An ultra-low-power sensor interface built around a reconfigurable incremental sigma-delta modulator for sensor networks employing electromagnetic backscatter

Abstract

An ultra-low-power four-channel sensor interface for wireless sensor networks employing semi-active RFID transponders as sensor nodes is described in the present paper. Each channel is based on a self-contained switched-capacitor second-order single-bit Sigma Delta-modulator operated in an incremental manner. The power consumption can be regulated through variation of the sampling frequency (max. 1MHz), signal bandwidth (8Hz-16kHz), output resolution (max. 16 bits) and/or output word rate. The input and output stages of the employed amplifiers are both class AB for a high energy efficiency. Moreover, the bias current of every amplifier can be programmed according to the actual power availability, thus dynamically exchanging DC-gain, gain-bandwidth-product and slew-rate against power consumption. In addition, two channels may be cascaded (2-2 MASH configuration), further incrementing the resolution and/or reducing the number of clock cycles to obtain a given resolution. The MASH configuration uses an on-line adaptive noise cancellation scheme to further enhance the noise-shaping characteristic of the converter. The power consumption per channel ranges from 4 to 20 mu W at a supply voltage of 1.4

A Background Calibration Technique Based on Limit Cycles for Reconfigurable Sigma Delta Modulators

“…SDMs are capable of achieving very low power consumption levels while providing an inherent tradeoff between power, speed and accuracy [5]. While changing the sampling frequency is the most common way of reconfiguring the SDM [6]- [9]; flexible order loop-filters [10], [11], multibit quantizers and multi-stage [12]- [14] structures are also being used to achieve the most optimum power-accuracy trade-off and to extend/adapt the operation region of the SDM. Continuous-time Sigma Delta Modulators (CT-SDMs) also exhibit inherent anti-aliasing filtering, noise shaping of sampling non-linearity [5].…”