Game-Theoretic Load Balancing Control for IRS-Aided Multi-AP Joint Transmission in THz Industrial IoT Networks

The demand for automation in Industry 4.0 is driving the growth of wireless Industrial Internet of Things (IIoT) devices. In smart manufacturing, maintaining high reliability and high throughput of Wireless Local Area Networks (WLANs) are equally important for ensuring production safety and efficiency. Terahertz (THz) communication offers high-data-rate and low-latency transmission but faces challenges from coverage and blockage issues. Multi-Access Point (AP) joint transmission allows multiple APs to serve same users simultaneously, and Intelligent Reflecting Surface (IRS) enables the beyond Line-of-Sight (LoS) transmission to bypass obstacles. The integration of these technologies greatly enhances signal availability and system capacity. However, the load balancing problem still remains a critical issue in IIoT networks. Uneven traffic distribution can cause some AP to become overloaded while others remain underutilized. In dynamic industrial scenarios, such imbalance limits the network ability to respond to changing traffic demands. In this paper, we investigate the load balancing problem in IRS-aided THz joint transmission for IIoT networks. A cooperative game-theoretic method is proposed to maintain load balance and user demand satisfaction. Simulation results show that our method improves both network reliability and overall performance.