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To guarantee shipping safety, it is crucial to build a reliable wireless communication network. This study presents characteristic analysis of shipping wireless channel based on measurements. The authors conduct five channel measurements for two important water mobile communications, covering inland river and sea scenarios. Channel characteristics, e.g. power delay profile, amplitude distribution, delay spread and shadow fading, are extracted and compared for the two scenarios. It is found that the main difference between the them lies in more obstacles and scatterers in inland river propagation environment. The results show that more obstacles and scatterers can result in richer multipath effect and larger shadow fading decorrelation distance. A triple Gaussian mixture distribution (TGMD) is proposed to characterize the wireless channel with LOS, obstructed LOS and non-LOS situations in the practical propagation. To verify the effectiveness of TGMD, the goodness of fit between measurement and analysis results in terms of Rician K-factor, root mean square (RMS) delay spread and RMS Doppler spread is calculated. Furthermore, the cross-correlation among shadow fading, Rician K-factor and RMS delay spread are studied. Larger cross-correlation can be found in inland river and sea than vehicular communication due to the open propagation environment.

In this study, radio channel measurements were conducted in an urban inland river environment at 5.9GHz. The measurements consisted of both the line of sight (LOS) and non-line of sight (NLOS) cases. We estimate and model channel characteristics based on the measured data. For small-scale fading properties, best fit small-scale fading distribution is determined. Statistical models of the Ricean K-factors and Weibull shape parameters are provided. In addition, a distance-dependent Ricean K-factor model for the urban inland river environment is proposed. For the power delay profile (PDP), we perform cluster identification and obtain the cumulative distribution function (CDF) of the inter-cluster interval. A statistical model of the intracluster decay time constant is also presented, and an exponential decay model is applied for modeling the inter-cluster decay of the PDP. For delay spread and Doppler spread, the root mean square (RMS) delay spreads in the LOS case are compared with those in the NLOS case. Moreover, we estimate and analyze RMS Doppler spreads in both the LOS and NLOS cases. Finally, a bimodal Gaussian mixture distribution (BGMD) is employed to characterize the RMS delay spreads and RMS Doppler spreads. The BGMDs exhibit good matching levels.

In this study, vehicle-to-vehicle (V2V) radio channel measurements at 5.9 GHz were conducted on a suspension bridge and a beam bridge. Given that a different structure of the two bridges will result in different channel properties, the authors study small-scale and large-scale propagation characteristics for the bridge scenarios based on measurement data. By using Akaike's information criteria, the study determines optimal small-scale fading distribution. Owing to that Ricean distribution occupies the dominant position, Ricean K-factors in the two bridge scenarios are modelled separately and compared with each other. Afterwards, power delay profiles, Doppler power spectral densities, root-mean-square (RMS) delay spread and RMS Doppler spread are estimated and analysed in different cases. They employ bimodal Gaussian mixture distribution (BGMD) to model the RMS delay spreads and the RMS Doppler spreads. Fitting results of the BGMDs show good matching levels. For the large-scale propagation characteristics, path loss model for the beam bridge scenario is proposed based on the two-ray theory. On the other hand, path loss for the suspension bridge scenario is modelled by using an empirical function derived from WINNER II. Finally, grey relational grade–mean absolute percentage error, and RMS error criteria prove the effectiveness of the two proposed path loss models.

For a long time, the development of maritime communication has been restricted by the low data rate, high-latency and high cost of the current communication systems. The upgrade of new generation mobile communication technologies is attracting more and more attention to conduct a shore-based broadband mobile communication network with high-latency and high reliability to serve the maritime industries. This paper presents a solution by means of building a ship-to-infrastructure (S2I) and a ship-to-ship (S2S) wireless communication networks for an offshore region. We characterize the S2I and S2S channels at 5.9 GHz band based on the channel measurements in realistic environments. The channel characteristics, including power delay profile, delay spread, propagation path loss, are extracted and analyzed. In view of the difference between marine and terrestrial communications, we analyze the influencing factors of the offshore water, including effective reflection, divergence and shadowing from the water surface, and diffraction loss caused by the earth curvature. We also predict the power coverage range and the channel capacity for S2I and S2S wireless communications. Finally, the communication performance is evaluated according to the channel measurement and characterization analysis. The research results can be a reference for the construction of maritime communication networks.

Vehicular communication plays a vital role in intelligent transportation systems and smart cities. The huge data transmission and high mobility require a high-speed and stable wireless channel as a basis. This study presents a 5.9 GHz vehicle-to-vehicle (V2V) measurement, covering a complete inland lake bridge communication environment. Analysis of the channel characteristics is carried out according to three main propagation scenarios: ramp merging, a rear vehicle overtaking the front vehicle, and an urban scenario. Channel characteristics including the power delay profile, Doppler spectral density, amplitude distribution, and fading depth (FD) is extracted and analysed. An FD of ∼2.5 dB is determined in V2V communication. Furthermore, it is observed that, in addition to the impact from the ramp structure, metallic traffic signs, road lights, pedestrian bridges, and large trucks can also make significant contributions to vehicular communication. Moreover, a triple Gaussian mixture distribution is proposed to model the channel characterisation. The results demonstrate that the specific structure of the ramp will influence the channel performance more significantly than the general traffic road structure, which can provide a meaningful reference for the future research of V2V radio channels and is useful for the design and layout of vehicular communication systems.

