In this paper, a geometrically-based single-bounce multiple-input-multiple-output (GBSB- MIMO) channel model is proposed for the long term evolution-metro (LTE-M) system in tunnel scenarios. The periodic slots of leaky coaxial cable (LCX) are equivalent to a series of magnetic dipoles. Based on the electric field distribution of the LCX, the theoretical model for line-of-sight (LOS) and non-line-of-sight (NLOS) propagation paths in the tunnel environment are derived. The measurement and simulation results are compared in terms of condition number (CN), channel capacity, and channel correlation function (CF), which verifies the feasibility and rationality of the new proposed model. The simulation results demonstrate, under such circumstances when the Ricean K-factor is smaller, the LCX spacing has a little influence on the channel capacity and CN due to a large number of the NLOS propagation paths in the tunnel, while as Ricean K-factor increases, the LCX spacing has more influence on the channel capacity and CN. By comparison of the measurement and simulation results, it was found that the capacity and CN of the LCX-MIMO is better than the dipole MIMO with different Ricean K-factor values, and under such conditions when the spacing between LCXs and the dipole antennas is increased. Therefore, this paper delivers an optimal system design for channel capacity based on the LCX deployment in the tunnel environment.

The Industrial Internet of Things (IIoT) is a typical future application for the mobile networks. Unmanned aerial vehicle (UAV) has attracted a great deal of interest in relay assisted wireless communication systems due to its benefits of high mobility, rapid deployment and high probability of Line-of-Sight (LoS) transmissions. This article proposes the 3-D geometry-based nonstationary channel models for wireless communication underlaying UAV-based relay assisted IIoT networks in the subterahertz (sub-THz) band. In order to accurately describe the propagation characteristics of the UAV-based wireless channels in the sub-THz band, the propagation gain and atmospheric absorption gain in free space, LoS path, single UAV-based relay and double UAV-based relay propagation paths are considered in the proposed channel models. The channel impulse response (CIR) expressions of different propagation paths are derived, respectively. The statistical properties of the channel models, including path loss, channel capacity, temporal auto-correlation function (T-ACF), and Doppler power spectral density (DPSD) at 140-GHz band, are investigated and analysed, with a performance comparison at 60-GHz band.

Network function virtualization (NFV) offers a flexible and effective means to utilize heterogeneous resources for space-air–ground integrated networks (SAGINs), enabling seamless connectivity for data transmission over large spans. Converging the cloud and edge computing capabilities, SAGINs have the potential to further provision service function chains (SFCs) with various Internet applications. This is driving the need for efficient schemes of the cloud- or edge-based services in SAGINs. In this article, we propose a novel SAGIN architecture based on the cloud-serving and edge-processing collaboration. The cloud-based services are provisioned by the selected ground data centers (DCs), in which the traffic is processed by the virtual network function (VNF) hosted in the edge nodes and DCs. In such an architecture, the edge nodes enable flexible SFC provisioning solutions while DCs offer a variety of cloud-oriented network services. In addition, we apply anycast to further improve the agility of SFC provisioning. From these perspectives, we investigate the cloud-serving and edge-processing SFC provisioning problem leveraging anycast, concerning DC assignment, edge and VNF placement, SFC mapping, and delay constraints simultaneously. The joint problem is formulated by a mixed integer linear program (MILP) model to jointly minimize the communication and computation costs subject to their tradeoff. A decomposition approach is further developed for the sake of scalability. Results from numerical simulations show that the proposed approach can reduce overall costs by up to 32.99%.

This letter studies the effect of ultra-high mobility on the performance of multiple-input multiple-output (MIMO) wireless communication system in tunnel scenarios. It is found that the Doppler frequency shift generated by the ultra-high mobility reduces the correlation coefficient. Importantly, it is observed that there exists a key inflection point distance in the ultra-high speed tunnel scene. When this distance is exceeded, the channel correlation of MIMO can be significantly reduced. Moreover, it is perceived that the inflection point distance is relatively stable and is less affected by the communication frequency. On this basis, we propose a high-quality communication area with low MIMO channel correlation. For the ultra-high speed of 720km/h, the inflection distance is about 95m, and the reduction of MIMO channel correlation at 3.5GHz and 28GHz can reach up to 52.7% and 41.2%, respectively. The findings are extremely useful for the applications of the mobile MIMO communication system in tunnel and railway scenarios.

Due to the limited space in the tunnel environment, multiple-input multiple-output (MIMO) systems with double-port fed leaky coaxial cables (LCXs) can not only reduce the number of LCXs, but also improve the channel capacity. Based on the geometry based on single bonce (GBSB) and electromagnetic field radiation theory of LCX, a MIMO channel model with double–port fed LCX in a tunnel scenario is proposed in this paper. The channel impulse response (CIR) is derived, and verified with measurement results in terms of channel capacity. The distribution of channel capacity of single double-port fed LCX under different LCX lengths in the tunnel scenarios has also been analyzed in this work, and the distribution of channel capacity for the LCX–MIMO system with long LCX is predicted. The results show that the single double-port fed LCX–MIMO system outperforms the dipole antenna MIMO system with respect to channel capacity in the considered tunnel scenarios.

The number of real-time dynamic satellite observation missions has been rapidly increasing recently, while little attention has been paid to the dynamic mission-scheduling problem. It is crucial to reduce perturbations to the initial scheduling plan for the dynamic mission-scheduling as the perturbations have a significant impact on the stability of the Earth observation satellites (EOSs). In this paper, we focus on the EOS dynamic mission-scheduling problem, where the observation profit and perturbation are considered simultaneously. A multi-objective dynamic mission-scheduling mathematical model is first formulated. Then, we propose a multi-objective dynamic mission-scheduling algorithm (MODMSA) based on the improved Strength Pareto Evolutionary Algorithm (SPEA2). In the MODMSA, a novel two-stage individual representation, a minimum perturbation random initialization, multi-point crossover, and greedy mutation are designed to expand the search scope and improve the search efficiency. In addition, a profit-oriented local search algorithm is introduced into the SPEA2 to improve the convergence speed. Furthermore, an adaptive perturbation control strategy is adopted to improve the diversity of non−dominated solutions. Extensive experiments are conducted to evaluate the performance of the MODMSA. The simulation results show that the MODMSA outperforms other comparison algorithms in terms of solution quality and diversity, which demonstrates that the MODMSA is promising for practical EOS systems.