摘要
认知无线电中,协作频谱检测已经被证明可以有效提高系统的检测性能。但是在噪声不确定的情况下,认知用户会更加倾向于减少检测消耗来提高自身的吞吐量。本文主要是把进化博弈论应用到噪声不确定下的协作频谱检测中,认知用户可以动态地选择是否参加协作频谱检测,通过不断的迭代学习,得到一个进化稳定策略(ESS)。本文把所有认知用户作为整体参与博弈,由进化博弈论算法,得到其参与协作的认知用户平均吞吐量,并将其与所有用户的平均吞吐量对比。如不等则反复迭代直至相等,从而得到最终的进化稳定策略。仿真结果表明:噪声不确定度越高,达到平衡时认知用户参与协作检测的概率就越高;进化博弈论算法让认知用户选择性地参与协作检测比让所有用户都参与协作检测有更高的系统吞吐量。
In cognitive radio,cooperative spectrum detection has been shown to improve the detection performance of the system. But in the case of noise uncertainty,the cognitive user will be more inclined to reduce the detection of consumption to improve their throughput. In this paper,evolutionary game theory is applied to cooperative spectrum detection under noise uncertainty. Cognitive users can dynamically select whether to participate in cooperative spectrum detection. The system will achieve an evolutionary stabilization strategy（ESS） through continuous iterative learning. In this paper,all cognitive users participate in the game as a whole,and the evolutionary game theory algorithm is used to get the average throughput of the cognitive users participating in the collaboration and compare it with the average throughput of all users. Such as the same iteration until it is equal,so as to get the final evolutionary stability strategy. The simulation results show that the higher the noise uncertainty is,the higher the probability of cognition users participating in cooperative detection. Evolutionary game theory algorithm allows a user to selectively participate in the collaborative cognitive detect than to allow all users to collaborate on detection of a higher system throughput.
出处
《信号处理》
CSCD
北大核心
2017年第10期1385-1392,共8页
Journal of Signal Processing
基金
国家自然科学基金项目(61501253)
江苏省基础研究计划(自然科学基金)项目(BK20151506)
江苏省"六大人才高峰"第十一批高层次人才选拔培养资助项目(XXRJ-009)
江苏省重点研发计划(社会发展)项目(BE2016778)
南京邮电大学科研项目(NY217054)
关键词
协作频谱检测
噪声不确定
进化博弈论
吞吐量
collaborative spectrum detection
noise uncertainty
evolutionary game theory
throughput
