Patrick Mercier

A Sub-μW VCO-Based Direct Digitization Front-End with an Auto-Ranging Technique Achieving 1.8 NEF and 182.3 FoM DR for Energy-Efficient Neural Recording

Hong Liao, Xiaoxu Yang, Minghao Chen, Yuqian Li et autres

cn, us (code pays fourni par la source)

A Multi-Band IoT Tag Featuring a 150Mb/s Calibration-Free 64-QAM Backscatter Modulator and a 10Mb/s LO-Free DBPSK Receiver

Yongling Zhang, Zheng Qin, Lei Qiu, Patrick Mercier et autres

This paper presents the first energy-efficient backscatter tag that supports multi-band high-throughput bi-directional communication, by proposing a universal calibration-free reconfigurable 64-QAM backscatter modulator and a carrier-frequency-independent, LO-Free DBPSK receiver (RX). The chip consumes 9.65 µW for 64-QAM uplink at 150 Mb/s and …

cn, us (code pays fourni par la source)

A Sub-microwatt Blocker-Resilient Crystal-free Receiver for Ambient IoT Applications

Ahmed Gharib Gadelkarim, Patrick Mercier

This paper presents a receiver designed for Ambient IoT-style needs: sub-μW power, SIR<-40dB, and no crystal or off-chip matching networks. It does so by exploiting the power tone used for RF harvesting as an intermodulator processed by an input rectifier to mix …

us (code pays fourni par la source)

A Crystal-Less Backscatter Tag Demonstrating Bi-Directional 802.11b-WiFi Communication with On-the-Fly Baseband Processing

Yongling Zhang, Lei Qiu, Patrick Mercier, Miao Meng

This paper presents a crystal-less WiFi 802.11b backscatter tag, which generates directly-decodable WiFi packets by leveraging ambient, uncontrolled WiFi signals as carriers. This is accomplished by: 1) implementing an envelope-based demodulator that exploits the WiFi Barker-code property to extract pulse-width signatures for …

cn, us (code pays fourni par la source)

A Multi-Head Attention Transformer Model for Wearable in Situ Fall Detection

Jingxiao Tian, Shengjie Xu, Peter Gerstoft, Mahasweta Sarkar et autres

Falls represent a critical health hazard for elderly individuals, often leading to severe injuries and decreased quality of life. While existing fall detection systems predominantly rely on threshold-based algorithms or conventional machine learning approaches like CNNs and RNNs, they frequently exhibit limitations …

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