A Single-Chain Backscatter Tag for Multi-Sensor Multiplexing

TL;DR

MATRIX enables a single backscatter tag to concurrently multiplex readings from multiple onboard sensors using a voltage-division, PWM-based encoding scheme and a single analog modulation chain. A binary-weighted geometric progression ensures a uniquely invertible, well-spaced composite voltage, while an ambient RF-derived sawtooth provides a low-power timing reference. The receiver employs a phase-difference-based instantaneous frequency tracker, two-stage PWM-cycle segmentation, and an HMM-based demultiplexer to robustly recover per-sensor readings despite hardware imperfections and multipath. The approach achieves 20 dB average SNR for five sensors at 30 kHz sampling, with successful demonstrations in plant sensing, wearable health monitoring, and acoustic AoA estimation, while consuming sub-100 μW in ASIC form. MATRIX offers a scalable, low-footprint solution for co-located multi-modal sensing in real-world deployments.

Abstract

Many real-world sensing tasks require co-located, multi-modal measurements at a single site, typically a bundle of two to five sensors, for example, in plant stress sensing and blood pressure estimation. RF-backscatter devices have emerged as a low-power solution for sensing, yet existing backscatter tags support a single sensor. Placing several single-sensor tags at one site increases attachment footprint and induces mutual coupling between nearby tag antennas, thereby limiting practical deployment. We present MATRIX, a single-chain multi-sensor backscatter tag that concurrently supports multiple onboard sensors and multiplexes them as a composite voltage, then backscatters it through one analog modulation chain. Rather than time-division polling, which introduces inter-sensor sampling offsets, or frequency-division, which requires independent per-sensor modulation chains, MATRIX introduces a voltage-division multiplexing architecture in which each sensor value is encoded as a PWM waveform, carrying the measurement in its duty cycle and reserving the amplitude for multiplexing. To support reliable demultiplexing, MATRIX selects the voltage-division weights in a binary-weighted geometric progression so that every active-sensor set maps to a uniquely invertible, well-spaced composite voltage. The composite voltage is then converted into backscatter frequency shifts through a single modulation chain. At the receiver, MATRIX formulates demultiplexing as a Hidden Markov Model to recover per-sensor readings while tolerating analog hardware imperfections and multipath. MATRIX's ASIC design consumes 25.56uW. Detailed evaluation shows that the prototype, multiplexing five sensors, achieves 20 dB average signal reconstruction SNR at a 30 kHz sampling frequency; we further validate MATRIX with case studies in plant sensing, health monitoring, and microphone-based direction finding.

Figures (23)

• Figure 1: The Matrix tag concurrently acquires and multiplexes multiple onboard sensors and backscatters them via a single modulation chain.
• Figure 2: System overview of Matrix.
• Figure 3: TDM introduces inter-sensor sampling offsets. FDM requires multiple independent modulation chains for each sensor. In contrast, Matrix proposes a voltage-devision multiplexing (VDM) to sum all sensor readings and backscatter through a single modulation chain.
• Figure 4: Matrix encodes readings from multiple sensors into PWM signals on a shared time base (PWM's amplitude reserved for multiplexing); parallel comparators compare each input to a shared sawtooth timing reference, synchronizing sampling across sensors.
• Figure 5: Circuit flow of Matrix's sawtooth-timing extraction from ambient signals: (a) ambient two-tone RF carrier; (b) envelope extraction yielding the timing frequency; (c) amplitude-invariant square wave via a ground-referenced comparator; (d) RC differentiator and diode generating narrow timing pulses; (e) sawtooth generation via a constant-current source; a tunable $R_{\text{set}}$ adapts to on-the-fly sampling-rate tuning.