认知无线电
数学优化
计算机科学
稳健性(进化)
粒子群优化
信道分配方案
频道(广播)
算法
凸优化
资源配置
趋同(经济学)
无线
正多边形
数学
电信
计算机网络
生物化学
化学
几何学
经济
基因
经济增长
出处
期刊:Sensors
[MDPI AG]
日期:2022-09-08
卷期号:22 (18): 6796-6796
被引量:7
摘要
The use of a cognitive radio power allocation algorithm is an effective method to improve spectral utilization. However, there are three problems with traditional cognitive radio power allocation algorithms: (1) based on the ideal channel model analysis, channel fluctuation is not considered; (2) they do not consider fairness among cognitive users; and (3) some algorithms are complex and locating the optimal power allocation scheme is not an easy task. For the above problems, this study establishes a robust model which adds the cognitive user transmission rate variance constraint to solve the maximum channel capacity time power allocation scheme by considering the worst-case channel transmission model, and finally solves this complex non-convex optimization problem by using the hybrid particle swarm algorithm. Simulation results show that the algorithm has good robustness, improves the fairness among the cognitive users, makes full use of the channel resources under the constraints, and has a simple algorithm, fast convergence, and good optimization results.
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