmitter with line encoder.

Figure 7.69 NRZ line codes.

Figure 7.70 RZ line codes.

Figure 7.71 B–

and delay modulation line codes.

Figure 7.72 Power spectral density of an AMI encoded message.

Figure 7.73 Schemes equivalent to Figure 7.1. (a) Analog equivalent. (b) Dig...

Figure 7.74 Schemes equivalent to Figure 7.1. (a) Analog equivalent. (b) Dig...

Figure 7.75 Implementation of a PR system using a digital filter.

Figure 7.76 Plot of

for duobinary (

) and modified duobinary (‐ ‐) filters...

Figure 7.77 PSD of a modified duobinary PR system and of a PAM system.

Figure 7.78 Four possible solutions to the detection problem in the presence...

Figure 7.79 PR system with

precoding

.

Figure 7.80 Precoder and decoder for a dicode filter

with

. (a) Precoder....

Figure 7.81 QAM with analog mixer.

Figure 7.82 QAM with digital and analog mixers.

Figure 7.83 Polyphase implementation of the filter

for

.

Chapter 8

Figure 8.1 Block diagram of an MC system, where the channel has been omitted...

Figure 8.2 Equivalent MC system with input–output relation expressed in term...

Figure 8.3 Implementation of an MC system using the polyphase representation...

Figure 8.4 Equivalent MC system implementation.

Figure 8.5 Block diagrams of: (a) parallel to serial converter, (b) serial t...

Figure 8.6 Block diagram of an MC system with uniform filter banks: (a) gene...

Figure 8.7 Block diagram of an MC system with efficient implementation.

Figure 8.8 Block diagram of (a) transmitter and (b) receiver in a transmissi...

Figure 8.9 Filter frequency responses in a non‐critically sampled system.

Figure 8.10 Efficient implementation of the transmitter of a system employin...

Figure 8.11 Efficient implementation of the receiver of a system employing n...

Figure 8.12 Block diagram of an OFDM system with impulse response of the pro...

Figure 8.13 Amplitude of the frequency responses of adjacent subchannel filt...

Figure 8.14 Amplitude of the frequency responses of adjacent subchannel filt...

Figure 8.15 Baseband analog transmission of an MC signal.

Figure 8.16 (a) Passband analog MC transmission scheme; (b) baseband equival...

Figure 8.17 Block diagram of an OFDM system with CP and frequency‐domain sca...

Figure 8.18 OFDM discrete‐time model.

Figure 8.19 OFDM relation between transmitted data and signal at detection p...

Figure 8.20 Per‐subchannel equalization (DFE) for an FMT system with non‐cri...

Figure 8.21 (a) Equalization scheme for FMT in the case of approximately con...

Figure 8.22 Pilot symbols arrangements in the time‐frequency plane: the blac...

Figure 8.23 Other pilot symbols arrangements in the time‐frequency plane.

Figure 8.24 SC‐FDMA scheme, for user 1: (a) transmitter, (b) receiver.

Chapter 9

Figure 9.1 (a) Relation between the transmitted digital signal and the discr...

Figure 9.2 (a) A MIMO system and flat fading channel, (b) equivalent discret...

Figure 9.3 NB MIMO channel model.

Figure 9.4 SIMO combiner.

Figure 9.5 MIMO combiner.

Figure 9.6 V‐BLAST system.

Figure 9.7 MISO linear precoder.

Figure 9.8 MISO antenna selection or switched transmit diversity.

Figure 9.9 Example of generation of the second stream for dirty paper coding...

Figure 9.10 Hybrid beamformer operating as a combiner.

Figure 9.11 Spectral efficiency for analog, digital, and hybrid beamforming ...

Chapter 10

Figure 10.1 Baseband equivalent model of a DS system: (a) transmitter, (b) m...

Figure 10.2 Spreading operation: (a) correlator, (b) interpolator filter.

Figure 10.3 Equivalent scheme of spreader and pulse‐shaping filter in a DS s...

Figure 10.4 Optimum receiver with analog filters for a DS system with ideal ...