Overtaking case is a common traffic situation, but it is likely to pose a threat to traffic safety. To ensure reliable communication, it is necessary to study the characteristics of wireless channel under overtaking cases. In this paper, we focus on Vehicle-to-Vehicle (V2V) radio channel characteristics based on measurements at 5.9GHz. Through research and analysis, we can present empirical results of propagation channels in four scenarios. Our main concern is the difference in channel characteristics between overtaking and non-overtaking case. We propose a method to divide overtaking cases and non-overtaking cases points based on small-scale fading distribution, and results show that the dividing point is about 11 meters between the measured vehicles. Judging by Akaike Information Criterion(AIC), Weibull distribution is best under overtaking cases, while it follows Ricean distribution under non-overtaking. Then, we prove that the result of the AIC decision is valid by the Kolmogorov-Smirnov test. Therefore, we further compare Weibull $\beta $ -factor and Ricean K-factor under two cases. The values of root-mean-square (RMS) delay spreads and average fade duration under overtaking cases are higher than those under non-overtaking, but RMS Doppler spreads and the level crossing rate are smaller than those under non-overtaking. The cross-correlation between RMS delay spread and Ricean K-factor is also calculated. The correlation value in OT case is higher than that in NOT case. The value of the correlation in the case of overtaking is higher than the case of non-overtaking. By comparing the above methods, it is proved that the dividing point between overtaking cases and non-overtaking cases is effective.

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.

This study focused on differences in vehicle-to-vehicle radio channel characteristics in the same region but different traffic density and speeds at 5.9 GHz (congestion and non-congestion). The continuous measurement campaign was conducted on a city expressway through the complex dense urban area in Wuhan, China. Small-scale channel characteristics including power delay profile, amplitude fading distribution, K-factor, delay spread and Doppler shift were obtained, respectively. Specifically, the cumulative distribution function of root mean square delay spreads and root mean square Doppler spreads in the non-congested scenario and congested scenario were all fitted well with Lognormal distribution. We also found out that different intensity of traffic and speed of vehicles have little effect on root mean square delay spreads, but have a big impact on root mean square Doppler spreads and level crossing rate. According to estimation outcomes, the V2V channel characteristics for urban areas in Chinese big city were different from the previous measured results under similar scenarios in Europe. Delay spread and level crossing rate in this study can provide significant references to design the wireless communication system for vehicle-to-vehicle channel.

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.

Rush hour network capacity enhancement is one of the most hard-to-solve problems in the field of network optimization. With the bust of data traffic requirement in cellular communication, 5G network will face this challenge in future. However, there is few effective solutions to this problem for 5G network optimization. In this paper, a novel solution based on hot spot floating prediction is proposed. Our solution consists of a traffic prediction method for hot spot floating trend estimation, and a semi-dynamic distributed unit (DU) and active antenna unit (AAU) mapping to fit the forecasted high traffic burst with proper DU-AAU mapping. The proposed solution could fit real network irregular gNB distribution. Simulation outcomes indicate that the hot spot floating prediction precision outperforms around 10% in normalized root mean squired error with the existing prediction methods, and our semi-dynamic DU-AAU mapping solution receives a 20% throughput gain on average compared with that without DU-AAU mapping network solution.

In recent vehicle-to-vehicle (V2V) radio channel measurements, we find that some severe fading channels are not always well characterized by traditional Rayleigh model. This paper focuses mainly on the worse than Rayleigh (WR) fading in V2V radio channel due to the impact of soundproof walls in urban viaduct scenarios. Rayleigh, Weibull and Nakagami-m distributions are used as reference models to describe the measurement data. It is observed that, for the WR fading channel, not only the received power is poor, but also the $\beta$-factor of Weibull or m-factor of Nakagami-m distribution is smaller than the critical value which is used to differentiate WR and Rayleigh fading. A good negative correlation between fading factor and root mean square delay spread is obtained as well. The larger level crossing rate and the smaller average fading duration are also extracted from measurement data in WR region. The findings of this paper can be used to enrich the study of vehicular communications under new urban traffic environments.

A radio channel measurement campaign with a maximum distance of 2.6 km was performed in China. In this paper, a detailed description of the channel measurement campaign including antenna setups, channel sounder configurations and other related info is given. The received signal level (RSL) is shown and compared with the Plain Earth Loss model (PEL), the ITU-R P.1546-2 model (ITU-R) and the Round Earth Loss model (REL). It can be found that the REL model matches the measured RSL best according to the values of the Root Mean Square Error (RMSE). The Power-delay profiles (PDPs) are demonstrated, from which the mean excess delay and the RMS delay spread are extracted. It can be found that the 90% of the mean excess delay and the RMS delay spread are within 4.3 ns and 113.3 ns according the corresponding Cumulative Distribution Functions (CDF), respectively. The Akaike Information Criterion (AIC) is used to estimated the best-fit amplitude distribution of the small-scale fading. The Two-Wave with Diffuse power (TWDP) model is found to be the best-fit model with more than 90% incident percentage in the whole route.

