Multiple-input–multiple-output (MIMO) system offers a promising way for high data rate communication over bandwidth-limited underwater acoustic channels. However, MIMO communication not only suffers from intersymbol interference, but also introduces the additional co-channel interference, which brings challenge for underwater acoustic MIMO channel estimation and for channel equalization. In this article, we propose novel interference cancellation (IC) methods for handling this co-channel interference problem in the design of both channel estimation and channel equalization. Our method for channel estimation utilizes the spatial joint sparsity and the temporal joint sparsity in the multipath structure to estimate sparse channels with common delays under distributed compressed sensing framework. In this way, we enhance channel estimates with common delays, thus, suppress co-channel interference. Meanwhile, to address the case of multipath arrivals with different delays, which are estimated as noise under simultaneous orthogonal matching pursuit (SOMP) algorithm, we introduce forward–reverse strategy to SOMP algorithm, which is referred to as the FRSOMP algorithm. Our proposed FRSOMP algorithm performs the SOMP algorithm to achieve the initial channel estimates, performs the forward-add process, which attempts to add promising candidates into support sets, and performs the reverse-fetch process to check if the candidates in the support set are retained or removed. The purpose of channel estimation is to directly calculate the filter coefficients for channel-estimation-based decision feedback equalization (CE-DFE). In this article, we also propose a novel CE-DFE receiver with IC component. We design IC filters based on the traditional CE-DFE, and we derive the coefficients of the feedforward filters, feedback filters, and IC filters based on the channel estimate metric obtained by the FRSOMP algorithm, so the co-channel interference will be suppressed both in channel estimation and channel equalization. We demonstrate the performance of our approach by numerical simulation, lake experiment, and sea experiment. Results are provided to demonstrate the effectiveness of the proposed methods, which show that the proposed methods obtain higher output signal-to-noise ratio, lower bit error rate, and more separated constellations compared with the traditional compressed sensing channel estimation method and the traditional CE-DFE method.

中文翻译：

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利用时空联合稀疏性进行水下声学多输入多输出通信

多输入多输出 (MIMO) 系统为通过带宽受限的水声信道进行高数据速率通信提供了一种有前途的方式。然而，MIMO通信不仅受到码间干扰，而且还引入了额外的同信道干扰，这给水声MIMO信道估计和信道均衡带来了挑战。在本文中，我们提出了新的干扰消除 (IC) 方法，用于在信道估计和信道均衡设计中处理这种同信道干扰问题。我们的信道估计方法利用多径结构中的空间联合稀疏性和时间联合稀疏性来估计分布式压缩感知框架下具有公共延迟的稀疏信道。这样，我们增强了具有共同延迟的信道估计，从​​而抑制了同信道干扰。同时，针对同时正交匹配追踪（SOMP）算法下多径到达不同延迟被估计为噪声的情况，我们在SOMP算法中引入了前向-反向策略，称为FRSOMP算法。我们提出的 FRSOMP 算法执行 SOMP 算法以实现初始信道估计，执行前向添加过程，尝试将有希望的候选者添加到支持集中，并执行反向获取过程以检查支持集中的候选者是否被保留或删除。信道估计的目的是直接计算基于信道估计的决策反馈均衡（CE-DFE）的滤波器系数。在本文中，我们还提出了一种带有 IC 组件的新型 CE-DFE 接收器。我们在传统CE-DFE的基础上设计IC滤波器，并根据FRSOMP算法得到的信道估计量度推导出前馈滤波器、反馈滤波器和IC滤波器的系数，从而抑制了同信道干扰。信道估计和信道均衡。我们通过数值模拟、湖泊实验和海洋实验证明了我们方法的性能。结果证明了所提出方法的有效性，表明与传统压缩感知信道估计方法和传统CE相比，所提出方法获得更高的输出信噪比、更低的误码率和更多的分离星座。 -DFE 方法。我们在传统CE-DFE的基础上设计IC滤波器，并根据FRSOMP算法得到的信道估计量度推导出前馈滤波器、反馈滤波器和IC滤波器的系数，从而抑制了同信道干扰。信道估计和信道均衡。我们通过数值模拟、湖泊实验和海洋实验证明了我们方法的性能。结果证明了所提出方法的有效性，表明与传统压缩感知信道估计方法和传统CE相比，所提出方法获得更高的输出信噪比、更低的误码率和更多的分离星座。 -DFE 方法。我们在传统CE-DFE的基础上设计IC滤波器，并根据FRSOMP算法得到的信道估计量度推导出前馈滤波器、反馈滤波器和IC滤波器的系数，从而抑制了同信道干扰。信道估计和信道均衡。我们通过数值模拟、湖泊实验和海洋实验证明了我们方法的性能。结果证明了所提出方法的有效性，表明与传统压缩感知信道估计方法和传统CE相比，所提出方法获得更高的输出信噪比、更低的误码率和更多的分离星座。 -DFE 方法。基于FRSOMP算法得到的信道估计量度的反馈滤波器和IC滤波器，因此在信道估计和信道均衡中都会抑制同信道干扰。我们通过数值模拟、湖泊实验和海洋实验证明了我们方法的性能。结果证明了所提出方法的有效性，表明与传统压缩感知信道估计方法和传统CE相比，所提出方法获得更高的输出信噪比、更低的误码率和更多的分离星座。 -DFE 方法。基于FRSOMP算法得到的信道估计量度的反馈滤波器和IC滤波器，因此在信道估计和信道均衡中都会抑制同信道干扰。我们通过数值模拟、湖泊实验和海洋实验证明了我们方法的性能。结果证明了所提出方法的有效性，表明与传统压缩感知信道估计方法和传统CE相比，所提出方法获得更高的输出信噪比、更低的误码率和更多的分离星座。 -DFE 方法。我们通过数值模拟、湖泊实验和海洋实验证明了我们方法的性能。结果证明了所提出方法的有效性，表明与传统压缩感知信道估计方法和传统CE相比，所提出方法获得更高的输出信噪比、更低的误码率和更多的分离星座。 -DFE 方法。我们通过数值模拟、湖泊实验和海洋实验证明了我们方法的性能。结果证明了所提出方法的有效性，表明与传统压缩感知信道估计方法和传统CE相比，所提出方法获得更高的输出信噪比、更低的误码率和更多的分离星座。 -DFE 方法。