A Non-WSSUS Channel Simulator for V2X Communication Systems

Jaime-Rodriguez, J. J.; Gomez-Vega, Carlos A.; Gutiérrez, Carlos; Rivera, Juan Pablo; Campos-Delgado, Daniel U.; Velázquez, Ramiro

doi:10.3390/electronics9081190

Cited by 8 publications

(13 citation statements)

References 57 publications

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Section: Single Ring Geometrical Scattering Channel Modelmentioning

confidence: 99%

“…Considering that the vehicular channel does not fulfill the WSSUS condition, the channel representation proposed in [14][15][16] is used in this work. The channel introduced in [14][15][16] is a statistical geometrical model for mobile-to-mobile systems. The scenario has a mobile transmitter with variable velocity and acceleration, as well as a receptor moving at a variable velocity and acceleration.…”

Section: Single Ring Geometrical Scattering Channel Modelmentioning

confidence: 99%

“…Therefore, the model depicts a realistic representation of a mobile to mobile system scenario. Furthermore, the model proposed in [14][15][16] is physically complete but mathematically simple in comparison with other non-WSSUS geometry-based statistical channel models.…”

Section: Single Ring Geometrical Scattering Channel Modelmentioning

confidence: 99%

“…In the model presented in Figure 5, V T corresponds to the vector describing the velocity of the transmitter, V R is the vector describing the velocity of the receptor, a T represents the vector describing the acceleration of the transmitter, a R denotes the vector describing the acceleration of the receptor, d comes to be the radius of the ring, and l-th > IO corresponds to the l-th interfering object. As a result, the channel transfer function is given as follows [14][15][16],…”

Section: Single Ring Geometrical Scattering Channel Modelmentioning

confidence: 99%

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Semi-Supervised Extreme Learning Machine Channel Estimator and Equalizer for Vehicle to Vehicle Communications

et al. 2021

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Wireless vehicular communications are a promising technology. Most applications related to vehicular communications aim to improve road safety and have special requirements concerning latency and reliability. The traditional channel estimation techniques used in the IEEE 802.11 standard do not properly perform over vehicular channels. This is because vehicular communications are subject to non-stationary, time-varying, frequency-selective wireless channels. Therefore, the main goal of this work is the introduction of a new channel estimation and equalization technique based on a Semi-supervised Extreme Learning Machine (SS-ELM) in order to address the harsh characteristics of the vehicular channel and improve the performance of the communication link. The performance of the proposed technique is compared with traditional estimators, as well as state-of-the-art machine-learning-based algorithms over an urban scenario setup in terms of bit error rate. The proposed SS-ELM scheme outperformed the extreme learning machine and the fully complex extreme learning machine algorithms for the evaluated scenarios. Compared to traditional techniques, the proposed SS-ELM scheme has a very similar performance. It is also observed that, although the SS-ELM scheme requires the largest operation time among the evaluated techniques, its execution time is still far away from the latency requirements specified by the standard for safety applications.

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Section: Single Ring Geometrical Scattering Channel Modelmentioning

confidence: 99%

Section: Single Ring Geometrical Scattering Channel Modelmentioning

confidence: 99%

Section: Single Ring Geometrical Scattering Channel Modelmentioning

confidence: 99%

Section: Single Ring Geometrical Scattering Channel Modelmentioning

confidence: 99%

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Semi-Supervised Extreme Learning Machine Channel Estimator and Equalizer for Vehicle to Vehicle Communications

et al. 2021

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“…Regarding the propagation environment, some assumptions are made on the distributions of interfering objects for particular scenarios [36]. Conventional approaches consider isotropic or nonisotropic distributions of interfering objects around the vehicles [21]. For more realistic scenarios, ray-tracing models provide accurate representations of the propagation environments by considering the exact positions and electromagnetic properties of the interfering objects [37].…”

Section: Introductionmentioning

confidence: 99%

Doppler Spectrum Measurement Platform for Narrowband V2V Channels

et al. 2022

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This paper describes the implementation of a Doppler spectrum measurement platform for narrowband frequency-dispersive vehicle-to-vehicle (V2V) channels. The platform is based on a continuous-wave (CW) channel sounding approach widely used for path-loss and large-scale fading measurements, but whose effectiveness to measure the Doppler spectrum of V2V channels is not equally known. This channel sounding method is implemented using general-purpose hardware in a configuration that is easy to replicate and that enables a partial characterization of frequency-dispersive V2V channels at a fraction of the cost of a dedicated channel sounder. The platform was assessed in a series of field experiments that collected empirical data of the instantaneous Doppler spectrum, the mean Doppler shift, the Doppler spread, the path-loss profile, and the large-scale fading distribution of V2V channels under realistic driving conditions. These experiments were conducted in a highway scenario near San Luis Potosí, México, at two different carrier frequencies, one at 760 MHz and the other at 2,500 MHz. The transmitting and receiving vehicles were moving in the same direction at varying speeds, ranging from 20 to 130 km/h and dictated by the unpredictable traffic conditions. The obtained results demonstrate that the presented measurement platform enables the spectral characterization of narrowband V2V channels and the identification of their Doppler signatures in relevant road-safety scenarios, such as those involving overtaking maneuvers and rapid vehicles approaching the transmitter and receiver in the opposite direction.INDEX TERMS Doppler shift, Doppler spectrum, fading channels, radio-frequency propagation, vehicular communications.

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