基于改进帧结构设计的无人机集群信道均衡

UAV Cluster Channel Equalization Based on Improved Frame Structure Design

针对无人机集群链路单载波频域均衡(Single Carrier Frequency Domain Equalization,SC-FDE)系统信号同步与信道估计模块相互独立、系统开销大、信道估计精度不高的问题,提出了一种基于Schmidl&Cox的改进数据帧结构设计,使用同一训练序列实现信号同步和信道估计,降低了系统开销;利用快速傅里叶变换的周期性及线性性质,将多次复杂频域信道估计转换为时域降噪处理,得到更精确的信道频域响应估计。通过引入NH(Neumann-Hoffman)序列,解决了Schmidl&Cox定时方法存在峰值平台的问题,定时测度函数尖锐,方差性能较好。利用Matlab软件对设计算法进行了仿真验证,结果表明,在不增加系统开销的情况下,所提算法在相同信噪比下比传统均衡算法误码率更低,在误码率为1×10^(-5)时有2~3 dB的性能增益,系统开销由0.28降为0.2,实现复杂度低。

In order to solve the problems of unmanned aerial vehicle(UAV)cluster link single carrier frequency domain equalization(SC-FDE)system such as signal synchronization and channel estimation modules being independent of each other,high system overhead,and poor channel estimation accuracy,an improved data frame structure design based on Schmidl&Cox is presented.This design is performed by using the same training sequence to achieve signal synchronization and channel estimation.By using this process,system overhead is reduced.Moreover,the periodicity and linearity of fast Fourier transform(FFT)are utilized to convert multiple frequency domain channel estimation into time domain noise reduction process,and then a more accurate channel frequency domain response estimation result is obtained.On the other hand,by introducing the Neumann-Hoffman(NH)sequence,the problem of the peak plateau in the Schmidl&Cox timing method is solved,and then a shape timing measurement function and better variance performance is obtained.The design algorithm is simulated and verified by Matlab.The results show that without increasing system overhead,the improved data frame structure has a lower bit error rate(BER)than the traditional equalization algorithm.When the BER is 1×10^(-5),the gain is 2~3 dB,the accuracy of fixed frequency is 1×10^(-3),and the synchronization error is small.Moreover,this method is easy to be realized.