Abstract
Reasonable and effective allocation of cognitive radio spectrum resource according to user’s requirements is the key task of cognitive radio network. Cognitive radio spectrum allocation problem can be viewed as an optimization problem. This paper analyzes the application of bio-inspired intelligent algorithm in cognitive radio network spectrum allocation, and based on graph theory model of spectrum allocation, proposesaspectrum allocation algorithm based on autonomously evolutionary scheme. Three objective functions: Max-Min-Reward, Max-Sum- Reward and Max-Proportional-Fair are employed to evaluate the proposed algorithm capacity. The simulation result reveals that the proposed method can make the system user to obtain better network benefits and better embody the fairness between cognitive users. In the process of allocation, the proposed method was not restricted by user scale and the number of spectrums.
Priority-based reserved spectrum allocation by multi-agent through reinforcement learning in cognitive radio network
