Cross-Layer optimization design of solar assisted LoRa sensor network for smart agriculture

This study addresses the challenges of energy supply and communication reliability in wireless sensor networks for smart agriculture scenarios, proposing an optimized design method for solar-assisted LoRa sensor networks across layers. By establishing a solar energy harvesting model and a LoRa communication power consumption model, a joint optimization framework is constructed that spans physical layers, MAC layers, and network layers. The proposed adaptive transmission parameter adjustment algorithm can dynamically adjust spreading factors, transmission power, and data rates based on energy status and communication requirements. Experimental results show that compared to traditional methods, this approach improves energy efficiency, extends network lifespan , and ensures the reliability of agricultural data collection. Case studies further validate the effectiveness of this method in practical smart farmland monitoring systems. This research provides new insights into optimizing LoRa networks in energy-constrained environments and is significant for advancing IoT technology in smart agriculture.