Structured Packet Scheduling for Ground-Based LoRa IoT Networks: Trends, Challenges and TDMA Solutions
This article provides a detailed examination of structured packet scheduling methodologies in ground-based LoRa networks, with a special emphasis on Time Division Multiple Access (TDMA) techniques. As LoRa becomes an important enabler for long-range, low-power IoT deployments, managing packet collisions and energy efficiency in dense, multi-sensor node environments has become a crucial challenge, particularly in the ground segment of space-integrated IoT systems. Traditional ALOHA-based access methods have significant collision rates and unpredictable delays, highlighting the need for more deterministic and scalable scheduling algorithms. This paper examines current advances in TDMAbased frameworks, adaptive scheduling algorithms, and synchronisation approaches that aim to improve real-time data transfer from sensor nodes to ground gateways. Comparative analyses are carried out to assess techniques in terms of packet delivery ratio, latency, and energy performance, using data from both simulation-based research and prototype implementations. Furthermore, emergent research issues like AI-assisted scheduling, predictive synchronisation, and hardware testbeds are investigated as potential solutions to practical restrictions. By focusing solely on the ground segment, this study highlights the importance of intelligent, energyefficient TDMA scheduling for dependable packet aggregation in LoRa-based IoT networks. The findings are intended to direct future research into establishing strong, scalable communication frameworks for environmental monitoring, disaster management, and other vital remote sensing applications.
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