Aimed at the abominable influences to blind equaliza-tion algorithms caused by complex time-space variability existing in underwater acoustic channels, a new self-adjusting decision feedback equalization （DFE） algor...Aimed at the abominable influences to blind equaliza-tion algorithms caused by complex time-space variability existing in underwater acoustic channels, a new self-adjusting decision feedback equalization （DFE） algorithm adapting to different under-water acoustic channel environments is proposed by changing its central tap position. Besides, this new algorithm behaves faster convergence speed based on the analysis of equalizers’ working rules, which is more suitable to implement communications in dif-ferent unknown channels. Corresponding results and conclusions are validated by simulations and spot experiments.展开更多
A deconvolution algorithm is proposed to account for the distortions of impulse shape introduced by propagation process. By finding the best correlation of the received waveform with the multiple templates, the number...A deconvolution algorithm is proposed to account for the distortions of impulse shape introduced by propagation process. By finding the best correlation of the received waveform with the multiple templates, the number of multipath components is reduced as the result of eliminating the ＂phantom paths＂, and the captured energy increases. Moreover, it needs only a single reference measurement in real measurement environment （do not need the anechoic chamber）, which by far simplifies the templates acquiring procedure.展开更多
The simplified joint channel estimation and symbol detection based on the EM (expectation-maximization) algorithm for space-time block code (STBC) are proposed. By assuming channel to be invariant within only one STBC...The simplified joint channel estimation and symbol detection based on the EM (expectation-maximization) algorithm for space-time block code (STBC) are proposed. By assuming channel to be invariant within only one STBC word and utilizing the orthogonal structure of STBC, the computational complexity and cost of this algorithm are both very low, so it is very suitable to implementation in real systems.展开更多
In this paper we study the geometrical structures of FIR filters and their application to multichannel blind deconvolution. First we introduce a Lie group structure and a Riemannian structure on the manifolds of the F...In this paper we study the geometrical structures of FIR filters and their application to multichannel blind deconvolution. First we introduce a Lie group structure and a Riemannian structure on the manifolds of the FIR filters. Then we derive the natural gradients on the manifolds using the isometry of the Riemannian metric. Using the natural gradient, we present a novel learning algorithm for blind deconvolution based on the minimization of mutual information. Some properties of the learning algorithm, such as equivariance and stability are also studied. Finally, the simulations are given to illustrate the effectiveness and validity of the proposed algorithm.展开更多
在室内可见光通信中符号间干扰和噪声会严重影响系统性能,K均值(K-means)均衡方法可以抑制光无线信道的影响,但其复杂度较高,且在聚类边界处易出现误判。提出了改进聚类中心点的K-means(Improved Center K-means,IC-Kmeans)算法,通过随...在室内可见光通信中符号间干扰和噪声会严重影响系统性能,K均值(K-means)均衡方法可以抑制光无线信道的影响,但其复杂度较高,且在聚类边界处易出现误判。提出了改进聚类中心点的K-means(Improved Center K-means,IC-Kmeans)算法,通过随机生成足够长的训练序列,然后将训练序列每一簇的均值作为K-means聚类中心,避免了传统K-means反复迭代寻找聚类中心。进一步,提出了基于神经网络的IC-Kmeans(Neural Network Based IC-Kmeans,NNIC-Kmeans)算法,使用反向传播神经网络将接收端二维数据映射至三维空间,以增加不同簇之间混合数据的距离,提高了分类准确性。蒙特卡罗误码率仿真表明,IC-Kmeans均衡和传统K-means算法的误码率性能相当,但可以显著降低复杂度,特别是在信噪比较小时。同时,在室内多径信道模型下,与IC-Kmeans和传统Kmeans均衡相比,NNIC-Kmeans均衡的光正交频分复用系统误码率性能最好。展开更多
基金supported by the National Natural Science Foundation of China(61101205)the Natural Science Foundation of Hubei Province of China(2009CDB337)the Natural Science Foundation of Naval University of Engineering(HGDQNJJ13019)
文摘Aimed at the abominable influences to blind equaliza-tion algorithms caused by complex time-space variability existing in underwater acoustic channels, a new self-adjusting decision feedback equalization （DFE） algorithm adapting to different under-water acoustic channel environments is proposed by changing its central tap position. Besides, this new algorithm behaves faster convergence speed based on the analysis of equalizers’ working rules, which is more suitable to implement communications in dif-ferent unknown channels. Corresponding results and conclusions are validated by simulations and spot experiments.
基金the Key Program of the National Natural Science Foundation of China (60432040)the China Postdoctors Science Foundation (20060390792).
文摘A deconvolution algorithm is proposed to account for the distortions of impulse shape introduced by propagation process. By finding the best correlation of the received waveform with the multiple templates, the number of multipath components is reduced as the result of eliminating the ＂phantom paths＂, and the captured energy increases. Moreover, it needs only a single reference measurement in real measurement environment （do not need the anechoic chamber）, which by far simplifies the templates acquiring procedure.
基金This project was supported by the National Natural Science Foundation of China (60272079).
文摘The simplified joint channel estimation and symbol detection based on the EM (expectation-maximization) algorithm for space-time block code (STBC) are proposed. By assuming channel to be invariant within only one STBC word and utilizing the orthogonal structure of STBC, the computational complexity and cost of this algorithm are both very low, so it is very suitable to implementation in real systems.
基金the National Natural Science Foundation of China.
文摘In this paper we study the geometrical structures of FIR filters and their application to multichannel blind deconvolution. First we introduce a Lie group structure and a Riemannian structure on the manifolds of the FIR filters. Then we derive the natural gradients on the manifolds using the isometry of the Riemannian metric. Using the natural gradient, we present a novel learning algorithm for blind deconvolution based on the minimization of mutual information. Some properties of the learning algorithm, such as equivariance and stability are also studied. Finally, the simulations are given to illustrate the effectiveness and validity of the proposed algorithm.
文摘在室内可见光通信中符号间干扰和噪声会严重影响系统性能,K均值(K-means)均衡方法可以抑制光无线信道的影响,但其复杂度较高,且在聚类边界处易出现误判。提出了改进聚类中心点的K-means(Improved Center K-means,IC-Kmeans)算法,通过随机生成足够长的训练序列,然后将训练序列每一簇的均值作为K-means聚类中心,避免了传统K-means反复迭代寻找聚类中心。进一步,提出了基于神经网络的IC-Kmeans(Neural Network Based IC-Kmeans,NNIC-Kmeans)算法,使用反向传播神经网络将接收端二维数据映射至三维空间,以增加不同簇之间混合数据的距离,提高了分类准确性。蒙特卡罗误码率仿真表明,IC-Kmeans均衡和传统K-means算法的误码率性能相当,但可以显著降低复杂度,特别是在信噪比较小时。同时,在室内多径信道模型下,与IC-Kmeans和传统Kmeans均衡相比,NNIC-Kmeans均衡的光正交频分复用系统误码率性能最好。
