基于认知用户信任度的协作频谱检测方法的研究

发布时间：2018-06-02 06:22

本文选题：认知无线电 + 频谱检测　；参考：《江苏大学》2017年硕士论文

【摘要】：随着通信技术的飞速发展,无线通信相关业务占用了大量的频谱资源,然而传统的无线网络所使用的频谱分配原则是固定、不改变的,所导致的直接结果就是无线通信的相关业务量已经不能够满足人们与日增长的需求。认知无线电(Cognitive Radio,CR)技术可以通过对周围环境进行主动学习,来判断出频谱的使用情况,并利用机会接入的方式来对空闲的授权频段进行使用,从而使频谱的利用率得到提高。频谱检测是实现CR技术中的一个核心环节,本文重点对多个用户协作式频谱检测进行详细研究。首先,研究了CR技术的发展背景及其意义、国内外研究现状;对一些具有代表意义的单个用户的频谱检测法对比分析,其详细的研究内容包括:主用户发射机端检测与接收机端检测;为了避免本地频谱检测法的局限性,进一步系统地研究了协作式频谱检测法与其有关的数据融合准则。其次,针对CR系统中传统双门限检测算法不足与信道不理想所导致的检测效果不理想的情况。第三章提出了一种基于认知用户信任度的协作式频谱检测法,进一步改善了系统地检测性能。此方法基于传统双门限检测算法和认知用户信任度不同,在传输过程中对信任用户采用纠错编码技术,来提高系统的检测性能,传送2比特和3比特编码到融合中心(Fusion Center,FC),之后再分别应用不同融合准则融合,最后在FC进行“或”准则融合。经仿真结果得出,本章提出的方法可以有效的提升频谱检测性能及可靠性。最后,针对CR系统中控制信道上过多的通讯需求不仅耗损大量的带宽成本而且判断结果不可靠的问题,第四章提出一种基于改进的信任度分簇式协作频谱检测方案。此方法将自适应双门限检测方法与分簇式协作检测方法联合起来,对次信任区域进行均分划分,对信任区域与次信任区域用户分别编码发送至簇头,簇头将次信任区域编码转化为判决结果,与信任用户判决结果使用“或”准则融合得到簇内判决结果,并发送至FC,从而得到最终判决。经仿真结果得出,本章所提出的方案,不仅可以有效地提升检测概率,并且可以降低控制信道上的通信请求,进而减少系统资源的消耗。
[Abstract]:With the rapid development of communication technology, wireless communication related services occupy a large number of spectrum resources. However, the spectrum allocation principles used in traditional wireless networks are fixed and unchanged. The direct result is that the related traffic of wireless communication can no longer meet the increasing demand. Cognitive Radio Cognitive Radio (CR) technology can be used to determine the use of the spectrum through active learning of the surrounding environment, and to use the free authorized frequency band by the way of opportunity access, so that the utilization rate of the spectrum can be improved. Spectrum detection is a key link in CR technology. This paper focuses on cooperative spectrum detection of multiple users. First of all, the background and significance of CR technology are studied, and the research status at home and abroad is discussed. In order to avoid the limitation of the local spectrum detection method, the cooperative spectrum detection method and its related data fusion criteria are studied systematically. Secondly, aiming at the situation that the traditional two-threshold detection algorithm is insufficient and the channel is not ideal in CR system, the detection effect is not ideal. In chapter 3, a cooperative spectrum detection method based on cognitive user trust is proposed, which further improves the detection performance. This method is based on the difference of traditional two-threshold detection algorithm and cognitive user trust. In order to improve the detection performance of the system, error correcting coding technology is used to improve the performance of the system. The two bits and three bits are transmitted to the fusion center, and the fusion criteria are fused respectively. Finally, the "or" criterion fusion is carried out in FC. The simulation results show that the proposed method can effectively improve the performance and reliability of spectrum detection. Finally, aiming at the problem that too much communication demand in CR control channel not only consumes a lot of bandwidth cost but also results are unreliable, chapter 4 proposes a cooperative spectrum detection scheme based on improved trust clustering. In this method, the adaptive two-threshold detection method is combined with the cluster-based cooperative detection method, and the sub-trust region is divided equally, and the users of the trust region and the sub-trust region are coded to the cluster head, respectively. The cluster head converts the sub-trust region coding into the decision result, and fuses the "or" criterion with the trust user decision result to obtain the intra-cluster decision result, and sends it to the FC to obtain the final decision. The simulation results show that the proposed scheme can not only effectively improve the detection probability, but also reduce the communication request on the control channel, thus reducing the consumption of system resources.
【学位授予单位】：江苏大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN925

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