SpoQFL applies sporadic learning to quantum federated learning by suppressing noisy client updates, claiming higher accuracy and more stable convergence in noisy-device simulations.
Performance Evaluation of LoRa Technology for Rural Connectivity: An Experimental Analysis in Nepal
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abstract
LoRa technology has garnered significant interest in the Information and Communications Technology (ICT) field in recent years due to its ability to operate at low power while maintaining effective communication. Despite gaining attention, LoRa technology faces challenges in effectively facilitating communication in rural settings due to specific transmission and reception conditions. This research paper provides an in-depth analysis of using a LoRa mesh network that accesses the performance of different LoRa configurations by varying parameters like Bandwidth (BW), Spreading Factor (SF), and Coding Rate (CR). Metrics, like the Received Signal Strength Indicator (RSSI), Signal-Noise Ratio (SNR), and packet loss, are analyzed to check the optimal configurations for LoRa nodes, specifically in the context of rural areas of Nepal. Furthermore, the varying propagation loss concerning the change in physical layer parameters is also discussed. The experimental setup utilizes Arduino Uno and ESP 32 microcontroller boards with LoRa modules to build the transmitter and receiver nodes, which are paired with a self-constructed monopole antenna, showing superior gain compared to commercially available options. This paper also explores the potential of integrating the acquired data with cloud platforms such as ThingSpeak. This integration establishes a strong backbone for the Internet of Things (IoT), which can gather and analyze remote data, providing the capacity for remote access to the data. This paper finally recommends specific values for the examined parameters for the specific case of a particular type of hilly and mountainous terrain in a country like Nepal, keeping in mind the unique trade-offs each one offers, thereby enabling optimal rural wireless communication.
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quant-ph 1years
2025 1verdicts
REJECT 1representative citing papers
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Sporadic Federated Learning Approach in Quantum Environment to Tackle Quantum Noise
SpoQFL applies sporadic learning to quantum federated learning by suppressing noisy client updates, claiming higher accuracy and more stable convergence in noisy-device simulations.