arXiv subjects

José Álamos

Publications and source records attributed to José Álamos.

5 recordsLinked to original sources

arXiv2026

LZn : Robust LoRa Frame Synchronization Under Frame Collisions and Ultra-Low SNR Conditions

LoRa has become a widely adopted wireless modulation scheme in LPWANs due to its low cost, long range, and minimal transmission power. However, collisions between frames of the same spreading factor -- common in dense LoRa deployments -- prevent conventional LoRa receivers from detecting and correctly decoding frames. Recent work has introduced methods to improve recovery, yet their detection stage degrades sharply under low signal-to-noise ratio (SNR) and high collision rates. In this work, we introduce LZn, a low-complexity synchronization scheme driven by a spectral intersection operation. Our method enables robust frame synchronization even under multiple packet overlaps or extremely low SNR conditions. We evaluate LZn on simulations and three independent, real-world LoRa datasets. LZn improves detection sensitivity by up to 10dB and increases detection probability by up to 1.54x. In real-world datasets, LZn improves decoding by 3.46x in the most challenging single-user scenario and up to 1.22x in collision scenarios compared to the second best collision-tolerant scheme (TnB). These results demonstrate that LZn substantially improves the frame recovery of LoRa receivers, while remaining compatible with real-time requirements.

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arXiv2025

CoRa: A Collision-Resistant LoRa Symbol Detector of Low Complexity

Long range communication with LoRa has become popular as it avoids the complexity of multi-hop communication at low cost and low energy consumption. LoRa is openly accessible, but its packets are particularly vulnerable to collisions due to long time on air in a shared band. This degrades communication performance. Existing techniques for demodulating LoRa symbols under collisions face challenges such as high computational complexity, reliance on accurate symbol boundary information, or error-prone peak detection methods. In this paper, we introduce CoRa , a symbol detector for demodulating LoRa symbols under severe collisions. CoRa employs a Bayesian classifier to accurately identify the true symbol amidst interference from other LoRa transmissions, leveraging empirically derived features from raw symbol data. Evaluations using real-world and simulated packet traces demonstrate that CoRa clearly outperforms the related state-of-the-art, i.e., up to 29% better decoding performance than TnB and 178% better than CIC. Compared to the LoRa baseline demodulator, CoRa magnifies the packet reception rate by up to 11.53x. CoRa offers a significant reduction in computational complexity compared to existing solutions by only adding a constant overhead to the baseline demodulator, while also eliminating the need for peak detection and accurately identifying colliding frames.

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arXiv2023

6LoRa: Full Stack IPv6 Networking with DSME-LoRa on Low Power IoT Nodes

Long range wireless transmission techniques such as LoRa are preferential candidates for a substantial class of IoT applications, as they avoid the complexity of multi-hop wireless forwarding. The existing network solutions for LoRa, however, are not suitable for peer-to-peer communication, which is a key requirement for many IoT applications. In this work, we propose a networking system - 6LoRa, that enables IPv6 communication over LoRa. We present a full stack system implementation on RIOT OS and evaluate the system on a real testbed using realistic application scenarios with CoAP. Our findings confirm that our approach outperforms existing solutions in terms of transmission delay and packet reception ratio at comparable energy consumption.

cs.NI↗

arXiv2022

DSME-LoRa: Seamless Long Range Communication Between Arbitrary Nodes in the Constrained IoT

Long range radio communication is preferred in many IoT deployments as it avoids the complexity of multi-hop wireless networks. LoRa is a popular, energy-efficient wireless modulation but its networking substrate LoRaWAN introduces severe limitations to its users. In this paper, we present and thoroughly analyze DSME-LoRa, a system design of LoRa with IEEE 802.15.4 DSME as a MAC layer. DSME-LoRa offers the advantage of seamless client-to-client communication beyond the pure gateway-centric transmission of LoRaWAN. We evaluate its feasibility via a full-stack implementation on the popular RIOT operating system, assess its steady-state packet flows in an analytical stochastic Markov model, and quantify its scalability in massive communication scenarios using large scale network simulations. Our findings indicate that DSME-LoRa is indeed a powerful approach that opens LoRa to standard network layers and outperforms LoRaWAN in many dimensions.

cs.NI↗

arXiv2022

WIP: Exploring DSME MAC for LoRa -- A System Integration and First Evaluation

LoRa is a popular wireless technology that enables low-throughput (bytes) long-range communication (km) at low energy consumption (mW). Its transmission, though, is on one side prone to interference during long on-air times, and on the other side subject to duty cycle restrictions. LoRaWAN defines a MAC and a vertical stack on top of LoRa. LoRaWAN circumvents the above limitations by imposing a centralized network architecture, which heavily reduces downlink capacity and prevents peer-to-peer communication. This makes it unusable for many deployments. The Deterministic and Synchronous Multichannel Extension (DSME) of IEEE 802.15.4e benefits of time-slotted communication and peer-to-peer communication and has the potential to overcome LoRaWAN limitations. In this work, we implement DSME on top of LoRa in the open source IoT OS RIOT and open the field for first evaluation experiments on real hardware. Initial results indicate that DSME-LoRa not only enables reliable peer-to-peer communication for constrained IoT devices, but also scales with an increasing number of nodes.

cs.NI↗