Figure 10.5 Optimum receiver with discrete‐time filters for a DS system with...

Figure 10.6 Multiuser receiver for a CDMA synchronous system with an ideal A...

Figure 10.7 (a) Block diagram of an FH/

‐FSK system. (b) Time-frequency allo...

Figure 10.8 Frequency distribution for an FH/4‐FSK system with bands non‐ove...

Figure 10.9 Frequency distribution for an FH/4‐FSK system with bands overlap...

Figure 10.10 Power spectral density of an

‐QAM signal with minimum bandwidt...

Figure 10.11 Chip matched filter receiver for a dispersive channel.

Figure 10.12 Two receiver structures: (a) chip matched filter with despreade...

Figure 10.13 Rake receiver for a channel with

resolvable paths.

Figure 10.14 (a) Single‐user receiver, and (b) multiuser receiver.

Figure 10.15 Receiver as a fractionally‐spaced chip equalizer.

Figure 10.16 Receiver as a fractionally‐spaced symbol equalizer.

Figure 10.17 Receiver as MF and multiuser detector.

Figure 10.18 Eight orthogonal signals obtained from the Walsh code of length...

Chapter 11

Figure 11.1 Device for the sum of two elements

and

of

.

Figure 11.2 Device for the multiplication of two elements

and

of

.

is...

Figure 11.3 Scheme of an encoder for cyclic codes using a shift register wit...

Figure 11.4 Scheme of an encoder for cyclic codes using a shift register wit...

Figure 11.5 Device to compute the division of the polynomial

by

. After

Figure 11.6 Scheme of a decoder for binary cyclic single error correcting co...

Figure 11.7 Generation of a PN sequence as a repetition of a code word of a ...

Figure 11.8 Recursive filter to compute syndromes (see (11.201)).

Figure 11.9 (a) Encoder and (b) tree diagram for the convolutional code of E...

Figure 11.10 (a) Trellis diagram and (b) state diagram for the convolutional...

Figure 11.11 Block diagram of an encoder for a convolutional code with

,

,...

Figure 11.12 Block diagram of an encoder for a systematic convolutional code...

Figure 11.13 Examples of encoders for three convolutional codes.

Figure 11.14 Trellis diagram of the code of Example 11.3.1; the labels repre...

Figure 11.15 State diagram of the code of Example 11.3.1; the labels represe...

Figure 11.16 State diagram of the code of Example 11.3.1; node (0,0) is spli...

Figure 11.17 State diagram of the code of Example 36; node (0,0) is split to...

Figure 11.18 (a) Encoder and (b) state diagram for a catastrophic convolutio...

Figure 11.19 Two distinct infinite sequences of information bits that produc...

Figure 11.20 Transition diagram of the Fano algorithm.

Figure 11.21 (a) Block diagram of the encoder and bit mapper for a trellis c...

Figure 11.22 Symbol error probabilities for the 512‐state 16‐PAM trellis cod...

Figure 11.23 Transmission scheme with concatenated codes and interleaver.

Figure 11.24 Soft‐output VA.

Figure 11.25 Modified soft‐output VA.

Figure 11.26 Encoder of a turbo code with code rate

.

Figure 11.27 Turbo encoder adopted by the UMTS standard.

Figure 11.28 Recursive systematic encoder that generates a code with the sam...

Figure 11.29 A 16‐state component encoder for the turbo code of Berrou and G...

Figure 11.30 Principle of the decoder for a turbo code with rate

.

Figure 11.31 Termination of trellis.

Figure 11.32 Performance of the turbo code defined by the UMTS standard, wit...

Figure 11.33 Curves of convergence of the decoder for the turbo code defined...

Figure 11.34 Performance of the turbo code defined by the UMTS standard achi...

Figure 11.35 Encoder structure, bit mapper, and modulator; for 16‐PAM:

.

Figure 11.36 Iterative detection and decoding.

Figure 11.37 Tanner graph corresponding to the parity check matrix of the (7...

Figure 11.38 Tanner graph corresponding to the parity check matrix of code (...

Figure 11.39 Illustrative example of iterative decoding: each sub‐figure sho...

