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中文摘要：
针对认知无线网络中的引擎参数调整问题，提出了一种基于拟态物理学多目标优化的求解算法．根据认知参数编码的二进制特点，设计了基于海明距离的个体排序方法，并改进了微粒的更新方程，最后求出问题的Pareto最优解集．多载波环境下的仿真实验表明，算法可以根据无线信道环境的动态变化和认知用户需求的不同需求，自适应调整各个子载波的调制方式和发射功率，满足参数优化需求．
英文摘要：
To solve the engine parameter adjustment problem of cognitive radio networks,an artificial physics multi-objective optimization algorithm was proposed. According to its binary encoded features of cognitive parameters, Hamming distance based individual ranking method was designed and particle updated equation was improved, and finally the Pareto optimal set were achieved. Simulation results show that under the multi-cattier environment, the proposed algorithm can adjust transmission power and modulation mode according to the changing of channel and cognitive user demands. So it meets the demands for parameters optimization.
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