An Event-Driven Quasi-Level-Crossing Delta Modulator Based on Residue Quantization

Abstract

This article introduces a digitally intensive event-driven quasi-level-crossing (quasi-LC) delta-modulator analog-to-digital converter (ADC) with adaptive resolution (AR) for Internet of Things (IoT) wireless networks, in which minimizing the average sampling rate for sparse input signals can significantly reduce the power consumed in data transmission, processing, and storage. The proposed AR quasi-LC delta modulator quantizes the residue voltage signal with a 4-bit asynchronous successive-approximation-register (SAR) sub-ADC, which enables a straightforward implementation of LC and AR algorithms in the digital domain. The proposed modulator achieves data compression by means of a globally signal-dependent average sampling rate and achieves AR through a digital multi-level comparison window that overcomes the tradeoff between the dynamic range and the input bandwidth in the conventional LC ADCs. Engaging the AR algorithm reduces the average sampling rate by a factor of 3 at the edge of the modulator's signal bandwidth. The proposed modulator is fabricated in 28-nm CMOS and achieves a peak SNDR of 53 dB over a signal bandwidth of 1.42 MHz while consuming 205 mu text{W} and an active area of 0.0126 mm2.