基于分数时延信道模型的低复杂度信道估计方法

由于多载波系统无线信道固有的稀疏特性,压缩感知技术(compressed sensing,CS)已被应用于正交频分复用(orthogonal frequency division multiplexing,OFDM)系统的信道估计中以提高频谱利用率.然而,传统的时域普通采样方法会导致信道恢复字典不够精细,无法精确反映传输信道路径特性.针对这一问题,提出采用多径稀疏分数时延信道模型来模拟OFDM系统的无线多径信道,利用在接收端进行时域过采样方法细化信道恢复字典以提高信道估计精度.同时,针对过采样引起的压缩感知测量矩阵的扩大而导致重构算法的复杂度增加的问题提出采用广义正交匹配追踪算法(generalized orthogonal matching pursuit,GOMP)以降低计算复杂度.仿真结果表明接收端时域过采样方法能准确检测到信道的分数时延且采用的GOMP算法能将传统的OMP算法的复杂度降低近80％,验证了所采用的信道估计方法的可靠性和有效性.

Low complexity channel estimation method based on fractional delay channel model

Due to the inherent sparse feature of the wireless channel in multi-carrier system,compressed sensing techniques are applied in the channel estimation of the OFDM system to improve spectrum utilization.However,the conventional timedomain sampling method causes the imprecision to the channel recovery dictionary,which can't accurately reflect the characteristics of the transmission channel path.To solve this problem,a multipath sparse fractional delay channel model is used to simulate the OFDM wireless multipath channel.In addition,a time-domain oversampling based generalized orthogonal matching pursuit (GOMP) algorithm at the receiver is exploited to improve the estimation accuracy and keep a relatively low computational complexity which is increased due to the time-domain oversampling.Simulation results demonstrate that the time-domain oversampling can effectively detect the fractional delay.In contrast to the conventional OMP algorithm,the GOMP algorithm reduces the computational complexity by 80％.Hence,it verifies the reliability and the validity of the proposed method in this paper.