OptSamp: Optimizing the Sampling Rate for LoRa Energy Efficiency Enhancement

Abstract

LoRa, as a widely used Low-Power Wide-Area Network (LP-WAN) technology, is designed for long-term use. However, in practice, the battery life of LoRa devices often falls far short of the expected decade-long duration. We propose OptSamp, a software-based approach that reduces the energy consumption of LoRa devices by lowering their physical-layer sampling rate, thereby extending battery life. To address the challenge of frequency aliasing caused by down-sampling, we embed a specially designed feature into each modulated symbol, enabling the OptSamp receiver to accurately recover the distorted signal. In addition, we design an adaptive sampling-rate selection mechanism to balance link reliability and energy efficiency. We further propose OptSamp+, which compresses symbol duration to shorten uplink transmission time, thereby reducing transmitter energy consumption and enhancing spectral efficiency. We prototype OptSamp and OptSamp+ on software-defined LoRa platforms and evaluate them in both indoor and outdoor environments. Results show that OptSamp reduces the receiver-side sampling rate to 1/16 of the Nyquist rate, cutting downlink energy consumption by 68%, and OptSamp+ reduces uplink transmission time by up to 1/32 compared to traditional LoRa.