Deep Learning-based receiver for Uplink in LoRa Networks with Sigfox Interference - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2022

Deep Learning-based receiver for Uplink in LoRa Networks with Sigfox Interference

Résumé

The Internet of Things faces a significant scaling issue due to the rapid growth of the number of devices and asynchronous communications. Different technologies in the license-free industrial, scientific, and medical (ISM) band have been widely deployed to fill this gap. LoRa and Sigfox are the most common. Many devices can use the ISM band if they obey the regulations and cope with internal and external interference. However, when there is massive connectivity, the effect of inter and intra-network interference between multiple networks is significant. This study uses a deep learning-based technique to decode signals and deal with the interference in the uplink of a LoRa network. Two classification-based symbol detection methods are proposed using a deep feedforward neural network (DFNN) and a convolutional neural network (CNN). The proposed receivers can decode the signals of a selected user when many LoRa users transmit simultaneously using the same spreading factor over the same frequency band (intra-spreading factor interference) and multiple Sigfox users interfere (internetwork interference). Simulation results show that both receivers outperform the conventional LoRa receiver in the presence of interference. For a target symbol error rate (SER) of 0.001, the proposed DFNN and CNN-based receivers attain around 2 dB and 3.5 dB gain, respectively.
Fichier principal
Vignette du fichier
Deep_Learning_based_receiver_for_Uplink_in_LoRa_Networks_with_Sigfox_Interference.pdf (646.55 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03847016 , version 1 (10-11-2022)

Identifiants

Citer

Angesom Ataklity Tesfay, Eric Pierre Simon, Sofiane Kharbech, Laurent Clavier. Deep Learning-based receiver for Uplink in LoRa Networks with Sigfox Interference. IEEE 18th International Conference on Wireless and Mobile Computing, Networking and Communications, WiMob 2022, Oct 2022, Thessaloniki, Greece. pp.25-29, ⟨10.1109/WiMob55322.2022.9941543⟩. ⟨hal-03847016⟩
113 Consultations
67 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More