On the Connectivity Maximization in NOMA-Aided Industrial IoT With Multiple Services

Abstract

Industrial Internet-of-Things (IIoT) improving by leaps and bounds has brought new possibilities for industrial manufacturing. Meanwhile, it does bring some serious challenges with the increasing number of devices. In which massive connectivity and multi-service are two major challenges for IIoT. In order to address the two main issues, in this paper, we jointly consider non-orthogonal multiple access (NOMA) and wireless network slicing scenario, where multi-service devices share the same communication resources. To connect devices as many as possible, we formulate the connectivity maximization problem with joint sub-carrier association and power allocation as a mixed-integer nonlinear programming (MINLP) problem, under the constraints of limited communication resources. To solve the problem effectively, we first split the MINLP problem into two subproblems by introducing a power allocation weight. Then, we analyze the theoretical approach for a special case and propose the Layered Access (LA) algorithm for general cases. Furthermore, a Bisection Search (Bisearch) algorithm is devised to find out the optimal power allocation weight. Simulation results show that the proposed LA algorithm has better performance compared to other benchmark schemes.