Changzhen Li

Path Loss Channel Model for Inland River Radio Propagation at 1.4 GHz

In this paper, a propagation path loss model for inland river is proposed by three improvements compared with the Round Earth Loss (REL) model for open-sea environment. Specifically, parameters optimization uses Okumura-Hata model in dB scale to replace the equation transformed from the free space loss in REL model; secondly, diffraction loss caused by the obstacles (e.g., large buildings, bridges, or some other facilities near the river bank) is also taken into account; mixed-path methodology as another improvement is used for Inland River (IR) model because the actual propagation environment between transmitter (TX) antenna and receiver (RX) antenna contains both land part and water part. The paper presents a set of 1.4 GHz measurements conducted along the Yangtze River in Wuhan. According to the comparison between path loss models and experimental results, IR model shows a good matching degree. After that, Root Mean Square Error (RMSE), Grey Relation Grade and Mean Absolute Percentage Error (GRG-MAPE), Pearson Correlation Coefficient, and Mean Absolute Percentage Error (PCC-MAPE) are employed to implement quantitative analysis. The results prove that IR model with consideration of mixed path and deterministic information is more accurate than other classic empirical propagation models for these scenarios.

Vehicle-to-Vehicle Radio Channel Characteristics for Congestion Scenario in Dense Urban Region at 5.9 GHz

This paper reports the results of a car-following measurement of the wireless propagation channel at 5.9 GHz on a seriously congested urban road in Wuhan, China. The small-scale amplitude-fading distribution was determined to be a Ricean distribution using the Akaike information criterion. This result shows that this car-following scenario can be regarded as a line-of-sight radio channel. Moreover, the statistical K-factor features follow a Gaussian distribution. According to the power delay profile and average power delay profile, we found that street buildings in this dense urban environment contributed to very strong reflection phenomena. The impact of a powerful reflection is analyzed through path loss, delay, and Doppler spreads in the channel statistical properties. In the frequency domain, we observe a U-shape delay-Doppler spectrum that proved that the dense urban scenario consists of scattering channels. All these results are summarized in tabular form that will be useful in the modeling of vehicle-to-vehicle wireless communication systems.

V2V radio channel properties at urban intersection and ramp on urban viaduct at 5.9 GHz

As a hotspot of wireless communication, vehicular communication is playing an important role in the smart city. This study focuses on vehicle-to-vehicle (V2V) radio channel characteristics at 5.9 GHz band based on measurement, under a ramp with soundproof wall on the urban viaduct and an urban intersection scenario, which are two similar but with slight difference propagation environments. Differences of V2V radio channel characteristics between two scenarios have been measured and analysed, in the view of best fit distribution of fades, power delay profile, delay spread, channel gain and Doppler spread. It is found that Weibull and Ricean distribution has a good match in non-line-of-sight and line-of-sight region, respectively. Transformation of different propagation mechanisms can increase or reduce the received power by 9-11 dB on average. Also, the power delay profile and root mean square delay spread are influenced by the different propagation conditions. Moreover, Ricean K-factors and Weibull shape parameters are modelled based on the least-square. The comparison of channel properties between these two classical urban scenarios is vital to the optimal design and performance of V2V communication system.

V2V Radio Channel Performance Based on Measurements in Ramp Scenarios at 5.9 GHz

This paper focuses on vehicle-to-vehicle (V2V) radio channel properties under ramp scenarios with different structures. Ramps are categorized according to different construction structures into: 1) viaduct ramp with soundproof walls in an urban area and 2) a general ramp without soundproof walls in a suburban region. Furthermore, considering whether the line of sight is available, the entire propagation process of the radio signal is divided into various propagation zones. Propagation characteristics, including the distribution of fading, fading depth (FD), level crossing rate, average fade duration, Root-Mean-Square (rms) delay spread, propagation path loss, and shadow fading, have been estimated and extracted. In particular, the radio channel properties in different types of ramp scenarios are compared and some interesting findings are obtained: 1) an abrupt fluctuation of the received signal level (RSL) in the urban viaduct ramp scenario indicates the nonignorable impact of soundproof walls on V2V radio channel and 2) continuous changes of RSL and different FD values in various propagation zones can be observed in suburban ramp scenarios. Furthermore, the statistical characteristics of RMS delay spread are fitted using a generalized extreme value model with a good fit. Furthermore, propagation path loss is modeled, demonstrating the difference of path loss values in the transition region owing to the impact of soundproof walls. Overall, the research results emphasize the significance of the V2V radio channel modeling under ramp scenarios.

GRG-MAPE and PCC-MAPE Based on Uncertainty-Mathematical Theory for Path-Loss Model Selection

In this contribution, Grey Relational Grade (GRG) and Pearson Correlation Coefficient (PCC) which are originally used for automation area are proposed in path-loss model selection of channel modeling. The commonly used method-Root Mean Square Error (RMSE) is employed as a comparison. Measurement data derived from inland river regions and open sea environment as well as many kinds of propagation path loss models (such as: Okumura-Hata model, Free-space model, REL model and ITU-R model) are for evaluation the performance of model selection algorithms. The results prove that optimal models which are chosen by GRG-MAPE and PCC-MAPE based on Uncertainty-Mathematical Theory have the better matching degree with measurement data. Consequently, both GRG-MAPE and PCC-MAPE are more accurate than RMSE.