Safwan El Assad is Associate Professor (HDR) at Polytech Nantes, France. From 1988 to 2005, his research activities concerned radar imagery and digital communications. With a background in radar imagery and digital communications, today his research largely focuses on chaos-based cryptography.Dominique Barba is a retired Professor from Polytech Nantes. His research has focused for over 45 years on the processing of still and moving images (improvement, compression), their analysis, human and artificial vision, as well as digital communications (compression).

• Foreword xiPart 1. Theory of Information 1Introduction to Part 1 3Chapter 1. Introduction to Telecommunications 51.1. Role of a communication system 51.1.1. Types of services offered by communication systems 61.1.2. Examples of telecommunications services 71.2. Principle of communication 71.3. Trend towards digital communications 10Chapter 2. Measurement of Information of a Discrete Source and Channel Capacity 132.1. Introduction and definitions 132.2. Examples of discrete sources 142.2.1. Simple source (memoryless) 142.2.2. Discrete source with memory 142.2.3. Ergodic source: stationary source with finite memory 152.2.4. First order Markovian source (first order Markov chain) 152.3. Uncertainty, amount of information and entropy (Shannon’s 1948 theorem) 162.3.1. Entropy of a source 182.3.2. Fundamental lemma 182.3.3. Properties of entropy 192.3.4. Examples of entropy 192.4. Information rate and redundancy of a source 202.5. Discrete channels and entropies 202.5.1. Conditional entropies 222.5.2. Relations between the various entropies 242.6. Mutual information 252.7. Capacity, redundancy and efficiency of a discrete channel 272.7.1. Shannon’s theorem: capacity of a communication system 272.8. Entropies with k random variables 29Chapter 3. Source Coding for Non-disturbance Channels 313.1. Introduction 313.2. Interest of binary codes 313.3. Single decoding codes 323.3.1. Regular code 333.3.2. Single-decoded code (decipherable or decodable code) 333.3.3. Instantaneous code (irreducible code) 343.3.4. Prefix 343.3.5. Design of an instantaneous binary code 353.3.6. Kraft McMillan inequality 363.4. Average codeword length 363.4.1. Coding efficiency in terms of transmission speed 363.4.2. Minimum average codeword length lmin 373.5. Capacity, efficiency and redundancy of a code 383.6. Absolute optimal codes 383.7. K-order extension of a source 393.7.1. Entropy of the 2nd order extension of a source [S] 393.7.2. Simple example of the interest of coding a source extension 403.8. Shannon’s first theorem 413.9. Design of optimal binary codes 423.9.1. Shannon–Fano coding 423.9.2. Huffman code 43Chapter 4. Channel Coding for Disturbed Transmission Channels 474.1. Introduction 474.2. Shannon’s second theorem (1948) 484.3. Error correction strategies 484.4. Classification of error detection codes or error correction codes 494.5. Definitions related to code performance 504.5.1. Efficiency 504.5.2. Weight of linear code or Hamming’s weight 504.5.3. Hamming distance 514.6. Form of the decision 514.6.1. Maximum a posteriori likelihood decoding 524.7. Linear group codes 534.7.1. Decoding ball concept: Hamming’s theorem 544.7.2. Generating matrix [G] and test matrix [H] 554.7.3. Error detection and correction 584.7.4. Applications: Hamming codes (r = 1) 594.7.5. Coding and decoding circuits 624.7.6. Extension of Hamming codes 634.7.7. Relationships between columns of the matrix [H’] 644.8. Cyclic codes 654.8.1. Introduction 654.8.2. Expression of a circular permutation 674.8.3. Generating polynomial g(x), generating matrix [G] and theorem of cyclic codes 684.8.4. Dual code generated by h(x) and parity control matrix [H] 714.8.5. Construction of the codewords (coding) 724.9. Linear feedback shift register (LFSR) and its applications 834.9.1. Properties 844.9.2. Linear feedback shift register encoder and decoder (LFSR) 854.9.3. Coding by multiplication: non-systematic code 924.9.4. Detection of standard errors with cyclic codes 954.9.5. Pseudo-random sequence generators: M-sequences, Gold, Kasami and Trivium 97Part 2. Baseband Digital Transmissions and with Carrier Modulation 117Introduction to Part 2 119Chapter 5. Binary to M-ary Coding and M-ary to Signal Coding: On-line Codes 1235.1. Presentation and typology 1235.2. Criteria for choosing an on-line code 1255.3. Power spectral densities (PSD) of on-line codes 1265.4. Description and spectral characterization of the main linear on-line codes with successive independent symbols 1275.4.1. Binary NRZ code (non-return to zero): two-level code, two types of code 1285.4.2. NRZ M-ary code 1315.4.3. Binary RZ code (return to zero) 1325.4.4. Polar RZ on-line code 