论文部分内容阅读
多输入多输出技术通过采用多个阵元进行多发多收空间复用信道可在极其有限的通信带宽下实现高速水声通信,但由于同时存在通道间干扰和多径干扰,水声MIMO信道估计变得困难。提出利用MIMO水声信道多径稀疏结构存在的相关性,在经典联合稀疏模型的基础上对MIMO观测矩阵进行重组,从而建立基于分布式压缩感知的单载波水声MIMO通信信道联合稀疏模型;同时,针对信道响应中具有相同多径位置的稀疏部分和特有稀疏部分设计区分性正交匹配追踪算法进行联合重构,进一步抑制通道间干扰的影响。最后通过仿真和海上实验进行本方法有效性的验证,实现16 kbps的MIMO水声通信。通过算法推导、仿真和实验可得到结论:利用MIMO水声信道多径相关性进行分布式压缩感知估计可提高估计性能。
Multiple-Input Multiple-Output (MIMO) Multiplexed Multiplexed Multiplexed Channels Using Multiple Arrays Enables high-speed underwater acoustic communication at extremely limited communication bandwidths. However, due to the simultaneous presence of inter-channel interference and multipath interference, the underwater acoustic MIMO channel estimation It becomes difficult. This paper proposes the use of MIMO underwater acoustic channel multipath sparse structure of the existing correlation, based on the classical joint sparse model of the MIMO observation matrix is reorganized, so as to establish a single-carrier underwater acoustic MIMO communication channel joint sparse model based on distributed compression sensing; at the same time , The joint reconfiguration of discriminant Orthogonal Matching Pursuit algorithm with sparse parts with the same multi-path position in the channel response and the special sparse part is designed to further suppress the influence of inter-channel interference. Finally, the validity of this method is verified through simulation and offshore experiments to realize 16 kbps MIMO underwater acoustic communication. Through algorithm deduction, simulation and experiment, it can be concluded that using distributed compression perceptual estimation of multipath correlation of MIMO underwater acoustic channel can improve the estimation performance.