基于DDST的信道估计与信号检测

Channel Estimation and Signal Detection Based on Data-Dependent Superimposed Training

为提高信道估计与信号检测的精度且不增加系统频谱开销的情况下,在基于数据相关叠加训练序列方案(Data-De⁃pendent Superimposed Training,DDST)中加入降噪处理。发送端将导频与发送数据采用DDST方式叠加;接收端对估计的信道状态信息(Channel State Information,CSI)进行降噪处理,随后进行信号检测。仿真结果表明,在DDST系统中加入降噪处理能有效改善信道估计精度,从而进一步提高信号检测性能。

To improve the accuracy of channel estimation and signal detection without increasing the spectrum overhead of the sys⁃tem,noise reduction is added to data-dependent superimposed training(DDST).The pilot frequency and the transmitting data are superimposed by DDST at the sender.At the receiver,the estimated channel state information(CSI)is denoised,and then the sig⁃nal is detected.The simulation results show that adding noise reduction to DDST system can effectively improve the channel esti⁃mation accuracy and further improve the signal detection performance.