Figure 11.40 Illustrative example of a 4‐cycle Thanner graph. The cycle is s...

Figure 11.41 Message‐passing decoding.

Figure 11.42

function.

Figure 11.43 Performance of LDPC decoding with Code 2 and 16‐QAM for various...

Figure 11.44 Simulation results for a regular (3,6) LDPC, an optimized irreg...

Figure 11.45 Polar code encoding.

Figure 11.46 Polar code encoding with CRC.

Figure 11.47 Tanner graph for transformation matrix

.

Figure 11.48 One

‐block at stage 

of the Tanner graph.

Figure 11.49 Structure of the polar code SC decoder.

Figure 11.50

‐block at stage 

with LLRs and detected bits.

Figure 11.51 Tanner graph for

, as used for decoding.

Figure 11.52

‐block at stage 

with mean values of LLRs.

Figure 11.53 Tanner graph for

, as used for DE/GA.

Figure 11.54 Tanner graph of

for encoding.

Figure 11.55 Tanner graph of

for decoding with punctured position.

Figure 11.56 Tanner graph of

for decoding with shortened position.

Figure 11.57 Performance of a polar code of length

and rate

under SC and...

Figure 11.58 Spectral efficiency versus

for various codes proposed over ti...

Chapter 12

Figure 12.1 Block diagram of a transmission system with trellis coded modula...

Figure 12.2 Eight‐state trellis encoder and bit mapper for the transmission ...

Figure 12.3 Trellis diagram for the encoder of Figure 12.2 and the map of Fi...

Figure 12.4 Section of the trellis for the decoder of an eight‐state trellis...

Figure 12.5 Partitioning of the symbol set for an 8‐PSK system.

Figure 12.6 Partitioning of the symbol set for a 16‐QAM system.

Figure 12.7 (a)

lattice; (b)

lattice.

Figure 12.8 The integer lattice

as template for QAM constellations.

Figure 12.9 Binary partitioning chain of the lattice

.

Figure 12.10 The four cosets of

in the partition

.

Figure 12.11 Uncoded transmission of 2 bits per modulation interval by 4‐PSK...

Figure 12.12 Transmission of 2 bits per modulation interval using (a) a two‐...

Figure 12.13 Trellis codes with (a) 4, (b) 8, and (c) 16 states for transmis...

Figure 12.14 Encoder/bit‐mapper for a 4‐state trellis code for the transmiss...

Figure 12.15 Eight‐state trellis code for the transmission of 3 bits per mod...

Figure 12.16 General structure of the encoder/bit‐mapper for TCM.

Figure 12.17 Block diagram of a systematic convolutional encoder with feedba...

Figure 12.18 Partitioning of the lattice

.

Figure 12.19 Trellis diagram for the decoding of block codes obtained by the...

Chapter 13

Figure 13.1 Increasing order of factors

.

Figure 13.2 Representation of all possible loadings.

Figure 13.3 The Hughes‐Hartogs algorithm.

Figure 13.4 Description of the plane wave used by the KRJ algorithm.

Figure 13.5 Bisection search algorithm.

Figure 13.6 Equivalence between a continuous time system, (a) passband model...

Chapter 14

Figure 14.1 Analog front end for passband QAM systems.

Figure 14.2 Baseband equivalent model of the channel and analog front end fo...

Figure 14.3 Block diagram of a PLL.

Figure 14.4 Baseband model of a PLL.

Figure 14.5 Linearized baseband model of the PLL.

Figure 14.6 PLL baseband model in the presence of noise.

Figure 14.7 Linearized PLL baseband model in the presence of additive noise....

Figure 14.8 Plots of

as a function of

, for a second‐order loop filter wi...

Figure 14.9 Plots of

as a function of

, for a second‐order loop filter wi...

Figure 14.10 Plots of

as a function of

, for a second‐order loop filter w...

Figure 14.11 Plot of

as function of

for a second‐order loop.

Figure 14.12 Carrier recovery in PAM‐DSB systems.

Figure 14.13 Baseband and passband components of the product of two generic ...

