论文标题
无限采样框架中量化信号的重建条件
Reconstruction Condition of Quantized Signals in Unlimited Sampling Framework
论文作者
论文摘要
无限采样框架（USF）领域的最新理论进步表明，有可能避免模拟转换器（ADC）的剪切问题。迄今为止，大多数相关作品都集中在实现的模量样本上，但是关于量化影响的报道很少。在本文中，我们研究了更实用的USF系统，其中模量样品被量化为有限数量的位。特别是，我们提出了针对采样率的下限的新要求，以确保从量化的模量样品中精确恢复原始信号。最小采样率由信号带宽和量化位共同确定。数值结果表明，在存在量化噪声的情况下，具有不同波形和带宽的信号以新的最小采样率完美恢复，而恢复在修改前以最小采样率失败，这也验证了理论的正确性。还为从业人员提供了抽样率，量化位和恢复算法的计算复杂性的权衡。
The latest theoretical advances in the field of unlimited sampling framework (USF) show the potential to avoid clipping problems of analog-to-digital converters (ADC). To date, most of the related works have focused on real-valued modulo samples, but little has been reported about the impact of quantization. In this paper, we study more practical USF system where modulo samples are quantized to a finite number of bits. In particular, we present a new requirement about the lower bound of sampling rate to ensure exact recovery of original signals from quantized modulo samples. The minimum sampling rate is jointly determined by signal bandwidth and quantization bits. Numerical results show that in the presence of quantization noise, signals with different waveforms and bandwidths are recovered perfectly at the new minimum sampling rate while the recovery fails at minimum sampling rate before modification, which also verifies the correctness of the theory. The trade-offs of sampling rates, quantization bits and computational complexity of recovery algorithm are also given for practitioners to weigh.
