Abstract: Tree cognitive radio subnets employ multi-cluster parallel operation mode．Its spectrum decision involves subnet capacity,subnet throughput and subnet stability,leading to high compute complexity．To solve the spectrum decision making problem,a triple-layer priority decision model was established and a corresponding heuristic decision algorithm was proposed．The proposed algorithm creates a search space without generating duplicated nodes via cluster structure and cluster growth degree,greedily searching for subnet structure with higher growth rate on the heuristic condition that is the search steps of updating the optimal solution．The solution space is rigorously pruned at double thresholds,i.e.,subnet capacity limit and the available spectrum and subnet transmission rate limit．Simulation results show that the proposed algorithm can obtain the optimal solution and meet real-time requirement under a specified subnet scale and spectrum space constraints.

Key words: Cognitive radio,Spectrum decision,Tree-based network,Multi-objective optimization,Backtracking algorithm