Figure 14.14 Squarer/PLL for carrier recovery in PAM‐DSB systems.

Figure 14.15 Costas loop for PAM‐DSB systems.

Figure 14.16 Carrier recovery in QAM systems.

Figure 14.17 Extended Costas loop for QPSK systems.

Figure 14.18 Analog receiver for QAM systems.

Figure 14.19 Digital receiver for QAM systems.

Figure 14.20 Plot of the saw‐tooth function

.

Figure 14.21 (a) Transmitter time scale; (b) receiver time scale with

, for...

Figure 14.22 (a) Feedback estimator of

; (b) feedback estimator of

.

Figure 14.23 FB early‐late timing estimator.

Figure 14.24 NDA joint timing and phase (for

) estimator.

Figure 14.25 NDA timing estimator via spectral estimation for the case

....

Figure 14.26 Phase independent DA (DD) timing estimator.

Figure 14.27 DA (DD) joint phase and timing estimator.

Figure 14.28 DD&D

‐FB timing estimator.

Figure 14.29 Mueller and Muller type A timing estimator.

Figure 14.30 DD&D

estimator of the phasor

.

Figure 14.31 NDA estimator of the phasor

for

‐PSK.

Figure 14.32 (a) PHLL; (b) DD&D

‐FB phasor estimator.

Figure 14.33 Receiver of Figure 14.19 with interpolator and matched filter i...

Figure 14.34 NDA frequency offset estimator.

Figure 14.35 NDA‐ND

‐FB frequency offset estimator.

Figure 14.36 NDA‐D

‐FB frequency offset estimator.

Figure 14.37 Baseband transmitter for spread‐spectrum systems.

Figure 14.38 Digital receiver for spread‐spectrum systems.

Figure 14.39 Non‐coherent DLL.

Figure 14.40 Direct section of the non‐coherent MCTL.

Figure 14.41 Direct section of the coherent DLL.

Figure 14.42 The four different cases on the location of the timing offset....

Figure 14.43 Example of payload using repetitive training symbol for STO est...

Figure 14.44 Example of timing metric for an AWGN channel.

Chapter 15

Figure 15.1 Discrete‐time equivalent channel and equalizer filter.

Figure 15.2 Illustration of the cost function

for the system

and of the ...

Figure 15.3 Update of the parameters

,

.

Figure 15.4 Illustration of the transformation

.

Figure 15.5 Characteristic of the pseudo error

as a function of the equali...

Figure 15.6 Evolution in time of the

contour

for a two‐dimensional constel...

Figure 15.7 Characteristic of the pseudo error

as a function of the equali...

Figure 15.8 Block diagram of a self‐training equalizer for a PR‐IV system us...

Figure 15.9 Block diagram of a self‐training equalizer with the contour algo...

Figure 15.10 Block diagram of a self‐training equalizer with the Sato algori...

Figure 15.11 Block diagram of a self‐training equalizer using the CMA.

Figure 15.12 The 64‐QAM constellation and the circle of radius

.

Figure 15.13 Illustration of the contour line and surface

for a 64‐QAM con...

Figure 15.14 Illustration of the rotation of the symbol constellation in the...

Figure 15.15 Illustration of the convergence of the contour algorithm for a ...

Figure 15.16 MSE convergence with the Sato algorithm for a QPR‐IV system.

Figure 15.17 MSE convergence with the contour algorithm for a QPR‐IV system....

Figure 15.18 Overall baseband equivalent channel impulse response for simula...

Figure 15.19 Convergence behaviour of MSE and parameter

using the contour ...

Figure 15.20 Illustration of the convergence behaviour of MSE and second ord...

Chapter 16

Figure 16.1 Transmitter of an 8‐PSK system.

Figure 16.2 Receiver of an

‐PSK system. Thresholds are set at

,

.

Figure 16.3 Schemes of (a) transmitter and (b) receiver for a BPSK system wi...

Figure 16.4 Comparison between PSK and DPSK.

Figure 16.5 Non‐coherent baseband differential receiver. Thresholds are set ...

