Maximizing the Connectivity of Wireless Network Slicing Enabled Industrial Internet-of-Things

作者：Yin Bo, Jianhua Tang, Miaowen Went · 发表于：2021 IEEE Global Communications Conference (GLOBECOM) · 年份：2021 · DOI：10.1109/globecom46510.2021.9685411 · 被引用次数：9 · 研究领域：Advanced Wireless Communication Technologies、IoT and Edge/Fog Computing、Full-Duplex Wireless Communications

The emergence of 5G brings unprecedented possibilities for deploying the anticipated Industrial Internet of Things (IIoT). To achieve high density connectivity with multiple services in 5G empowered IIoT, we consider the non-orthogonal network slicing in this work. In particular, we jointly utilize network slicing to incorporate two different types of services and exploit non-orthogonal multiple access (NOMA) to maximize the number of total devices that can be accessed to the system. We formulate the connectivity maximization problem as a mixed-integer nonlinear programming (MINLP) by jointly optimizing the transmit power and device-subcarrier association. To tackle the intractable MINLP, we first transform it into a mixed-integer linear programming (MILP) and then reduce the MILP by devising a simple but effective transmit power allocation scheme. Thereafter, we propose a low-complexity best-effort pairing (BEP) algorithm to solve the reduced MILP. By comprehensive simulations, we find that our proposed BEP significantly outperforms the benchmark schemes.