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The emergence of Industrial Internet of Things (IIoT) networks has sparked a demand for reliable and efficient communication systems. One promising strategy to overcome interference and coverage issues in IIoT setups is leveraging massive multiple-input multiple-output (MIMO) technology in a cell-free configuration. However, implementing large antenna arrays for such systems can be impractical and expensive, especially in remote or dynamic environments. Unmanned aerial vehicles (UAVs) have emerged as a versatile solution, including for communication relays. This study investigates the integration of UAV swarms into cell-free massive MIMO systems for IIoT networks. The proposed approach involves deploying a swarm of UAVs equipped with multiple antennas as aerial base stations to serve ground-based IIoT devices. It examines the benefits of employing UAV swarms, such as expanded coverage, better interference management, and increased flexibility. Additionally, it addresses challenges like UAV mobility, resource allocation, and power consumption. To address these challenges, an algorithm for resource allocation is proposed. This algorithm considers factors like UAV mobility, quality-of-service requirements for IIoT devices, and interference among UAVs. It aims to optimize transmit power and antenna selection for each UAV, ensuring QoS satisfaction and enhancing overall system capacity. Simulation results demonstrate the effectiveness of the algorithm, indicating improvements in system capacity, coverage, and interference management. Moreover, the findings highlight the trade-offs between system performance and power consumption within the UAV swarm. In essence, this study contributes to understanding the potential of utilizing UAV swarms in cell-free massive MIMO systems for IIoT networks. The proposed resource allocation algorithm offers insights for planning and enhancing such nodes, paving the way for further research and development in this promising field. |
