## 1 Introduction
However, designing better resource allocation algorithms to manage the inter-user interference between D2D users and cellulars is the key challenge for improving system performance. Resource allocation and interference problems of D2D communication have been investigated in many works [13; 14; 15]. The authors in [16] propose a cell sectorization scheme to alleviate the interference between cellular users and D2D users. In [17], the authors investigate interference coordination for downlink full-dimension multiple-output systems with underlying D2D communications. Adopting D2D technology, the number of supported devices can be improved in mMTC scenarios [18]. By allowing unauthorized devices to reuse the frequency bands of authorized cellular users, bandwidth utilization can be improved [19; 20; 21]. The literature [22] proposes a heuristic subcarrier allocation method to set the user's signal-to-noise ratio (SNR) threshold to meet the QoS of the system. The authors in [23] propose a mobile traffic offloading scheme that combines small base stations with D2D offloading. The goal is to accommodate a large number of MTC connections by maximizing the throughput of the network system. The impact of radio frequency energy harvesting on the spectral efficiency of the D2D-assisted MTC system is analyzed first in [24]. In [25], the authors propose two solutions to manage the communication between D2D devices and the BS to lighten the overhead of MTC devices on the 5G network. However, resource allocation [19; 20; 21; 22; 23; 24; 25] mainly focuses on throughput maximization or interference minimization. In an IIoT enabled by D2D communications, massive devices demand access to the network via D2D mode. Thus, the connectivity maximization problem becomes a challenging issue to tackle. To support a system in which the number of users is higher than the number of subcarriers, a range of fair subcarrier allocation algorithms is proposed that always improves the reliability [26]. However, the author only considers the scenario of mobile users in the downlink and does not consider the influence of interference. In this paper, we investigate a D2D-enabled internet of things in which some devices (enhanced Mobile Broadband (eMBB) devices) connect to the centralized controller while other devices (mMTC devices) communicate with their adjacent devices via D2D communication to promote inter-device cooperation in industry automation. Specifically, mMTC devices reuse the spectrum resource with eMBB devices. We establish the connectivity maximization problem of mMTC devices while guaranteeing the QoS of eMBB devices and mMTC devices. Furthermore, we propose an interference-aware subcarrier allocation algorithm to tackle the problem. The main contributions of this paper are as follows:  
* We establish a problem of maximizing the number of accessed mMTC pairs subject to the constraints of QoS in a system with both eMBB and mMTC devices, which is proven to be a mixed-integer non-linear programming (MINLP) problem. * We propose an interference-aware subcarrier allocation algorithm for mMTC (IASA) considering the interference range of each mMTC device. * In order to evaluate the proposed algorithm, a simulation is conducted. The results demonstrate that the proposed algorithm outperforms two benchmark algorithms significantly in terms of the number of mMTC pairs accessed under the same constraints. The remainder of the paper is organized as follows. The system model and assumptions is elaborated in the \"System Model\" section. The optimization problem and constraints are introduced in the \"Problem Formulation\" section. The proposed subcarrier allocation algorithm is presented in the \"Interference-Aware Subcarrier Allocation for mMTC Communication Algorithm\" section. Comprehensive simulation results are provided in the \"Simulation result analysis\" section. Finally, we conclude the paper in the \"Conclusion\" section.