摘要
在深海远程正交频分复用(OFDM)水声通信中,信道时延长、频率选择性衰落严重,传统的块独立压缩感知稀疏估计需要较高导频插入密度才能保证一定的估计性能,通信频谱利用率较低。提出了一种基于信道稀疏时变建模的块间迭代信道估计方法,利用深海信道在两个相邻OFDM数据块之间的时间相关性建立块间信道稀疏多途结构的时变关系,在此基础上,对传统稀疏信道估计算法中的候选字典矩阵的字典原子进行删减并改进优化方程,实现了对前一数据块所估信道信息的有效利用,显著降低了信道估计所需的导频插入密度。在深海不同接收深度、不同距离条件下开展了海试验证,实验结果表明,与传统稀疏信道估计方法相比,本方法在导频插入密度减半的条件下可达到优于传统方法的估计性能。
In long-range communication of deep sea,underwater acoustic channel is characterized by long delay spread and serious frequency selective fading.During estimation of Orthogonal Frequency Division Multiplexing(OFDM)system in this channel,traditional block-independent Compressed Sensing(CS) algorithm need a larger number of pilot symbols to ensure acceptable estimation performance,which would lead to low spectrum efficiency.An inter-block iterative channel estimation method based on sparse time-varying modeling was proposed to deal with this problem.The temporal correlation features of deep-sea channel are exploited to establish iterative channel estimation model between adjacent data blocks,and based on this model,a number of elements are cut from the candidate dictionary matrix of traditional sparse channel estimation algorithm and the optimization equation is modified.In this process,the previous estimated channel could offer useful prior information for the estimation of current block,which would significantly decrease the number of pilot symbols.To validate the effectiveness of this method,an underwater acoustic communication experiment was carried out at different receiving depths and distances of deep sea.The experimental results show that this proposed method could get better estimation performance than traditional sparse estimation method with only half the pilot inserted.
作者
王悦悦
王海斌
台玉朋
汪俊
胡承昊
王光旭
WANG Yueyue;WANG Haibin;TAI Yupeng;WANG Jun;HU Chenghao;WANG Guangxu(State Key Laboratory of Acoustics,Institute of Acoustics,Chinese Academy of Sciences,Beijing 100190;University of Chinese Academy of Sciences,Beijing 100049)
出处
《声学学报》
EI
CAS
CSCD
北大核心
2023年第1期16-26,共11页
Acta Acustica
基金
国家自然科学基金项目(62171440)资助。