Figure 16.6 Baseband equivalent scheme of Figure 16.5.

Figure 16.7 Non‐coherent 1 bit differential detector.

Figure 16.8 Baseband equivalent scheme of Figure 16.7.

Figure 16.9 FM discriminator and integrate and dump filter.

Figure 16.10 Implementation of a limiter–discriminator.

Figure 16.11 Baseband equivalent scheme of a FM discriminator followed by an...

Figure 16.12 Non‐coherent ML receiver of the type

square‐law detector

....

Figure 16.13 Implementation of a branch of the scheme of Figure 16.12 by a c...

Figure 16.14 Non‐coherent ML receiver of the type

envelope detector

, using p...

Figure 16.15 (a) Ideal implementation of an envelope detector, and (b) two s...

Figure 16.16 Two ML receivers for a non‐coherent 2‐FSK system. (a) Square‐la...

Figure 16.17 Envelope detector receiver for an on–off keying system.

Figure 16.18 Two receivers for a DSB modulation system with

‐ary signalling...

Figure 16.19 Bit error probability as a function of

for BPSK and binary FS...

Figure 16.20 Generation of a binary (non‐coherent) FSK signal by two oscilla...

Figure 16.21 (a) Binary FSK waveforms for

, and

and (b) transmitted signa...

Figure 16.22 Coherent demodulator for orthogonal binary FSK.

Figure 16.23 Non‐coherent demodulator for orthogonal binary FSK.

Figure 16.24 Limiter–discriminator FSK demodulator.

Figure 16.25 Waveforms as given by (16.98) with

,

,

, and

.

Figure 16.26 CPFSK modulator. (a) Passband model and (b) baseband equivalent...

Figure 16.27 Comparison between FSK and MSK signals. (a) FSK waveforms, (b) ...

Figure 16.28 Continuous part of the PSD of a CPFSK signal for five values of...

Figure 16.29 MSK demodulator classification.

Figure 16.30 Differential (1BDD) non‐coherent MSK demodulator. (a) Passband ...

Figure 16.31 Coherent MSK demodulator.

Figure 16.32 Comparison among various error probabilities.

Figure 16.33 Normalized PSD of the complex envelope of signals obtained by t...

Figure 16.34 GMSK modulator.

Figure 16.35 Overall pulse

, with amplitude normalized to

, for various va...

Figure 16.36 Phase deviation

of (a) GMSK signal for

, and (b) MSK signal....

Figure 16.37 Trajectories of the phase deviation of a GMSK signal for

(sol...

Figure 16.38 Estimate of the PSD of a GMSK signal for various values of

.

Figure 16.39 GMSK modulator: configuration I.

Figure 16.40 GMSK modulator: configuration II.

Figure 16.41 Frequency responses of

and

, for

, and various lengths of t...

Figure 16.42 GMSK modulator: configuration III.

Figure 16.43 Digital implementation of the VCO.

Figure 16.44 GMSK modulator with a complex‐valued digital VCO.

Figure 16.45 Pulse

for a GMSK signal with

.

Figure 16.46 Linear approximation of a GMSK signal.

is a suitable pulse wh...

Figure 16.47

as a function of

for the four modulation systems of Table 1...

Figure 16.48

as a function of

for a coherently demodulated GMSK (

), for...

Figure 16.49 Eye diagram at the decision point of the 1BDD for a GMSK system...

Figure 16.50

as a function of

obtained with the 1BDD for GMSK, for an id...

Figure 16.51 Comparison between Viterbi algorithm and DFE preceded by a MF f...

Figure 16.52 Three examples of phase response pulses for CPM: (a) PSK, (b) C...

Chapter 17

Figure 17.1 Model of a full‐duplex PAM transmission system.

Figure 17.2 Configuration of an echo canceller for a PAM transmission system...

Figure 17.3 Model of a dual‐duplex transmission system.

Figure 17.4 A set of

interlaced echo cancellers (EC).

Figure 17.5 Block diagram of an adaptive transversal filter echo canceller....

Figure 17.6 Block diagram of an adaptive distributed‐arithmetic echo cancell...

