Spectrum Allocation in Cognitive Radio
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Using game theory, we conduct an in-depth analysis of power control problems in cognitive radio systems. This problem requires consideration of multiple factors including transmission distance, environmental conditions, and device performance characteristics. To address this challenge, we developed an iterative algorithm that achieves Nash equilibrium through progressive refinement. The implementation employs key functions for utility calculation and best-response updates, where each node iteratively adjusts its power level based on other users' strategies. Our solution incorporates graphical visualization to clearly demonstrate the convergence process and equilibrium results, using plot functions to display power levels and utility changes over iterations. This algorithm provides deeper insights into cognitive radio power control dynamics, establishing a solid foundation for future research in distributed spectrum management systems.
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