arXiv subjects

Joachim Tapparel

Publications and source records attributed to Joachim Tapparel.

5 recordsLinked to original sources

arXiv2026

Centralized RAN for Future Low-Power Wide-Area Networks: A LoRa Case Study

In recent years, low-power wide-area network (LPWAN) technologies have gained significant traction as a connectivity option for Internet of Things (IoT) applications. While these networks have been successful in providing long-range, low-power, and low-cost connectivity, they currently face scalability, reliability, and efficiency challenges that require immediate attention. In this paper, we first identify important challenges for LPWANs. We then advocate for the introduction of a centralized radio access network (C-RAN) architecture tailored for LPWANs and present a proof-of-concept implementation and deployment of the proposed C-RAN for the widely popular long range (LoRa) standard. We also provide experimental results to demonstrate and quantify the increased sensitivity that can be obtained from joint processing of the baseband signals of multiple receivers, enabled by the proposed centralized architecture in quasi-static scenarios and drone-mounted transmitters.

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arXiv2025

Dataset and UAV Propagation Channel Modeling for LoRa in the 860 MHz ISM Band

LoRa is one of the most widely used low-power wide-area network technology for the Internet of Things. To achieve long-range communication with low power consumption at a low cost, LoRa uses a chirp spread spectrum modulation and transmits in the sub-GHz unlicensed industrial, scientific, and medical (ISM) frequency bands. Due to the rapid densification of IoT networks, it is crucial to obtain tailored channel models to evaluate the performance of LoRa networks. While channel models for cellular technologies have been investigated extensively, specific characteristics of LoRa transmissions operating at long range with a rather small (~ 250kHz) bandwidth require dedicated measurement campaigns and modeling efforts. In this work, we leverage an SDR-based testbed to gather and publish a dataset of LoRa frames transmitted in a campus environment. The dataset includes IQ samples of the received frames at multiple locations and allows for the evaluation of channel variations with high time resolution. Using the gathered data, we derive empirical propagation channel models for LoRa that include receiver correlation over distance for three scenarios: unmanned aerial vehicle (UAV) line-of-sight (LoS), UAV non-LoS, and pedestrian non-LoS. Furthermore, the dataset is annotated with synchronization information, enabling the evaluation of receiver algorithms using experimental data.

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arXiv2025

LoRa Fine Synchronization with Two-Pass Time and Frequency Offset Estimation

LoRa is currently one of the most widely used low-power wide-area network (LPWAN) technologies. The physical layer leverages a chirp spread spectrum modulation to achieve long-range communication with low power consumption. Synchronization at long distances is a challenging task as the spread signal can lie multiple orders of magnitude below the thermal noise floor. Multiple research works have proposed synchronization algorithms for LoRa under different hardware impairments. However, the impact of sampling frequency offset (SFO) has mostly either been ignored or tracked only during the data phase, but it often harms synchronization. In this work, we extend existing synchronization algorithms for LoRa to estimate and compensate SFO already in the preamble and show that this early compensation has a critical impact on the estimation of other impairments such as carrier frequency offset and sampling time offset. Therefore it is critical to recover long-range signals.

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arXiv2020

A Maximum-Likelihood-based Multi-User LoRa Receiver Implemented in GNU Radio

LoRa is a popular low-power wide-area network (LPWAN) technology that uses spread-spectrum to achieve long-range connectivity and resilience to noise and interference. For energy efficiency reasons, LoRa adopts a pure ALOHA access scheme, which leads to reduced network throughput due to packet collisions at the gateways. To alleviate this issue, in this paper we analyze and implement a LoRa receiver that is able to decode LoRa packets from two interfering users. Our main contribution is a two-user detector derived in a maximum-likelihood fashion using a detailed interference model. As the complexity of the maximum-likelihood sequence estimation is prohibitive, a complexity-reduction technique is introduced to enable a practical implementation of the proposed two-user detector. This detector has been implemented along with an interference-robust synchronization algorithm on the GNU Radio Software-Defined-Radio (SDR) platform. The SDR implementation shows the effectiveness of the proposed method and also allows its experimental evaluation. Measurements indicate that our detector inherently leverages the time offset between the two colliding users to separate and demodulate their contributions.

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arXiv2020

An Open-Source LoRa Physical Layer Prototype on GNU Radio

LoRa is the proprietary physical layer (PHY) of LoRaWAN, which is a popular Internet-of-Things (IoT) protocol enabling low-power devices to communicate over long ranges. A number of reverse engineering attempts have been published in the last few years that helped to reveal many of the LoRa PHY details. In this work, we describe our standard compatible LoRa PHY software-defined radio (SDR) prototype based on GNU Radio. We show how this SDR prototype can be used to develop and evaluate receiver algorithms for LoRa. As an example, we describe the sampling time offset and the carrier frequency offset estimation and compensation blocks. We experimentally evaluate the error rate of LoRa, both for the uncoded and the coded cases, to illustrate that our publicly available open-source implementation is a solid basis for further research.

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