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

Shui, Yishui; Li, Fang; Yu, Jiguo; Chen, Wei; Li, Changzhen; Yang, Kun; Chang, Fuxing

doi:10.1155/2018/1751869

Cited by 12 publications

(7 citation statements)

References 40 publications

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“…The virtually identical RMSE values recorded by all the calibrated models of the three examples considered in this paper very clearly support the uniqueness property of the QMM pathloss model calibration algorithm as defined in [9], [15]. It has however been suggested, [6], [13], [14], that a better assessment of pathloss model prediction performance is offered by the Grey Relational Grade Mean Absolute Percentage Error, GRG-MAPE. Because [13] and [14] presented the generic GRG-MAPE algorithm without specializing it to the case of pathloss prediction, it is helpful to provide details of the algorithm's use for the results presented here.…”

Section: Fig 3 Comparison Of Pathloss Predicted By Calibrated Modelssupporting

confidence: 69%

“…The first step in the GRG-MAPE algorithm is that of 'normalization', for which the quantities are defined. Next, the 'deviation sequence' is determined for each of the measurement and prediction data according to from which the Grey Relational Coefficient is obtained as Equation (31) expresses the relationship between measured and predicted pathloss, and the 'distinguishing' or 'identification coefficient' symbolized by ' ', is prescribed as [13], [14],…”

Section: The Grey Relational Grade Mape Algorithmmentioning

confidence: 99%

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On the Uniqueness of the Quasi-Moment-Method Solution to the Pathloss Model Calibration Problem

Muhammed

Ayorinde

Okewole

et al. 2022

JCIS

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Investigations in this paper focus on establishing the uniqueness properties of the Quasi-Moment-Method (QMM) solution to the problem of calibrating nominal radiowave propagation pathloss prediction models. Nominal (basic) prediction models utilized for the investigations, were first subjected to QMM calibrations with measurements from three different propagation scenarios. Then, the nominal models were recast in forms suitable for Singular Value Decomposition (SVD) calibration before being calibrated with both the SVD and QMM algorithms. The prediction performances of the calibrated models as evaluated in terms of Root Mean Square Prediction Error (RMSE), Mean Prediction Error (MPE), and Grey Relational Grade-Mean Absolute Percentage Error (GRG-MAPE) very clearly indicate that the uniqueness of QMMcalibrations of basic pathloss models is more readily observable, when the basic models are recast in forms specific to SVD calibration. In the representative case of calibration with indoorto-outdoor measurements, RMSE values were recorded for QMM-calibrated nominal models as 5.2639dB for the ECC33 model, and 5.3218dB for the other nominal models.Corresponding metrics for the alternative (rearranged) nominal models emerged as 5.2663dB for the ECC33 model and 5.2591dB for the other models. A similar general trend featured in the GRG-MAPE metrics, which for both SVD and QMM calibrations of all the alternative models, was recorded as 0.9131, but differed slightly (between 0.9138 and 0.9196) for the QMM calibration of the nominal models. The slight differences between these metrics (due to computational round-off approximations) confirm that when the components of basic models are linearly independent, the QMM solution is unique. Planning for wireless communications network deployment may consequently select any basic model of choice for QMM-calibration, and hence, identify relative contributions to pathloss by the model's component parts.

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Section: Fig 3 Comparison Of Pathloss Predicted By Calibrated Modelssupporting

confidence: 69%

Section: The Grey Relational Grade Mape Algorithmmentioning

confidence: 99%

On the Uniqueness of the Quasi-Moment-Method Solution to the Pathloss Model Calibration Problem

Muhammed

Ayorinde

Okewole

et al. 2022

JCIS

View full text Add to dashboard Cite

show abstract

“…In this section, several statistical characteristics of the proposed channel model are simulated and analyzed, including the spatial ACF, temporal ACF, and Doppler PSD. Based on measurement data in [28,52] and measurement methods in [53][54][55], the simulation parameters at the initial time are set and listed in Table 2. As for the scenario with slope scenario 2 is chosen in simulations.…”

Section: Simulation Results and Analysismentioning

confidence: 99%

Analytical Nonstationary 3D MIMO Channel Model for Vehicle-to-Vehicle Communication on Slope

Liu

Wei

Chen

2021

International Journal of Antennas and Propagation

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Vehicle-to-vehicle communication plays a strong role in modern wireless communication systems, appropriate channel models are of great importance in future research, and propagation environment with slope is one special kind. In this study, a novel three-dimensional nonstationary multiple-input multiple-output channel model for the sub-6 GHz band is proposed. This model is a regular-shaped multicluster geometry-based analytical model, and it combines the line-of-sight component and multicluster scattering rays as the nonline-of-sight components. Each cluster of scatterers represents the influence of different moving vehicles on or near a slope, and scatterers are, respectively, distributed within two spheres around the transmitter and the receiver. In this model, it is considered that the azimuth and elevation angles of departure and arrival are jointly distributed and conform to the von Mises–Fisher distribution, which can easily control the range and concentration of the scatterers within spheres to mimic the real-world situation well. Moreover, the impulse response and the autocorrelation function of the corresponding channel is derived and proposed; then, the Doppler power spectrum density of the channel is simulated and analyzed. In addition, the nonstationary characteristics of the presented channel model are observed through simulations. Finally, the simulation results are compared with measurement data in order to validate the utility of the proposed model.

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“…The employed channel sounder was also used in several other indoor and outdoor radio measurement campaigns (see, e.g., [25,51,52]) and has shown a very good performance in capturing the non-stationary properties of channels involving moving scatterers.…”

Section: Measurement Methodologymentioning

confidence: 99%

Time-Frequency Characteristics of In-Home Radio Channels Influenced by Activities of the Home Occupant

Borhani

Pätzold

Yang³

2019

Sensors

Self Cite

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While aging is a serious global concern, in-home healthcare monitoring solutions are limited to context-aware systems and wearable sensors, which may easily be forgotten or ignored for privacy and comfort reasons. An emerging non-wearable fall detection approach is based on processing radio waves reflected off the body, who has no active interaction with the system. This paper reports on an indoor radio channel measurement campaign at 5.9 GHz, which has been conducted to study the impact of fall incidents and some daily life activities on the temporal and spectral properties of the indoor channel under both line-of-sight (LOS) and obstructed-LOS (OLOS) propagation conditions. The time-frequency characteristic of the channel has been thoroughly investigated by spectrogram analysis. Studying the instantaneous Doppler characteristics shows that the Doppler spread ignores small variations of the channel (especially under OLOS conditions), but highlights coarse ones caused by falls. The channel properties studied in this paper can be considered to be new useful metrics for the design of reliable fall detection algorithms. We share all measured data files with the community through Code Ocean. The data can be used for validating a new class of channel models aiming at the design of smart activity recognition systems via a software-based approach.

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

Cited by 12 publications

References 40 publications

On the Uniqueness of the Quasi-Moment-Method Solution to the Pathloss Model Calibration Problem

On the Uniqueness of the Quasi-Moment-Method Solution to the Pathloss Model Calibration Problem

Analytical Nonstationary 3D MIMO Channel Model for Vehicle-to-Vehicle Communication on Slope

Time-Frequency Characteristics of In-Home Radio Channels Influenced by Activities of the Home Occupant

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