Abstract
The LoRa radio technology has been recently expanded into the 2.4 GHz spectrum, which offers advantages such as increased bandwidth and global regulation compatibility. 2.4 GHz LoRa promises higher data rates and throughput, crucial for data-intensive industrial applications. It maintains key features such as long-range communication and low power consumption, making it suitable for various industrial Internet of Things (IoT) applications. However, 2.4 GHz gateways face challenges due to their design limitations that require only one Spreading Factor (SF) setting and channel to be assigned to each of the four available transceivers. This design limits the number of available options that the end-devices (EDs) can have and leads to resource allocation problems. To this extent, this paper presents a gateway configuration problem for 2.4 GHz LoRa gateways, mainly aiming at providing a trade-off between energy consumption and fairness among end-devices. A bi-objective optimization problem is introduced, which is solved by considering a convex combination of two objective functions. A λ ∈[0,1] coefficient is employed to discover a Pareto optimal solution between the two objectives. Due to the high computational complexity of the integer linear programming (ILP) approach, two practical heuristics with lower computation costs are also proposed. Simulation results show that the proposed approaches exhibit better fairness and packet reception ratio (PRR) compared to the static configuration of gateways. Moreover, the results reveal that λ is capable of providing a trade-off between fairness and energy efficiency. The findings are confirmed by conducting experiments on a small-scale testbed consisting of 16 ESP32 devices.
Original language | English |
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Article number | 101567 |
Journal | Internet of Things (The Netherlands) |
Volume | 31 |
DOIs | |
Publication status | Published - May 2025 |
Keywords
- 2.4 GHz ISM
- Energy consumption
- Fairness
- LoRa
- Optimization
ASJC Scopus subject areas
- Software
- Computer Science (miscellaneous)
- Information Systems
- Engineering (miscellaneous)
- Hardware and Architecture
- Computer Science Applications
- Artificial Intelligence
- Management of Technology and Innovation