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Artificial Intelligence in Wireless Communications.
This cutting-edge resource offers practical overview of cognitive radio, a paradigm for wireless communications in which a network or a wireless node changes its transmission or reception parameters. The alteration of parameters is based on the active monitoring of several factors in the external an...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Norwood :
Artech House,
2009.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Artificial Intelligence in Wireless Communications; Contents; Acknowledgments; 1 Introduction to Cognitive Radio; 1.1 Brief Concept of Cognitive Radio; 1.2 Very Brief Cognitive Radio History; 1.3 Definition; 1.4 Contributions; 1.5 Contents; References; 2 The Cognitive Engine: Artificial Intelligence for Wireless Communications; 2.1 Cognitive Radio Design; 2.2 Cognitive Engine Design; 2.3 Component Descriptions; 2.3.1 Sensors; 2.3.2 Optimizer; 2.3.3 Decision Maker; 2.3.4 Policy Engine; 2.3.5 Radio Framework; 2.3.6 User Interface; 2.3.7 Cognitive Controller Configuration.
- 2.4 Artificial Intelligence in Wireless Communications2.5 Artificial Intelligence Techniques; 2.5.1 Neural Networks; 2.5.2 Hidden Markov Models (HMM); 2.5.3 Fuzzy Logic; 2.5.4 Evolutionary Algorithms; 2.5.5 Case-Based Reasoning; 2.6 Conclusions; References; 3 Overview and Basics of Software Defined Radios; 3.1 Background; 3.2 Benefits of Using SDR; 3.3 Problems Faced by SDR; 3.4 GNU Radio Design; 3.4.1 The Universal Software Radio Peripheral; 3.4.2 The USRP Version 2; 3.4.3 Flow Graphs; 3.4.4 Parallel Programming in GNU Radio; 3.4.5 Flow Graph for Simulation and Experimentation.
- 3.4.6 Available Knobs and Meters3.5 Conclusions; References; 4 Optimization of Radio Resources; 4.1 Objective Space; 4.1 Objective Space; 4.2 Multiobjective Optimization: Objective Functions; 4.2 Multiobjective Optimization: Objective Functions; 4.2.1 Bit Error Rate (BER); 4.2.1 Bit Error Rate (BER); 4.2.2 Bandwidth (Hz); 4.2.2 Bandwidth (Hz); 4.2.3 Spectral Efficiency (bits/Hz); 4.2.4 Interference; 4.2.5 Signal to Interference Plus Noise Ratio (SINR); 4.2.6 Throughput; 4.2.7 Power; 4.2.8 Computational Complexity; 4.3 Multiobjective Optimization: A Different Perspective.
- 4.4 Multiobjective Analysis4.4.1 Utility Functions; 4.4.2 Population-Based Analysis; 4.5 Conclusion; References; 5 Genetic Algorithms for Radio Optimization; 5.1 A Brief Review; 5.2 Simple Example: The Knapsack Problem; 5.3 Multiobjective GA; 5.4 Wireless System Genetic Algorithm; 5.4.1 Details of Chromosome Structure; 5.4.2 Objective Function Definition; 5.4.3 Optimal Individual Selection; 5.5 Conclusions; References; 6 Decision Making with Case-Based Learning; 6.1 Case-Based Decision Theory; 6.2 Cognitive Engine Architecture with CBDT; 6.2.1 Memory and Forgetfulness.
- 6.3 Cognitive Engine Case-Based Decision Theory Implementation6.4 Simple CBDT Example; 6.5 Cognitive Radio Example Problem; 6.6 Conclusion; References; 7 Cognitive Radio Networking and Rendezvous; 7.1 Waveform Distribution and Rendezvous; 7.2 Cognitive Radio Networks; 7.3 Distributed AI; 7.4 Conclusions; References; 8 Example Cognitive Engine; 8.1 Functional System Design; 8.2 Simple Simulations; 8.2.1 BER-only; 8.2.2 BER and Power (1); 8.2.3 BER and Power (2); 8.2.4 Throughput; 8.2.5 Waveform Efficiency; 8.3 Interference Environment; 8.3.1 Interference (1): Simple BER Tests.