认知无线电中基于MIMO的传输与感知技术

发布时间：2019-04-02 13:50

【摘要】：随着无线通信技术的广泛应用,频谱资源越来越稀缺,匮乏的无线频谱资源已经严重影响无线通信技术的发展速度。认知无线电技术应运而生,在不影响授权用户正常使用的情况下,利用自身一定的学习能力,通过对频谱资源的感知,自适应地调整发射频率与功率,提高了频率使用效率,此技术成为将来无线通信领域的一个研究热点。目前认知无线电通过频谱检测与共享技术可以大幅提高频率资源时间维度上的使用效率,而从提升单位频率的信息量提高传输速率和降低误码改善传输质量方面做的研究较少。本文将现有的MIMO技术融入到认知无线电通信系统,并使用USRP软件无线电平台对MIMO通信功能进行设计与实现。在实现过程中,重点完成的第一个方案是基于空时编码的MIMO系统,采用Alamouti编码,主要工作是对编码、信道估计、同步以及译码数字信号处理模块的设计和编写;第二个方案是基于接收分集的MIMO系统,采用的是MRC(最大比值合并)合并方案,主要工作是基于RSSI(接收信号强度指示)求得近似SNR(信噪比),并求得各分路的合并权值。对这两种方案分别首先进行了Matlab理论仿真,然后使用C++对算法进行编码,使用GNURadio软件及USRP(通用软件无线电外设)进行实测验证,并对仿真及实验结果进行了分析。最后,对现有的无线通信获取位置信息算法进行分析,针对具有MIMO功能的认知无线电系统,利用其多天线的特性,提出了基于RSSI/TDOA(接收信号强度/到达时间差)获取认知无线电授权用户位置与功率信息的算法,以牺牲了较小精确度为代价简化了定位模型以及计算过程。鉴于通信噪声的存在,本文进一步提出了基于RSSI及TDOA数据的加权算法,从统计学的角度上对基于RSSI/TDOA获取的授权用户位置信息进行优化,减少了其均方根误差(RMSE)。基于这两个理论算法使用Matlab进行了仿真实验,并对结果进行了分析。
[Abstract]:With the wide application of the wireless communication technology, the spectrum resources are becoming more and more scarce, and the scarce wireless spectrum resources have seriously affected the development speed of the wireless communication technology. The cognitive radio technology comes into being, and under the condition of not affecting the normal use of the authorized user, the cognitive radio technology utilizes a certain learning ability, adjusts the transmission frequency and the power adaptively, adaptively adjusts the transmission frequency and the power, and improves the frequency utilization efficiency without affecting the normal use of the authorized user, This technology is a hot topic in the field of future wireless communication. At present, the use efficiency of the frequency resource time dimension can be greatly improved by the frequency spectrum detection and sharing technology of the cognitive radio, and the research on the improvement of the transmission rate and the reduction of the transmission quality of the error code can be reduced from the information amount of the frequency of the lifting unit. In this paper, the existing MIMO technology is integrated into the cognitive radio communication system, and the MIMO communication function is designed and implemented using the USRP software radio platform. in the implementation process, the first scheme which is focused on is based on a space-time-coded MIMO system, adopts Alamouti coding, and the main work is to design and write the coding, channel estimation, synchronization and decoding digital signal processing module; and the second scheme is a MIMO system based on receiving diversity, The MRC (maximum ratio combining) combining scheme is adopted, and the main work is to obtain the approximate SNR (signal-to-noise ratio) based on the RSSI (received signal strength indication) and to obtain the combined weight of each branch. The two schemes are simulated by Matlab, then the algorithm is coded using C ++, and the measured verification is carried out using the GNURadio software and the USRP (general software radio peripheral), and the simulation and experimental results are analyzed. and finally, analyzing the existing wireless communication acquisition position information algorithm, aiming at the cognitive radio system with the MIMO function, The algorithm of obtaining the location and power information of the cognitive radio based on the RSSI/ TDOA (received signal strength/ arrival time difference) is proposed, and the positioning model and the calculation process are simplified at the expense of the small precision. In view of the existence of communication noise, this paper further proposes a weighting algorithm based on the RSSI and TDOA data, and optimizes the location information of the authorized user based on the RSSI/ TDOA obtained from the statistics, and reduces the root mean square error (RMSE). Based on these two theoretical algorithms, the simulation experiment is carried out using Matlab, and the result is analyzed.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN925

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