1345.4.5. Binary biphase on-line code (Manchester code) 1365.4.6. Binary biphase mark or differential code (Manchester mark code) 1385.5. Description and spectral characterization of the main on-line non-linear and non-alphabetic codes with successive dependent symbols 1395.5.1. Miller’s code 1405.5.2. Bipolar RZ code or AMI code (alternate marked inversion) 1415.5.3. CMI code (code mark inversion) 1445.5.4. HDB-n code (high density bipolar on-line code of order n) 1455.6. Description and spectral characterization of partial response linear codes 1475.6.1. Generation and interest of precoding 1485.6.2. Structure of the coder and precoder 1505.6.3. Power spectral density of partial response linear on-line codes 1535.6.4. Most common partial response linear on-line codes 155Chapter 6. Transmission of an M-ary Digital Signal on a Low-pass Channel 1676.1. Introduction 1676.2. Digital systems and standardization for high data rate transmissions 1686.3. Modeling the transmission of an M-ary digital signal through the communication chain 1706.3.1. Equivalent energy bandwidth Δfe of a low-pass filter 1746.4. Characterization of the intersymbol interference: eye pattern 1756.4.1. Eye pattern 1766.5. Probability of error Pe 1796.5.1. Probability of error: case of binary symbols ak = ±1 1806.5.2. Probability of error: case of binary RZ code 1856.5.3. Probability of error: general case of M-ary symbols 1876.5.4. Probability of error: case of bipolar code 1936.6. Conditions of absence of intersymbol interference: Nyquist criteria 1966.6.1. Nyquist temporal criterion 1966.6.2. Nyquist frequency criterion 1966.6.3. Interpretation of the Nyquist frequency criterion 1976.7. Optimal distribution of filtering between transmission and reception 2066.7.1. Expression of the minimum probability of error for a low-pass channel satisfying the Nyquist criterion 2116.8. Transmission with a partial response linear coder 2126.8.1. Transmission using the duobinary code 2136.8.2. Transmission using 2nd order interleaved bipolar code 2156.8.3. Reception of partial response linear codes 2176.8.4. Probability of error Pe 220Chapter 7. Digital Transmissions with Carrier Modulation 2237.1. Introduction and schematic diagram of a digital radio transmission 2237.2. Multiple access techniques and most common standards 2257.3. Structure of a radio link, a satellite link and a mobile radio channel 2307.3.1. Structure of a terrestrial link (one jump) 2307.3.2. Structure of a satellite telecommunication link 2307.3.3. Mobile radio channel 2317.4. Effects of multiple paths and non-linearities of power amplifiers 2327.4.1. Effects of multiple paths: simple case of a direct path and only one delayed path 2327.4.2. Effects of non-linearities of power amplifiers 2357.5. Linear digital carrier modulations 2377.5.1. Principle 2377.5.2. General characteristics of the modulated signal s(t) 2387.6. Quadrature digital linear modulations: general structure of the modulator, spatial diagram, constellation diagram and choice of a constellation 2417.6.1. General structure of the modulator 2427.6.2. Spatial diagram (or vectorial) and constellation diagram 2437.6.3. Choosing a constellation diagram 2457.7. Digital radio transmission and equivalent baseband digital transmission: complex envelope 2467.7.1. Equivalent baseband digital transmission: complex envelope 2477.8. Equivalent baseband transmission, interest and justification: analytical signal and complex envelope 2517.8.1. Interest: important simplification in numerical simulation 2517.8.2. Analytical signal and complex envelope of a modulated signal 2517.9. Relationship between band-pass filter H and equivalent low-pass filter He 2537.9.1. Probability of errors 2587.10. M-ary Phase Shift Keying Modulation (M-PSK) 2587.10.1. Binary Phase Shift Keying (BPSK) modulation and demodulation 2597.10.2. Quaternary Phase Shift Keying (QPSK) modulation and demodulation 2627.10.3. Differential M-PSK receiver 2677.10.4. Offset Quaternary Phase Shift Keying (OQPSK) 2717.11. M-ary Quadrature Amplitude Modulation (M-QAM) 2747.12. Detailed presentation of 16-QAM modulation and demodulation 2757.12.1. Spectral occupancy of the 16-QAM modulated signal 2777.13. Amplitude and Phase Shift Keying Modulation (APSK) 2807.13.1. CIR (4, 4, 4, 4) modulation: 4 amplitudes, 4 phases (ITU-V29, 1980) 2807.14. Detailed presentation of the 8-PSK modulation and demoludation 2817.14.1. Differential coding and decoding of the 8-PSK modulation 2847.14.2. Realization of the differential encoder and decoder: by Simulink simulation (MATLAB) and hardware implementation based on a ROM or EPROM memory 2857.15. Performances of modulations in spectral occupancy and efficiency 291References 293Index 295