B2LoRa: Boosting LoRa Transmission for Satellite-IoT Systems with Blind Coherent Combining

TL;DR

This work tackles unreliable LoRa downlinks in satellite-IoT by introducing B2LoRa, a blind coherent combining method that leverages the repeated broadcasting of beacons to coherently sum retransmissions without channel-state information. The approach comprises three components: joint packet sniffing with a SAR-inspired detection, frequency shift alignment using a linear intra-packet DFS model and rotating conjugate multiplication, and phase drift mitigation via an initial phase search with a small number of candidates. Experiments on a real-world satellite-IoT testbed and an SDR-based setup show substantial gains: approximately 9 dB in packet-detection and notable PRR improvements over LoRa, XCopy, and Spectrumize, across diverse passes and parameter settings. The results demonstrate that B2LoRa can improve link reliability for satellite-IoT IoT ground devices without requiring orbital data or large payloads, enabling more scalable, global IoT coverage with low-cost hardware. $SF$ and $BW$ configurations, Doppler offsets, and PLL-induced phase drift are effectively managed, highlighting the method's practical impact for future satellite-IoT deployments.

Abstract

With the rapid growth of Low Earth Orbit (LEO) satellite networks, satellite-IoT systems using the LoRa technique have been increasingly deployed to provide widespread Internet services to low-power and low-cost ground devices. However, the long transmission distance and adverse environments from IoT satellites to ground devices pose a huge challenge to link reliability, as evidenced by the measurement results based on our real-world setup. In this paper, we propose a blind coherent combining design named B2LoRa to boost LoRa transmission performance. The intuition behind B2LoRa is to leverage the repeated broadcasting mechanism inherent in satellite-IoT systems to achieve coherent combining under the low-power and low-cost constraints, where each re-transmission at different times is regarded as the same packet transmitted from different antenna elements within an antenna array. Then, the problem is translated into aligning these packets at a fine granularity despite the time, frequency, and phase offsets between packets in the case of frequent packet loss. To overcome this challenge, we present three designs - joint packet sniffing, frequency shift alignment, and phase drift mitigation to deal with ultra-low SNRs and Doppler shifts featured in satellite-IoT systems, respectively. Finally, experiment results based on our real-world deployments demonstrate the high efficiency of B2LoRa.

Figures (15)

• Figure 1: Measurement results on our real-world testbed during three satellite passes at varying MAX elevation angles: (a) The Cumulative Distribution Function (CDF) of the variation in packet arrival intervals between re-transmissions; (b) The changing Doppler shift (when the carrier frequency is 503 MHz).
• Figure 2: The spectrogram of a LoRa packet.
• Figure 3: The overview of satellite-IoT systems.
• Figure 4: The real-world satellite-IoT testbed: (a) Our satellite's LoRa transmitter (Semtech SX1276); (b) Our IoT devices with LoRa receiver (Semtech SX1276); (c) Our satellite's orbit; (d) Our satellite's sub-point trajectory in three days; (e) The CDF of an IoT device of the testbed detecting at least one LoRa packet transmitted by our satellite during passes of varying MAX elevation angles; (f) The average number of times the satellite passes over four different latitude locations each day, based on data over 90 days, categorized by the MAX elevation angle (denoted as $i$) of each pass.
• Figure 5: The framework of $\text{B}^2$LoRa.

Theorems & Definitions (1)

• Proposition 1