BETS: A MIMO-Based Approach for Enhancing Time-Sensitive Traffic Delivery in Industrial Wireless Networks
Abstract
The rise of Industry 4.0 has driven the need for ultra-reliable, low-latency wireless communication systems capable of supporting Time-Sensitive Networking (TSN) requirements. While traditional research in Multiple-Input Multiple-Output (MIMO) has focused on maximizing spectral efficiency and bitrate, and TSN work has emphasized scheduling, there is significant potential in applying beamforming to improve TSN capacity—a topic that has received limited attention in the literature. In this work, we propose a novel joint scheduling, and resource allocation framework for mmWave MIMO networks that integrates spatial multiplexing through MIMO beamforming, OFDMA, and traffic shaping for TSN streams. We formulate the problem of optimizing both frame scheduling and network provisioning as a unified, though computationally intractable, problem. To address this, we propose the Beam Enhanced Time Shaping (BETS) algorithm, a practical iterative heuristic based on alternating optimization. BETS tackles the challenge by jointly optimizing network provisioning (MIMO beamweights and bandwidth partitioning) and network demand (frame-level schedules). Simulation results in an indoor factory setting with mmWave channel models show that BETS outperforms an equal-resource-allocation baseline, improving the number of satisfied TSN streams by 39% to 50%. These results also demonstrate BETS's robustness, scalability, and potential for deployment in future MIMO-enabled industrial networks.