Transitions from digital communications to quantum communications : concepts and prospects / / Malek Benslama, Hadj Batatia, Abderraouf Messai

• Record Nr.: UNINA9910812858003321
• Autore: Benslama Malek
• Pubbl/distr/stampa: London, [England] ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2016; ©2016
• ISBN: 1-119-33019-X; 1-119-33027-0
• Descrizione fisica: 1 online resource (218 p.)
• Collana: Networks and Telecommunications Series
• Disciplina: 621.382
• Soggetti: Digital communications; Quantum communication
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Table of Contents; Dedication; Title; Copyright; Foreword; Preface; Introduction; List of Acronyms; PART 1: Theory; 1 Non-linear Signal Processing; 1.1. Distributions; 1.2. Variance; 1.3. Covariance; 1.4. Stationarity; 1.5. Bayes inference; 1.6. Tensors in signal processing; 1.7. Processing the quantum signal; 2 Non-Gaussian Processes; 2.1. Defining Gaussian processes; 2.2. Non-Gaussian processes; 2.3. Principal component analysis or Karhunen-Loève transformation; 2.4. Sparse Gaussian processes; 2.5. Levy process; 2.6. Links with quantum communications; 3 Sparse Signals and Compressed Sensing; 3.1. Sparse Signals3.2. Compressed sensing; 3.3. Compressed sensing and quantum signal; 4 The Fourier Transform; 4.1. The Classic Fourier Transform; 4.2. The Discreet Fourier Transform and the Fast Fourier Transform; 4.3. The Fourier Transform and hyper-functions; 4.4. Hilbert Transform; 4.5. Clifford algebra and the Fourier Transform; 4.6. Spinors and quantum signals; 5 The Contribution of Arithmetic to Signal Processing; 5.1. Gauss sums; 5.2. Applications for Gauss sums; 6 Riemannian Geometry and Signal Processing; 6.1. Context; 6.2. Riemannian varieties; 6.3. Voronoi cells; 6.4. Applications to Voronoi cellsPART 2: Applications; 7 MIMO Systems; 7.1. Introduction; 7.2. A brief history of OFDM; 7.3. Multi-; carrier technology; 7.4. OFDM technique; 7.5. Generating OFDM symbols; 7.6. Inter-symbol and inter-carrier interference; 7.7. Cyclic prefix; 7.8. Mathematical model of the OFDM system; 7.9. MIMO channels; 7.10. The MIMO channel model; 7.11. MIMO OFDM channel model; 8 Minimizing Interferences in DS-CDMA Systems; 8.1. Convolutional encoding; 8.2. Structure of convolutive codes; 8.3. Polynomial representation; 8.4. Graphic representations of convolutive codes; 8.5. Decoding algorithms8.6. Discreet Wavelet Transform (DWT); 8.7. Construction and discreet filtering; 8.8. Defining the wavelet function: the place of detail; 8.9. Wavelets and filter banks; 8.10. Thresholding coefficients; 8.11. Simulating results; 9 STAP Radar; 9.1. Introduction; 9.2. Space-time adaptive processing (STAP); 9.3. Structure of the covariance matrix; 9.4. Clutter; 9.5. Optimal STAP; 9.6. Performance measures; 9.7. Influence of the radar's parameters on detection; 9.8. Sample matrix inversion algorithm (SMI); 9.9. Conclusion; 10 Tracking Radar (Using the Dempster-Shafer Theory)10.1. Introduction; 10.2. Dempster-Shafer theory; 10.3. Rules of combination; 10.4. Decision rules; 10.5. Digital simulation; 10.6. Conclusion; 11 InSAR Radar; 11.1. Introduction; 11.2. Coherence; 11.3. System model; 11.4. Inferometric phase statistics; 11.5. Quantitative examples; 11.6. Conclusion; 12 Telecommunications Networks; 12.1. Introduction; 12.2. Describing the ad hoc simulated network's topology; 12.3. The different scenarios enacted; 12.4. The statistics collected; 12.5. Discussion of results; 12.6. Part two: network using OLSR for routing