【作者】 徐静；

【导师】 胡艳军；

【作者基本信息】 安徽大学 ， 通信与信息系统， 2011， 硕士

【摘要】 下一代无线通信系统要求以更高的数据传输速率,以应对更高的服务质量的要求。无线技术的进步也使得各种应用和服务得到广泛而快速的发展。为了应付不断增长的需求以及不断稀缺的无线频谱资源,要求无线电设备具有共享和重新使用频谱资源的功能。认知无线电就是这样一种技术,它具有智能感知频谱环境,并根据网络性能要求不断调整系统参数,从而达到提高系统频谱资源利用率的作用。因此,本文研究了基于认知无线电思想的主动式抗干扰接收机。该接收机可接收多种通信体制或者不同业务类型的信号,并且可以根据接收信号的不同业务类型主动地选择适合的抗干扰方法。本论文就接收机中的认知无线电频谱检测方法展开研究。本文首先介绍了主动式抗干扰接收机的系统模型及工作原理,其次,研究了系统中的认知无线电技术,尤其是对认知无线电系统中的频谱检测方法进行了系统的分析,目前频谱检测的方法主要包括单节点频谱检测和多节点频谱感知,单节点频谱检测包括主用户发射端检测、主用户接收端检测两种,多节点频谱检测即协作频谱检测。主用户发射端检测包括匹配滤波检测、能量检测及循环平稳特征检测等。主用户接收端检测包括本振泄漏功率检测和基于干扰温度的检测。它们具有各自不同的优缺点,匹配滤波器检测是最优的信号检测方法,但是它需要已知主用户的调制类型、脉冲整形以及帧格式等先验知识；能量检测不仅不需要主用户先验知识,而且它适用于任何信号、实施起来也最简单,但是它只能检测到信号的有无,不能检测出信号的类型；循环平稳特征检测方法的优点是检测准确性高,缺点是复杂度较高；本振泄露功率检测算法的检测范围比较小并且需要的检测时间比较长；基于干扰温度的频谱检测计算难度太大。根据现有频谱检测方法的缺陷,本文在研究信号噪声子空间理论的基础上,提出了基于子空间跟踪的频谱检测方法,该方法不仅能够检测到主用户信号,而且能将信号恢复出来。最后,在MATLAB仿真平台上,以几种不同的信号为例,对基于子空间跟踪的频谱检测方法进行了仿真,得出仿真结果,并对该方法的检测性能进行了分析。仿真结果表明,基于子空间跟踪的频谱检测方法是一种性能优良的频谱检测方法。更多还原

【Abstract】 The next generation wireless communications systems require transmission at higher data rates in order to meet the higher demand of quality services. Wireless technology makes a variety of applications and services extensive and developed rapidly, in order to cope with the growing demand and a growing scarcity of wireless spectrum, requiring the radio device has to share and re-use the spectrum resources. Cognitive radio is such a technology, it can intellisenses spectrum environment, and continuously adjusts the system parameters based on the requirements of the network performance, to improves the spectral efficiency of the communication systems. Therefore, this thesis was researched about the active anti-interference mobile receivers based on cognitive radio. The receivers can receive a variety of signals from different communication systems or different types of business,and select the appropriate multi-user detection method according to the different types of the received signals. The spectrum detections of cognitive radio in this thesis studied.This thesis introduced the system model of active anti-interference receivers and the working principles firstly, secondly, the basic principles and the key technology of cognitive radio was studied, especially the spectrum efficiency of the cognitive radio was researched systematicly. Nowdays, spectrum detection methods includes single node and multi-nodes spectrum detection, the single node spectrum detections include the transmitter spectrum sensing of main users,and the receivers spectrum sensing of main users, multi-nodes spectrum sensing is the cooperative spectrum detection. The transmitter spectrum sensing of main users includes matched filtering detection, energy detection and cyclostationary feature detection. Primary user receivers detections include the detection of the LO leakage power and the detection based on interference temperature. They have their different advantages and disadvantages, matched filter detection is the best method of signal detection, but it needs the known types of modulation, pulse shaping, and prior knowledge of the frame formats of main users; energy detection does not require the known information of primary users, and it is not only applied to any signal, but also the easiest measure, it can only detect whether the signal,but can not detect the type of signals, cyclostationary feature detection method has the advantage of high detection accuracy, but the complexity is high; the detection range for the LO leakage power detection algorithm is relatively small and requires relatively long testing time; spectrum detection algorithm based on interference temperature dependes on power spectrum estimation, the computational complexity is too high. Under the existing method of spectrum detection of defects and shortcomings, we studied the signal noise subspace theory, the spectrum detection based on subspace tracking method can not only detect the primary user signals and the signals can be restored. Finally, on MATLAB simulation platform, several different signals are used in subspace tracking-based detection method of spectrum simulation, the simulation results are obtained and the detection performance is analyzed. The simulation results show that the spectrum detection based on subspace tracking is an excellent spectrum detection method.更多还原