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An blind equalization algorithm for underwater acoustic communication systems

机译:水下声通信系统的盲均衡算法

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The author builds a channel model on condition that underwater acoustic channel is given. Based on the model, the underwater acoustic MIMO system model is built. Due to the limitation of subspace method applying in real time, the author use subspace track technology to change the subspace method into an adaptive algorithm — the subspace track blind equalization algorithm, and use PM(power method) to accelerate the computing speed of parameter estimation. There are 3 steps of subspace track blind equalization algorithm to implement signal equalization: 1) using subspace track to adaptively estimate subspace; 2) using PM to adaptively estimate channel parameters; 3) direct equalization. As is shown from the analysis of the simulation results, the equalization effects of this algorithm are better, its computation is smaller and convergence rate is faster. This algorithm would be well applied in the communication area.
机译:作者在给出水下声波通道的条件下建立了通道模型。基于该模型,建立了水下声学MIMO系统模型。由于子空间法实时应用的局限性,作者利用子空间跟踪技术将子空间方法转变为一种自适应算法-子空间轨道盲均衡算法,并采用PM(幂方法)来加快参数估计的计算速度。 。子空间磁道盲均衡算法分为3个步骤来实现信号均衡:1)利用子空间磁道自适应地估计子空间。 2)使用PM自适应地估计信道参数; 3)直接均衡。仿真结果分析表明,该算法的均衡效果更好,计算量较小,收敛速度更快。该算法将很好地应用于通信领域。

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