SharpPeak: Unlocking the True Potential of Tunnel Diodes for Low-Power Long-Range Communication
2026 (English)In: SenSys 2026 - Proceedings of the 2026 ACM/IEEE International Conference on Embedded Artificial Intelligence and Sensing Systems, Part of CPS-IoTWeek 2026, Association for Computing Machinery (ACM) , 2026, p. 29-43Conference paper, Published paper (Refereed)
Abstract [en]
The need for generating radio signals with a high frequency stability and very low phase noise is a demanding requirement in communication systems. In low-power designs, such high-frequency signal generation is often the main source of power consumption, which necessitates low-power alternatives. Although tunnel diodes can generate high-frequency signals at low power, the generated signal is frequency unstable with high phase noise and unwanted harmonics. State-of-the-art address these limitations through injection locking, which requires an external signal generator that significantly increases the overall system power consumption. We present SharpPeak, a low-power long-range transmitter design that achieves high frequency stability using tunnel diodes without relying on external injection signals. This design lowers both system power and transmitter complexity, while improving frequency stability, phase noise, and frequency drifts. SharpPeak achieves high (370 kbps) data rates and long (1 km) communication range with under 175 μW power consumption at the RF front-end, advancing the state-of-the-art in energy-efficient communication systems. We believe that this work is a significant advancement in the development of a new generation of low-power communication systems. © 2026
Place, publisher, year, edition, pages
Association for Computing Machinery (ACM) , 2026. p. 29-43
Keywords [en]
Backscatter Communication, Bifurcation, Limit Cycles, Long-Range Communication, Sensing, Signal Generation, Tunnel Diode
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:ri:diva-81806DOI: 10.1145/3774906.3800468Scopus ID: 2-s2.0-105040941982OAI: oai:DiVA.org:ri-81806DiVA, id: diva2:2076547
Conference
International Conference on Embedded Artificial Intelligence and Sensing Systems, SenSys 2026, Saint Malo
Note
QC 20260622
2026-06-222026-06-222026-06-22Bibliographically approved