基于权值优化的认知WiMax信号协同识别

传统的正交频分复用(OFDM)系统识别算法只能识别出接收信号是否为基于全球微波互联接入技术(WiMax)的OFDM信号,但无法判断该信号是认知信号,并且在复杂电磁环境下识别正确率低.为此,提出了一种协同识别认知WiMax无线网络OFDM信号的算法.该算法首先利用OFDM信号的循环自相关特性估计信号的有用符号时间,并通过估计各协同感知节点的信噪比对时间参数的估计值进行加权,得到有用符号时间的协同估计值,进而判断接收信号是否为基于WiMax系统的OFDM信号;再通过自私攻击策略,实现对OFDM信号是否是认知WiMax信号的判别,为进一步研究认知WiMax网络节点定位技术奠定了基础.仿真结果表明,与非协同识别算法相比,提出的协同识别算法在多径和低信噪比条件下具有更高的识别率.

Cooperative recognition of cognitive WiMax signal based on weight optimization

Traditional Orthogonal Frequency Division Multiplexing ( OFDM ) system recognition algorithm can only recognize whether or not the received signal is OFDM signal based on Worldwide Interoperability for Microwave Access( WiMax) system,but it cannot judge the signal is a cognitive signal,and the recogni-tion rate of the algorithm is low in complex electromagnetic environment. For these problems, this paper proposes a cooperative recognition algorithm to recognize cognitive WiMax radio network OFDM signals. Firstly,the algorithm uses the cyclic autocorrelation characteristic of the OFDM signal to estimate the useful symbolic time of the signal. And the estimated values of the time parameters are weighted by estimating the signal-to-noise ratio( SNR) of the cooperative sensing nodes,then the cooperative estimation of the useful symbol time is obtained. Afterwards,it judges whether the received signal is OFDM signal based on WiMax system by the cooperative estimated value of the useful symbol time. Finally,the selfish attack strategy is used to discriminate whether the OFDM signal is a cognitive WiMax signal,which lays a foundation for fur-ther research on cognitive WiMax node localization technology. The simulation results show that the pro-posed cooperative algorithm has higher recognition rate under multipath and low SNR conditions than non-cooperative recognition algorithms.