A Low-Complexity LoRa Synchronization Algorithm Robust to Sampling Time Offsets

TL;DR

This paper introduces a low-complexity synchronization algorithm for LoRa receivers that effectively corrects sampling time and carrier frequency offsets, enhancing robustness with minimal computational overhead.

Contribution

It presents a new analytical model and an iterative synchronization algorithm for LoRa, addressing the previously overlooked issue of sampling time offsets.

Findings

Achieves a packet error rate of 10^-3 with only 1-2 dB higher SNR than ideal.

Requires low computational overhead, suitable for low-power IoT devices.

Demonstrates effective correction of both sampling time and carrier frequency offsets.

Abstract

LoRaWAN is nowadays one of the most popular protocols for low-power Internet-of-Things communications. Although its physical layer, namely LoRa, has been thoroughly studied in the literature, aspects related to the synchronization of LoRa receivers have received little attention so far. The estimation and correction of carrier frequency and sampling time offsets is however crucial to attain the low sensitivity levels offered by the LoRa spread-spectrum modulation. The goal of this paper is to build a low-complexity, yet efficient synchronization algorithm capable of correcting both offsets. To this end, a complete analytical model of a LoRa signal corrupted by these offsets is first derived. Using this model, we propose a new estimator for the sampling time offset. We also show that the estimations of the carrier frequency and the sampling time offsets cannot be performed independently. Therefore, to avoid a complex joint estimation of both offsets, an iterative low-complexity synchronization algorithm is proposed. To reach a packet error rate of 10^-3, performance evaluations show that the proposed receiver requires only 1 or 2 dB higher SNR than a theoretical perfectly synchronized receiver, while incurring a very low computational overhead.