The development of Industrial Internet of Things (IIoT) has been limited due to the shortage of spectrum resources. Based on cognitive radio (CR), cognitive IIoT (CIIoT) has been proposed to improve spectrum utilization via sensing and accessing the idle spectrum. To improve sensing and transmission performance of the CIIoT, a cluster-based CIIoT is proposed, wherein the cluster heads perform cooperative spectrum sensing to get available spectrum and the nodes transmit via Non-orthogonal Multiple Access (NOMA). The frame structure of the CIIoT is designed, and the spectrum access probability and average total throughput of the CIIoT are deduced. A joint resource optimization for sensing time, node powers and the number of clusters is formulated to maximize the average total throughput. The optimal solution is obtained via sensing and power optimization. The clustering algorithm and cluster head alternation are proposed to improve transmission performance and ensure energy balance, respectively. The simulations have indicated that the NOMA for the cluster-based CIIoT can better guarantee the transmission performance of each node, especially the node decoding first, than the traditional NOMA and OMA.

The shortage of spectrum resources has limited the development of Internet of Things (IoT). Fifth generation (5G) network can flexibly support a variety of devices and services, which makes it possible to combine 5G with IoT. In this paper, a novel multichannel IoT is proposed to dynamically share the spectrum with 5G Communication, where an IoT node including transmitter and receiver is designed to perform 5G communication and IoT communication simultaneously. The subchannel sets allocated for 5G communication and IoT communication are defined by two complementary spectrum marker vectors, respectively. Two independent spectrum sequences are generated by calculating the inner product of spectrum marker vector, pseudo-random (PR) phase and power scaling vector. Two time-domain fundamental modulation waveforms (FMW) generated by the inverse fast fourier transform (IFFT) of the spectrum sequences are used to modulate 5G data and IoT data, respectively. The receiver can detect the data using the same spectrum marker vectors as the transmitter. The BER performances of the system using binary modulation and cyclic code shift keying (CCSK) modulation in the cases of spectrum marker error and multiple access are analyzed, respectively. A subchannel and power optimization unit is formulated as a joint optimization problem, which seeks to maximize the 5G throughput under the constraints of minimal IoT throughput, maximal power and maximal interference. An alternative optimization problem is proposed to maximize the IoT throughput while guaranteeing the minimal 5G throughput. A joint optimization algorithm based on Lagrange dual decomposition is proposed to achieve the optimal solution. Simulation results indicate that the proposed IoT can improve the 5G throughput significantly while the IoT throughput is guaranteed.

The traditional ground industrial internet of things (IIoT) cannot supply wireless interconnections anywhere due to the small-scale communication coverage. In this paper, a multibeam satellite IIoT in Ka-band is proposed to realize wide-area coverage and long-distance transmissions, which uses NOMA for the beam to improve transmission rate. To guarantee QoS for the satellite IIoT, the beam power is optimized to match the theoretical transmission rate with the service rate. The transmission rate for each beam is maximized by optimizing the power allocation proportion of each node subject to the constraints of the total power for the beam and the minimal transmission rate for each node. Satellite-ground integrated IIoT is proposed to use the ground cellular network to supplement the satellite coverage in the blocked areas. The power allocation and network selection for the integrated IIoT are proposed to decrease the transmission cost. Simulation results are provided to validate the superiority of employing NOMA in the satellite IIoT and show lower transmission cost for the integrated IIoT.

Due to its flexibility and high maneuverability, Unmanned Aerial Vehicle (UAV) is able to quickly provide wireless connections to the ground vehicles in mobile environment. In this paper, a multi-UAV enabled mobile Internet of Vehicles (IoV) model is proposed, where the UAVs track to serve the mobile vehicles and send downlink information to the vehicles during the flight time. Considering the constraints of anti-collision and communication interference between the UAVs, the system throughput is maximized by jointly optimizing vehicle communication scheduling, UAV power allocation and UAV trajectory. The formulated non-convex optimization problem is separated into three subproblems, including communication scheduling optimization, power allocation optimization and UAV trajectory optimization, which can be solved by successive convex approximation (SCA). A joint iterative optimization algorithm of the three subproblems is put forward to get the optimal solution. Then, a fairness optimization problem is proposed to guarantee the fair communications for each vehicle. The numerical results reveal the excellent performance of the multi-UAV enabled mobile IoV by joint communication and trajectory optimization.

Internet of Things (IoT) is facing the shortage of spectrum resources due to the rapid growth of IoT terminals and big data services. Fifth generation (5G) network owns sufficient spectrum resources and supplies large data volume business, which can help to expand the communication resources of the IoT by combing IoT with 5G network. In this paper, a 5G-based IoT is designed to transfer both 5G and IoT information simultaneously. Two simultaneous transfer models including time switching model and power splitting model are proposed to carry out 5G and IoT communications using different time slots and power streams, respectively. For these two models, we have formulated joint optimization problem of allocation factors and node powers to maximize the 5G transmission rate while the IoT transmission rate and the total power are constrained. An alternative optimization problem is also proposed to maximize the IoT transmission rate while guaranteeing the minimal 5G transmission rate. A joint optimization algorithm based on the Lagrange dual optimization is proposed to obtain the solution to the optimization problems. An energy efficiency model is proposed to minimize the consumed total power of the IoT while keeping the minimal 5G and IoT transmission rates. Simulation results are given to evaluate the performance of our proposed models from diverse perspectives.