This chapter is organised as follows: Section 16.2 will briefly summarise CR and its integral phases, while Section 16.3 will elaborate the traditional spectrum sensing techniques by introducing their key features and main limitations. The predictive spectrum sensing idea and the corresponding state-of-the-art will be presented in Section 16.4, and finally Section 16.6 will conclude the chapter.

Chapter Contents:

• 16.1 Introduction
• 16.2 A brief description of cognitive radio concept
• 16.2.1 Spectrum sensing
• 16.2.2 Spectrum decision
• 16.2.3 Spectrum sharing
• 16.2.4 Spectrum mobility
• 16.3 Traditional spectrum-sensing techniques
• 16.3.1 Narrowband spectrum sensing
• 16.3.1.1 Methodologies
• 16.3.1.2 Limitations
• 16.3.2 Wideband spectrum sensing
• 16.3.2.1 Methodologies
• 16.3.2.2 Limitations
• 16.4 Predictive spectrum-sensing approach
• 16.4.1 Employed machine-learning methodologies
• 16.4.1.1 Hidden Markov models
• 16.4.1.2 Artificial neural networks
• 16.4.1.3 Deep learning
• 16.4.2 State-of-the-art
• 16.5 QoS-aware dynamic spectrum access techniques
• 16.5.1 Performance evaluation
• 16.6 Conclusion
• References

Inspec keywords: radio spectrum management; cognitive radio; learning (artificial intelligence)

Other keywords: cognitive radio spectrum sensing; predictive spectrum sensing; machine-learning-based predictive technique; CR

Subjects: Knowledge engineering techniques; Radio links and equipment; Communications computing