Radio signal propagation modeling plays an important role in designing wireless communication systems. The propagation models are used to calculate the number and position of base stations and predict the radio coverage. Different models have been developed to predict radio propagation behavior for wireless communication systems in different operating environments. In this paper we shall limit our discussion to the latest achievements in radio propagation modeling related to tunnels. The main modeling approaches used for propagation in tunnels are reviewed, namely, numerical methods for solving Maxwell equations, waveguide or modal approach, ray tracing based methods and two-slope path loss modeling. They are discussed in terms of modeling complexity and required information on the environment including tunnel geometry and electric as well as magnetic properties of walls.

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Abstract-Wave propagation characteristics in curved tunnels are of importance for designing reliable communications in subway systems. This paper presents the extensive propagation measurements conducted in two typical types of subway tunnelstraditional arched "Type I" tunnel and modern arched "Type II" tunnel-with 300-and 500-m radii of curvature with different configurations-horizontal and vertical polarizations at 920,2400, and 5705 MHz, respectively. Based on the measurements, statistical metrics of propagation loss and shadow fading (path-loss exponent, shadow fading distribution, autocorrelation, and crosscorrelation) in all the measurement cases are extracted. Then, the large-scale fading characteristics in the curved subway tunnels are compared with the cases of road and railway tunnels, the other main rail traffic scenarios, and some "typical" scenarios to give a comprehensive insight into the propagation in various scenarios where the intelligent transportation systems are deployed. Moreover, for each of the large-scale fading parameters, extensive analysis and discussions are made to reflect the physical laws behind the observations. The quantitative results and findings are useful to realize intelligent transportation systems in the subway system.

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In the future railway services, wireless communication is the fundamental part and millimeter wave (mmWave) is foreseen to be a key enabler towards the smart railway. An accurate understanding of the propagation environment can assist designing both systems and railway infrastructures for better communication services. In this paper, the influence of typical objects to the mmWave propagation channel are analyzed for "Train-to-infrastructure" and "Intra-wagon" railway scenarios with various configurations. Propagation measurements are conducted in the mmWave band for the 12 most common railway materials. The corresponding electromagnetic parameters are obtained and a 3D ray tracing (RT) simulator is calibrated. The mean absolute error of the simulated S21 parameter is-53.5 dB, indicating that the calibrated RT can be used to generate the close-to-real mmWave channel for railway scenarios. Statistically consistent scenarios and deployments are generated, which enables drawing unbiased numerical results based on intensive RT simulations. The influence of typical objects and corresponding material compositions are then compared and significant objects are determined for each scenario. The results of this work not only imply how the propagation environment impacts on the propagation channel, but also makes suggestions to efficiently reconstruct railway environment models for an accurate RT based channel model. Moreover, the understanding of the influence of the environment at object and material levels will in turn guide the construction of railway infrastructure for better railway services.

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Network testing plays an important role in the iterative process of developing new communication protocols and algorithms.However, test environments have to keep up with the evolution of technology and require continuous update and redesign. In this paper, we propose COINS, a framework that can be used by wireless technology developers to enable continuous integration (CI) practices in their testbed infrastructure. As a proof-ofconcept, we provide a reference architecture and implementation of COINS for controlled testing of multi-technology 5G Machine Type Communication (MTC) networks. The implementation upgrades an existing wireless experimentation testbed with new software and hardware functionalities. It blends web service technology and operating system virtualization technologies with emerging Internet of Things technologies enabling CI for wireless networks. Moreover, we also extend an existing qualitative methodology for comparing similar frameworks and identify and discuss open challenges for wider use of CI practices in wireless technology development.

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