认知无线电中基于欠采样的宽带频谱感知关键技术研究

发布时间：2018-12-11 18:36

【摘要】：无线通信技术的迅猛发展使其已经成为人们日常生活中必不可少的一部分。无线通信速率的快速增长是以更多频谱资源的消耗为基础的,而传统无线频谱管理基于固定分配,造成了人为的频谱资源危机,极大地限制了新型无线应用的发展。认知无线电技术允许非授权用户(Secondary User)感知授权用户(Primary User)的频谱使用情况,动态接入共享空闲频谱资源,能够有效地提高频谱利用率,解决频谱稀缺问题。频谱感知技术是认知无线电的基础,是实现动态频谱共享的第一步,具有重要的研究意义。未来无线通信的宽带化对宽带频谱感知技术提出了迫切的需求,而传统基于采样定理的宽带频谱感知对采样率的要求远超出现有ADC的采样能力,极大的限制了宽带频谱感知的发展。本文研究基于欠采样的宽带频谱感知技术,有效的降低宽带频谱感知对采样率的要求。本文首先对认知无线电中宽带频谱感知技术研究的背景、现状进行了详细的介绍,从奈奎斯特速率感知(Nyquist)和欠采样感知(Sub-Nyquist)两个方面详细讨论和分析了宽带频谱感知的相关研究工作。本文针对当前基于Nyquist采样率的宽带频谱感知算法对ADC采样率要求过高而基于Sub-Nyquist采样的压缩感知技术算法复杂,对设备同步要求高等问题,提出了基于欠采样的阵列化多速率宽带频谱感知方法SWSS。SWSS采用多个分支以不同的采样率对宽带信号进行采样,然后基于中国剩余定理对多个采样分支的欠采样信号进行解混叠,重构频谱,实现了宽带频谱的实时准确感知。MATLAB仿真表明,SWSS系统能够有效降低宽带频谱感知对ADC采样率的要求以及系统的复杂度,具有良好的扩展性。针对环境中电磁环境动态变化影响感知精度的问题,提出了基于采样率和检测分辨率调整的自适应欠采样宽带频谱感知方法ASWSS。基于宽带频谱感知的实际情况,分别针对检测信号信噪比变化和频谱占用率变化两种情况,提出了相应的自适应策略,促使系统能够自动根据当前环境状况调整系统的感知分支数、采样率、检测分辨率。MATLAB仿真实验表明ASWSS能够有效提高宽带频谱感知的准确性和稳定性。
[Abstract]:With the rapid development of wireless communication technology, it has become an essential part of people's daily life. The rapid growth of wireless communication rate is based on the consumption of more spectrum resources, while the traditional wireless spectrum management is based on fixed allocation, resulting in a man-made spectrum resource crisis, which greatly limits the development of new wireless applications. Cognitive radio technology allows unauthorized users (Secondary User) to perceive the spectrum usage of authorized (Primary User) and dynamically access and share free spectrum resources. It can effectively improve spectrum efficiency and solve the problem of spectrum scarcity. Spectrum sensing is the basis of cognitive radio and the first step to realize dynamic spectrum sharing. The broadband spectrum sensing technology of future wireless communication has put forward an urgent demand for wideband spectrum sensing technology, but the traditional wideband spectrum sensing based on sampling theorem requires the sampling rate far beyond the sampling ability of the existing ADC. It greatly limits the development of broadband spectrum sensing. In this paper, the under-sampling wideband spectrum sensing technology is studied to effectively reduce the sampling rate requirements of broadband spectrum sensing. In this paper, the background and status of broadband spectrum sensing technology in cognitive radio are introduced in detail. Based on Nyquist rate sensing (Nyquist) and under-sampling sensing (Sub-Nyquist), this paper discusses and analyzes the research work of wideband spectrum sensing in detail. In this paper, the current wideband spectrum sensing algorithm based on Nyquist sampling rate requires too much ADC sampling rate, while the compression sensing algorithm based on Sub-Nyquist sampling is complex and requires high equipment synchronization. In this paper, an array multi-rate wideband spectrum sensing method based on under-sampling is proposed. SWSS.SWSS uses multiple branches to sample wideband signals at different sampling rates. Then, based on the Chinese residue theorem, the under-sampled signals of multiple sampling branches are de-aliased, the spectrum is reconstructed, and the real-time accurate sensing of the wideband spectrum is realized. The MATLAB simulation shows that, SWSS system can effectively reduce the requirement of ADC sampling rate and the complexity of the system, and has good expansibility. Aiming at the problem that dynamic change of electromagnetic environment affects sensing accuracy, an adaptive under-sampling wideband spectrum sensing method ASWSS. based on sampling rate and detection resolution adjustment is proposed. Based on the actual situation of wideband spectrum sensing, a corresponding adaptive strategy is proposed to detect the signal to noise ratio change and spectrum occupancy rate change. MATLAB simulation results show that ASWSS can effectively improve the accuracy and stability of wideband spectrum sensing.
【学位授予单位】：国防科学技术大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN925

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