This paper finds the matched path loss models under three kinds of traffic flow conditions: high, medium and low traffic density based on the analysis of measured vehicle-to-vehicle (V2V) data at 5.9 GHz. We use the data of different traffic conditions in the Vehicular Ad Hoc Networks (VANETs) model to simulate the connectivity of VANETs. After simulating, the VANETs connectivity under different traffic flows based on the measured data is obtained as well as the obstruction considered effective communication coverage. The results show that the integrated VANETs connectivity model based on measured data can accurately reflect the V2V communication environment under real conditions.

This paper analyzes the path loss at 5.9 GHz in the forest city environment. This article introduces 3 modeling methods and gives the illustration for the path loss which is indicated in the forest city environment. Firstly, the field test of the forest city environment at 5.9 GHz is carried out, we gained a rich supply of data which would normally be inaccessible. The following steps demonstrate these 3 models (Free Space model, One Slope model and ITU-R P.833model) and calculated the differences between the fitted data and the measurement data. Meanwhile, the most crucial step is to find the most appropriate path loss model. Here the three algorithms are used to combine and analyze the optimal path loss model. The simulation and experimental results indicate that the three algorithms have the better performance and accuracy. The results show that the Free Space Model and the ITU-R-P.833 model cannot be directly used for path loss modeling due to the big difference between the calculated data and the measured data in the forest city environment. The One Slope Model can preferably solve the path loss modeling problem in the forest city environment.

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.

The investigation in this paper focuses on the impact of soundproof walls on vehicle-to-vehicle (V2V) communication in urban viaduct scenarios. Two measurement campaigns are conducted at 5.9 GHz band in the on-ramp and off-ramp scenarios in Wuhan, China. Line-of-sight (LOS) and non-line-of-sight (NLOS) regions caused by soundproof walls and their switch are emphasized. Akaike information criteria (AIC) is utilized to select the distribution that can best fit the amplitude fading. The results show Weibull distribution offers better fit in NLOS case and Ricean distribution is validated the best fit in LOS region. We observe that comparing to root mean square (RMS) delay spreads in NLOS region caused by soundproof walls, many strong multipath components (MPCs) in LOS cases will contribute to large RMS delay spreads. It is noted that there is fluctuation of fading depth between NLOS and LOS region. Our analysis illustrates that the reduction caused by soundproof walls cannot be neglected in V2V radio communication.

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.

Vehicular Ad Hoc Networks (VANETs) is one of the most important applications in the fifth generation. The stable connection between the vehicles can guarantee the construction of VANETs. This study 5 stresses on the connectivity probability analysis under different vehicle density. Firstly, this study investigates the matched path loss models under four kinds of traffic flow conditions: high, medium traffic density in urban areas and two low traffic density in suburb areas based on the analysis of measured vehicle-to-vehicle (V2V) data at 5.9 GHz. Secondly, based on the measured path loss and small-scale fading data, we build a VANETs model considering single-hop link connectivity and signal blocking phenomenon in multi-hop link. Finally, the VANETs connectivity probability under different traffic flows is obtained as well as the obstruction considered effective communication coverage. The results show that the integrated VANETs connectivity model based on measured data can accurately reflect the V2V communication environment under real conditions.

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.

This study focuses on the statistical properties of the Power Delay Profile (PDP) and path loss results at 5.9 GHz for the indoor environment. The measurement campaign was conducted by using a 5.9 GHz channel sounder to extract the characterization of the indoor radio channel. The successive PDP of our measurement data is presented and statistical properties of mean delay and RMS delay spread is investigated by using dedicated signal-processing methods. The statistical results show that 90% mean delay and RMS delay spread are within 165 ns and 58 ns, respectively. In addition, by comparing the measurement data with the simulation results of four classic indoor channel models, the One-Slope Model has been proven to be more accurate than the Partitioned Model, ITU-R Recommendation P.1238-1 Model(ITU-R) and Plain Earth Model.

In order to find the most appropriate one from various propagation path loss models, model selection is a crucial step in channel modeling. By treating it as a “data matching problem”, a method combined Grey Relational Grade (GRG) and Mean Absolute Percentage Error (MAPE) is proposed after analyzing a number of widely used path loss models. At the next stage, measurement data that derived from urban and suburban environments at 1.4 GHz are implemented for simulation and results comparison. The outcomes demonstrate that Okumura-Hata models are relatively better than others within these two environments. Due to the result obtained at the end of this paper, the GRG-MAPE method based on Grey System Theory can be determined as an effective methodology.