Ordentlich Or, Tabak Gizem, Hanumolu Pavan Kumar, Singer Andrew C, Wornell Gregory W
Hebrew University of Jerusalem, Israel.
University of Illinois, Urbana-Champaign, USA.
IEEE J Sel Top Signal Process. 2018 Oct;12(5):825-840. doi: 10.1109/jstsp.2018.2863189. Epub 2018 Aug 6.
Systems that capture and process analog signals must first acquire them through an analog-to-digital converter. While subsequent digital processing can remove statistical correlations present in the acquired data, the dynamic range of the converter is typically scaled to match that of the input analog signal. The present paper develops an approach for analog-to-digital conversion that aims at minimizing the number of bits per sample at the output of the converter. This is attained by reducing the dynamic range of the analog signal by performing a modulo operation on its amplitude, and then quantizing the result. While the converter itself is universal and agnostic of the statistics of the signal, the decoder operation on the output of the quantizer can exploit the statistical structure in order to unwrap the modulo folding. The performance of this method is shown to approach information theoretical limits, as captured by the rate-distortion function, in various settings. An architecture for modulo analog-to-digital conversion via ring oscillators is suggested, and its merits are numerically demonstrated.
捕获和处理模拟信号的系统必须首先通过模数转换器来采集信号。虽然后续的数字处理可以消除采集数据中存在的统计相关性,但转换器的动态范围通常会进行缩放,以匹配输入模拟信号的动态范围。本文提出了一种模数转换方法,旨在最小化转换器输出端每个样本的位数。这是通过对模拟信号的幅度进行模运算来减小其动态范围,然后对结果进行量化来实现的。虽然转换器本身是通用的,且与信号的统计特性无关,但量化器输出端的解码器操作可以利用统计结构来解开模折叠。在各种设置下,该方法的性能被证明接近由率失真函数所描述的信息理论极限。文中还提出了一种通过环形振荡器实现模模数转换的架构,并通过数值方法证明了其优点。