针对将线性最小均方误差(linear minimum mean square error, LMMSE)算法直接应用于通用滤波多载波(universal filter multi-carrier,UFMC)系统中需要先验信道相关矩阵信息的不足,提出基于LMMSE的改进算法.该算法在频域对使用最小二乘(least square, LS)算法获得的信道频率响应进行平滑处理,在时域通过优化采样点的截短以确定理想的信道采样长度,并采用迭代估计方法获得最优信道相关矩阵,从而避免先验信道相关矩阵信息.经MATLAB仿真验证,改进后的算法对噪声的干扰可以有效抑制,对比传统LMMSE算法误码性能提升约2 dB,可以有效改善信道估计的准确度.
Aiming at the deficiency that the prior channel correlation matrix information is required when the linear minimum mean square error(LMMSE)algorithm is directly applied to the universal filtered multi-carrier(UFMC)system, an improved algorithm based on LMMSE is proposed in this thesis. The algorithm smooths the channel frequency response obtained by the least square(LS)algorithm in the frequency domain, determines the ideal channel sampling length by optimizing the truncation of sampling points in the time domain, the optimal channel correlation matrix is obtained by iterative estimation method to avoid prior channel correlation matrix information. The MATLAB simulation verifies that the improved algorithm can effectively suppress the interference of noise. Compared with the traditional LMMSE algorithm, the bit error performance can be improved by about 2 dB, which can effectively improve the accuracy of channel estimation.
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