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An Energy-Efficient and High-Data-Rate IR-UWB Transmitter for Intracortical Neural Sensing Interfaces

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This article presents an implantable impulse-radio ultra-wideband (IR-UWB) wireless telemetry system for intracortical neural sensing interfaces. A 3-D hybrid impulse modulation that comprises phase shift keying (PSK), pulse position modulation… Click to show full abstract

This article presents an implantable impulse-radio ultra-wideband (IR-UWB) wireless telemetry system for intracortical neural sensing interfaces. A 3-D hybrid impulse modulation that comprises phase shift keying (PSK), pulse position modulation (PPM), and pulse amplitude modulation (PAM) is proposed to increase modulation order without significantly increasing the demodulation requirement, thus leading to a high data rate of 1.66 Gbps and an increased air-transmission range. Operating in a 6–9-GHz UWB band, the presented transmitter (TX) supports the proposed hybrid modulation with a high energy efficiency of 5.8 pJ/bit and modulation quality [error vector magnitude (EVM) < −21 dB]. A low-noise injection-locked ring oscillator (ILRO) supports 8-PSK with a phase error of 2.6°. A calibration-free delay generator realizes a 4-PPM with only $115~\mu \text{W}$ and avoids potential cross-modulation between PPM and PSK. A switch-cap power amplifier (PA) with asynchronous pulse-shaping performs 4-PAM with high energy efficiency and linearity. The TX is implemented in 28-nm CMOS technology, occupying a 0.155 mm2 core area. The wireless module including a printed monopole antenna has a module area of only 1.05 cm2. The TX consumes in total 9.7 mW when transmitting −41.3-dBm/MHz output power. The wireless telemetry module has been validated ex-vivo with a 15-mm multi-layer porcine tissue, and achieves a communication (air) distance up to 15 cm, leading to at least $16\times $ improvement in distance-moralized energy efficiency of 45 pJ/bit/m compared to a state-of-the-art.

Keywords: sensing interfaces; modulation; energy; high data; intracortical neural; neural sensing

Journal Title: IEEE Journal of Solid-State Circuits
Year Published: 2022

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