OFDMA系统中的频谱感知方法研究

现在及将来的许多无线通信标准采用了OFDMA技术，对OFDMA系统进行频谱感知具有重要的理论和实际意义。本项目主要研究利用现代统计信号处理方法来提高OFDMA系统中的频谱感知性能。内容包括：首先，针对单用户情况，结合无线通信标准信号参数配置的特点，从OFDM信号的时域统计特性角度研究循环前缀特性，进而设计出具有高性能的频谱感知方法；然后，根据频谱感知方法的实现机理剖析系统误差的作用，提出稳健的频谱感知方法；接着，针对多用户OFDMA情况，利用贝叶斯理论研究动态频段划分方法；最后，利用频段划分得到的统计参数研究宽带频谱感知方法。

OFDMA technology has been adopted in many present and future wireless communication standards. Spectrum sensing for OFDMA systems is of great importance in improving the spectrum utilization from both theoretical and practical views. This project focuses on the spectrum sensing for OFDMA systems by exploiting modern statistical signal processing method.First of all, we consider the single user case. To study the statistical characteristics of the cyclic prefix from the view of the statistical characteristics of OFDM signal in time domain, together with the characteristics of parameter configuration in wireless communication standards, and then to design some spectrum sensing methods with high performance; To analysis the effection of system error according to the mechanism of spectrum sensing methods, then proposed robust spectrum sensing methods; Secondly, we consider the multi-user OFDMA case. Intend to achieve dynamic band partition useing the Bayesian theory, and then to study the broadband spectrum sensing method exploiting the statistic parameters which are given by dynamic band partition.