Practical systems often suffer from hardware impairments that already appear during signal generation. Despite the limiting effect of such input-noise impairments on signal processing systems, they are routinely ignored in the literature. In this paper, we propose an algorithm for data detection and signal estimation, referred to as Approximate Message Passing with Input noise (AMPI), which takes into account input-noise impairments. To demonstrate the efficacy of AMPI, we investigate two applications: Data detection in massive multiple-input multiple-output (MIMO) wireless systems and sparse signal recovery in compressive sensing. For both applications, we provide precise conditions in the large-system limit for which AMPI achieves optimal performance. We furthermore use simulations to demonstrate that AMPI achieves near-optimal performance at low complexity in realistic, finite-dimensional systems.

中文翻译：

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具有输入噪声的系统中的最佳数据检测和信号估计


实际系统经常会受到信号生成过程中已经出现的硬件损伤的影响。尽管这种输入噪声损伤对信号处理系统的影响有限，但它们在文献中通常被忽略。在本文中，我们提出了一种数据检测和信号估计算法，称为输入噪声近似消息传递（AMPI），该算法考虑了输入噪声损伤。为了证明 AMPI 的功效，我们研究了两种应用：大规模多输入多输出 (MIMO) 无线系统中的数据检测和压缩感知中的稀疏信号恢复。对于这两种应用，我们在大型系统限制下提供了 AMPI 实现最佳性能的精确条件。我们还使用模拟来证明 AMPI 在现实的有限维系统中以低复杂性实现了接近最佳的性能。