# SDR-Based 28 GHz mmWave Channel Modeling of Railway Marshaling Yard
### Related Works
In the article, by comparing the path loss between simulation and measurement, the permittivity and loss tangent of concrete, which is the construction material of viaducts, are calibrated in the ray tracer. In [24], based on the wideband measurements conducted in the tunnel scenario by using the \"mobile hotspot network\" system, 3D ray tracing (RT) is calibrated and validated to explore more channel characteristics in different HSR scenarios. In [25], since the measurement of a mmWave channel is deficient for high mobility, the proposed channel model is developed using a ray-tracing (RT) simulator that is validated with the channel measurements performed in the HST scenario at 93.2 GHz. Ref. [26] focuses on the analysis of propagation characteristics for train-ground communication systems in tunnel scenarios at both low-frequency and mmWave bands, based on ray-tracing (RT) simulation, and the material parameters in the RT simulation are calibrated by measurement data collected in realistic tunnel environments. As for the research object, except for channel parameters such as power delay profiles (PDP), path loss, Rician K-factor, root-mean-square (RMS) delay spread, azimuth spread of arrival, and azimuth spread of departure, reconfigurable intelligent surface (RIS), beamforming, Doppler shift, energy efficient, user association, resource allocation and computation offloading, the influence of meteorological attenuation, sensing, minimal distance between base stations, as well as mmWave network architectures for railway have all been involved. In [27], the authors proposed a RIS-assisted scheduling scheme for scheduling interrupt flows and improving quality of service (QoS), and in the proposed scheme, an RIS is deployed between the BS and multiple mobile relays (MRs). In [28], multiple beams with different beamwidths are formed by the base station (BS) simultaneously to improve the system capacity, and the mobile relays (MRs) are provided with the ability to adjust the receiver (RX) beams automatically to enhance the received signal-to-noise ratio (SNR). In [29], control information and user information are transmitted through the high-frequency micro base station (BS) and the low-frequency macro BS, respectively, and an optimized beam width and power allocation scheme is proposed, which is combined with mobile relay (MR) technology to utilize the architecture of large-scale antenna beamforming. In [30], dynamic and fixed beamforming is evaluated based on the generalized model and the measured data, and the results show that the average throughput of dynamic beamforming is only 4% higher than that of fixed beamforming in the HSR tunnel, but 21% higher in the train station when severe beam misalignment is present. In [31], the authors proposed a new Doppler shift estimator for mmWave communication systems on HSRs: an equally-divided structure-based estimator (ESBE) that divides the effective orthogonal frequency-division multiplexing (OFDM) symbol into multiple equal fragments. In [32], the modeling of the Doppler effect for mmWave in HSR communications is conducted, and data-aided Doppler estimation and compensation algorithms are designed based on the new model. In [33], the authors proposed a new machine learning-based Doppler shift estimator (MLDSE), which estimates the Doppler shift by using the reference signal received power (RSRP) values measured by the mobile receiver at all times.