Unsourced Multiple Access for Mission-Critical Control Systems in Industrial Internet of Things

In mission-critical Industrial Internet of Things (IIoT), multiple sensors make independent observations at different locations and then transmit them to the base station (BS) to obtain a global system state vector. Uploading observation information to the BS by active sensors is a multiple access process. As the task is to complete state estimation instead of maximizing the physical-layer capacity, conventional multiple access schemes cannot be applied directly to mission-critical IIoT applications. Therefore, next generation multiple access (NGMA) techniques are urgently needed to realize the key performance indicators for the design of IIoT networks. Note that, in mission-critical IIoT systems, each sensor can only obtain the observation of a subset of state variables, and the BS only cares about the state information embedded in that observation not the identities of the sensors. This indicates that the whole process of data transmission and state estimation can be totally unsourced, thus resulting in a highly efficient IIoT system implementation. Based on this crucial finding, in this article, we propose an unsourced multiple access (UMA)-based mission-critical IIoT system. Moreover, a decoupled UMA (D-UMA) scheme is proposed to improve transmission efficiency and state estimation performance. We analyse the fundamental aspects of how our design affects and guarantees the controllability, observability, and stability of an IIoT control system. Simulation results verify the remarkable performance of the proposed scheme compared with the conventional orthogonal multiple access (OMA) and nonorthogonal multiple access (NOMA) schemes.