基于四维广义离散椭球序列的降秩MIMO-OFDM信道估计方法

Reduced-Rank MIMO-OFDM Channel Estimation Based on Four-Dimensional Generalized Discrete Prolate Spheroidal Sequences

传统的基于插值的信道估计器需要高导频负载来对快速时变的频选MIMO-OFDM信道进行稳健估计。为降低对高导频的需求,利用信道对低维子空间的限制作用设计了一种线性最小均方误差(LMMSE)信道估计器,该估计器采用由带限广义离散椭球(GDPS)序列得到的四维基扩展信道模型。仿真结果表明:与基于插值的最小二乘(LS)估计器相比,降秩估计器的均方估计误差较小,且对时延、多普勒和角扩展等均具有较强的鲁棒性。

For the multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM)high-speed rail communication system,the traditional interpolation-based channel estimators require high pilot load to perform robust estimation for fast time-varying and frequency-selective MIMO-OFDM channels.Here,a linear minimum mean square error(LMMSE)estimator by using the channel restriction on low-dimensional subspace is proposed to reduce the demand for high pilot frequency.The estimator uses a four-dimensional basis extended channel model derived from a band-limited generalized discrete prolate spheroidal(GDPS)sequences.Simulation results show that,compared with the least squares(LS)estimator based on interpolation,the reduced-rank estimator proposed in this paper has a smaller mean square estimation error with strong robustness to delay,Doppler and angle spreads.