认知无线电中基于联盟构成博弈论的频谱检测技术研究
发布时间：2019-06-18 11:29
【摘要】：随着无线通信服务的不断普及,人们对服务的需求量也在不断增长,频谱资源的短缺以及传统静态频谱接入技术的限制问题也因此变的更加突出。在这样一个频率资源异常珍贵的时代,如何满足额外的业务量需求,更加有效的使用原有频谱资源,同时引入新的频段,是现如今研究的热点。认知无线电是为解决频谱资源利用率低而发展的新兴技术。本文以提高认知用户的检测性能并且降低干扰为目标,分别优化了针对非合作式频谱检测的双门限能量检测优化算法和改进了针对合作式频谱检测的联盟构成博弈论算法。在单个认知用户提高检测性能方面,由于授权用户在认知用户感知阶段回归信道时认知用户容易发生误判而对授权用户造成干扰,因此本文优化了双门限能量检测算法。仿真结果表明,优化后的算法相对于未优化时的性能有显著提升。在信噪比值恒定时,优化算法分为10组的性能超过传统算法性能的15.4%,在虚警概率值恒定时,优化算法分10组的性能高出传统算法性能的6.5%。在多个认知用户共同提高检测性能方面,由于认知用户的感知时间不可忽略,并且会降低传输性能,所以本文研究了联合频谱感知与接入算法,并在该算法的基础上,改进了联盟构成博弈论算法。该算法允许认知用户根据用于找到空闲信道的平均时间和能获得的平均容量的总收益来决定是加入还是离开联盟。联盟内的成员通过互相合作,可以优化他们整体的检测和接入性能。通过对仿真结果分析,在认知用户数量N=20时,这个性能优势相对于非合作情况下达到56.25%,在授权信道数量K=20时,联盟构成博弈论算法的性能比非合作情况的性能高出63.5%。本文的研究可以为认知无线电频谱检测的进一步研究提供理论支持,同时也为认知无线电在5G方面的应用提供了相应参考。
[Abstract]:With the continuous popularization of wireless communication services, the demand for services is also growing, the shortage of spectrum resources and the limitations of traditional static spectrum access technology have become more prominent. In such an era of extremely precious frequency resources, how to meet the additional traffic requirements, more effective use of the original spectrum resources, and the introduction of new frequency bands, is now the focus of research. Cognitive radio is a new technology developed to solve the low efficiency of spectrum resources. In this paper, in order to improve the detection performance of cognitive users and reduce interference, the dual threshold energy detection optimization algorithm for non-cooperative spectrum detection and the alliance composition game theory algorithm for cooperative spectrum detection are optimized respectively. In order to improve the detection performance of a single cognitive user, the dual threshold energy detection algorithm is optimized because the authorized user is prone to misjudgment and interferes with the authorized user when the cognitive user returns to the channel in the cognitive user perception stage. The simulation results show that the performance of the optimized algorithm is significantly better than that of the unoptimized algorithm. When the signal-to-noise ratio (SNR) is constant, the performance of the optimization algorithm in 10 groups is 15.4% higher than that of the traditional algorithm, and when the false alarm probability is constant, the performance of the optimization algorithm in 10 groups is 6.5% higher than that of the traditional algorithm. In order to improve the detection performance of multiple cognitive users, because the perceptual time of cognitive users can not be ignored, and will reduce the transmission performance, this paper studies the joint spectrum sensing and access algorithm, and on the basis of this algorithm, improves the alliance composition game theory algorithm. The algorithm allows cognitive users to decide whether to join or leave the alliance according to the average time used to find the idle channel and the total benefit of the average capacity available. By working with each other, members of the alliance can optimize their overall detection and access performance. The simulation results show that the performance of the alliance game theory algorithm is 63.5% higher than that of the non-cooperative case when the number of cognitive users N 鈮，
本文编号：2501452
[Abstract]:With the continuous popularization of wireless communication services, the demand for services is also growing, the shortage of spectrum resources and the limitations of traditional static spectrum access technology have become more prominent. In such an era of extremely precious frequency resources, how to meet the additional traffic requirements, more effective use of the original spectrum resources, and the introduction of new frequency bands, is now the focus of research. Cognitive radio is a new technology developed to solve the low efficiency of spectrum resources. In this paper, in order to improve the detection performance of cognitive users and reduce interference, the dual threshold energy detection optimization algorithm for non-cooperative spectrum detection and the alliance composition game theory algorithm for cooperative spectrum detection are optimized respectively. In order to improve the detection performance of a single cognitive user, the dual threshold energy detection algorithm is optimized because the authorized user is prone to misjudgment and interferes with the authorized user when the cognitive user returns to the channel in the cognitive user perception stage. The simulation results show that the performance of the optimized algorithm is significantly better than that of the unoptimized algorithm. When the signal-to-noise ratio (SNR) is constant, the performance of the optimization algorithm in 10 groups is 15.4% higher than that of the traditional algorithm, and when the false alarm probability is constant, the performance of the optimization algorithm in 10 groups is 6.5% higher than that of the traditional algorithm. In order to improve the detection performance of multiple cognitive users, because the perceptual time of cognitive users can not be ignored, and will reduce the transmission performance, this paper studies the joint spectrum sensing and access algorithm, and on the basis of this algorithm, improves the alliance composition game theory algorithm. The algorithm allows cognitive users to decide whether to join or leave the alliance according to the average time used to find the idle channel and the total benefit of the average capacity available. By working with each other, members of the alliance can optimize their overall detection and access performance. The simulation results show that the performance of the alliance game theory algorithm is 63.5% higher than that of the non-cooperative case when the number of cognitive users N 鈮，
本文编号：2501452
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