Massively Enhancing 6G IoT Data Collection with Analog Backscatter

Purpose and goal

The goal of this project is to massively enhance 6G massive IoT’s data collection capabilities. Our key idea is to deploy and integrate additional extremely energy-efficient analog backscatter tags. Analog tags directly modulate sensor data on the carrier wave, avoiding energy expensive digital components onboard. Emerging applications such as digital twins and the training of machine learning algorithms require huge amounts of data which our tags can collect at an extremely low cost.

Expected effects and result

By the end of the project, we expect to develop and test hardware and software to integrate battery-free analog backscatter tags into the 6G infrastructure in an indoor setup. The deliverables are: (1) mmWave analog sensor prototype, (2) ZE-IoT gateway- communication, and (3) Analysis of ML and security for the ZE-IoT gateway. Analog backscatter is in an early research phase today. Its integration into the 6G network would enable scalable and cost-efficient data collection.

Planned approach and implementation

We build on our previous work on backscatter communication to design an analog backscatter tag and extend its frequency range. For the sub-GHz case (as typical for the standard mobile systems), we utilize one ZE-IoT device with memory and computation capabilities as a gateway. In upper mid-band and mmWave frequencies, we expect the base station to directly communicate with the analog sensors, without the additional gateway. We analyze different solutions and implement them on real hardware.