Figure 17.7 Configuration of an echo canceller for a QAM transmission system...

Figure 17.8 Configuration of an echo canceller for a DMT transmission system...

Figure 17.9 Block diagram of transmission channel and DFE structure.

Figure 17.10 Achievable rates of individual users versus cable length using ...

Figure 17.11 Achievable rates of individual users versus cable length using ...

Figure 17.12 Achievable rates of individual users versus cable length with a...

Figure 17.13 Achievable rates of individual users versus cable length with 1...

Figure 17.14 Achievable rates of individual users versus cable length with 1...

Chapter 18

Figure 18.1 Illustration of cell and frequency reuse concepts; cells with th...

Figure 18.2 Example of radio frame configuration with index

.

Figure 18.3 5G NR frame structure and basic terminologies. Source: Lin et al...

Figure 18.4 5g NR (a) PDCCH and (b) PUCCH.

Figure 18.5 The NR SSB.

Figure 18.6 The beam sweeping procedure in NR.

Figure 18.7 PRACH formats (long sequence).

Figure 18.8 Illustration of the network slicing architecture.

Figure 18.9 GSM system structure.

Figure 18.10 Bandwidth allocation of the GSM system.

Figure 18.11 TDM frame structure and slot structure of the GSM system.

Figure 18.12 Channel coding for the GSM system.

Figure 18.13 Illustration of the CSMA/CA protocol.

Figure 18.14 FDMA structure of the DECT system.

Figure 18.15 TDM frame structure and slot structure for the DECT system.

Figure 18.16 Illustration of links between ADSL modems over the subscriber l...

Figure 18.17 Illustration of FTTC and FTTH architectures.

Figure 18.18 Spectral allocation of signals for (a) HDSL and ADSL, and (b) V...

Figure 18.19 Illustration of 10BASE‐T signal characteristics.

Figure 18.20 Illustration of (a) 100BASE‐TX signal characteristics and (b) 1...

Figure 18.21 Illustration of a dual duplex transmission system.

Figure 18.22 Illustration of signal characteristics for transmission over to...

Figure 18.23 Illustration of the HFC network topology.

Figure 18.24 Examples of frequency allocations in HFC networks.

Figure 18.25 Example of a MAP message.

Figure 18.26 Finite state machine used by the cable modem for the registrati...

Figure 18.27 Finite state machine used by the HC for the registration proced...

Figure 18.28 Illustration of (a) FDMA, and (b) TDMA.

Figure 18.29 TDM in the European base group at 2.048 Mbit/s. (a) Basic schem...

Chapter 19

Figure 19.1 Block diagram of a QPR‐IV transceiver.

Figure 19.2 Overall analog channel considered for the joint optimization of ...

Figure 19.3 Convergence of the adaptive NEXT canceller.

Figure 19.4 Convergence of the adaptive equalizer for (a) best‐case sampling...

Figure 19.5 Convergence of the adaptive equalizer for worst‐case timing phas...

Figure 19.6 Adaptive distributed‐arithmetic NEXT canceller.

Figure 19.7 Digital adaptive equalizer: coefficient circulation and updating...

Figure 19.8 Coefficients and signals at the input of the multiply‐accumulate...

Figure 19.9 Adaptive digital equalizer: computation of coefficient adaptatio...

Figure 19.10 Elastic buffer: control of the read pointer.

Figure 19.11 Amplitude of the frequency response for a voice‐grade twisted‐p...

Figure 19.12 Dual‐duplex transmission over two wire pairs.

Figure 19.13 State diagram of 100BASE‐T2 physical layer control.

Figure 19.14 Signal encoding during idle mode.

Figure 19.15 Signal encoding during data mode.

Figure 19.16 Two‐dimensional symbols sent during idle and data transmission....

Figure 19.17 Principal signal processing functions performed in a 100BASE‐T2...

Figure 19.18 Spectral template specified by the 100BASE‐T2 standard for the ...

Figure 19.19 Crosstalk disturbance by: (a) alien NEXT from another synchrono...

Guide

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