Three-Event Energy Detection with Adaptive Threshold for Spectrum Sensing in Cognitive Radio Systems

Area of Science:

• Wireless Communications
• Signal Processing
• Cognitive Radio

Background:

• Dynamic spectrum access (DSA) in cognitive radio (CR) systems necessitates spectrum sensing for secondary users (SU) to detect licensed primary users (PU).
• Energy detection (ED) is a common spectrum sensing technique in CR systems.
• Minimizing decision error probability (DEP) is crucial for effective spectrum sensing.

Discussion:

• A novel adaptive sensing threshold is proposed for the three-event energy detection (3EED) algorithm.
• Newton's method with forced convergence is used to approximate the optimal decision threshold, minimizing DEP.
• The 3EED algorithm is analyzed and validated through simulations, comparing its performance against conventional ED (CED).

Key Insights:

• The proposed 3EED algorithm with an adaptive threshold offers improved spectrum sensing performance compared to CED.
• Accurate approximation of the optimal decision threshold is achieved efficiently using Newton's method.
• Simulation results demonstrate close agreement with theoretical predictions, validating the algorithm's effectiveness.

Outlook:

• Potential for enhanced spectral efficiency in CR networks through improved spectrum sensing.
• Further research could explore real-time implementation and adaptation to complex electromagnetic environments.
• The adaptive thresholding technique may be applicable to other signal detection problems.