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为利用水声信道的稀疏特性,提高循环前缀单载波分块传输系统的信道估计精度和误比特率性能,提出一种新的基于压缩感知的稀疏信道估计方法.新方法利用任意具有单位能量的导频构造满足约束等距条件的频域测量矩阵,通过Dantzig selector算法重构稀疏水声信道冲激响应.基于实测湖试信道模型的仿真结果表明,在相同训练序列长度条件下,利用频域最小均方误差检测方法,新的压缩感知信道估计方法较传统最小二乘信道估计方法有近5 dB的性能增益.
In order to utilize the sparse characteristics of underwater acoustic channels and improve the channel estimation accuracy and bit error rate performance of cyclic prefix single-carrier block transmission system, a new sparse channel estimation method based on compressed sensing is proposed. The new method utilizes any unit energy The pilot constructs a frequency-domain measurement matrix that satisfies the constraint isometric condition and reconstructs the sparse acoustic channel impulse response using the Dantzig selector algorithm. Simulation results based on the measured channel model indicate that under the same training sequence length, Minimum mean square error detection method, the new compressed perceptual channel estimation method than the traditional least squares channel estimation method has a performance gain of nearly 5 dB.