Wireless Communication in Tunnels

Connected and autonomous vehicles systems can provide a safe and convenient transportation solution through wireless communication between vehicles and roadside communication infrastructure. The vehicle's ability to establish its location plays an important role in such systems. This article presents an efficient localisation framework by combining physics‐based wireless propagation models and fingerprint localisation algorithms. To that end, a parabolic wave equation (PWE)‐based wireless channel simulator is utilised to obtain the direction of arrival (DOA) values that construct the fingerprint dataset. A detailed procedure on how to obtain the DOA information using PWE, as well as analysis and guidelines on the selection of the key parameters of the localisation framework are provided. Numerical results are compared with theoretical data in terms of accuracy, and the selection of parameters during the localisation process is investigated in actual road tunnel cases. Besides, various numbers of wireless access points and schemes of fingerprinting algorithms have been studied, showing the capability of the proposed approach to be employed for the pre‐design of wireless communication systems.

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“… The geometry of the Massif Central tunnel in south‐central France. (a) On‐site image [22]. (b) Cross‐section geometry.…”

Section: Application: Massif Central Tunnelmentioning

confidence: 99%

Physics‐based wave propagation model assisted vehicle localisation in tunnels

Qin

Zhang

2023

IET Microwaves Antenna & Prop

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“…In addition, Figure 3 shows the geometrical representation of RSBST V2V scattering model. As illustrated in Figure 3, we employ a Cartesian coordinate approach to investigate the distribution of random scatterers S pqr on the tunnel sidewalls and ceiling for ∀m, 1 ≤ p ≤ P, ∀q, 1 ≤ q ≤ Q, and ∀r, 1 ≤ r ≤ R. On the rectangle tunnel sidewalls and ceiling, we suppose that the infinite number of scattering components (i:e:, P, Q, R⟶∞) is distributed randomly [36].…”

Section: Analysis Of Geometric Rsbst Modelmentioning

confidence: 99%

Statistical Characteristics of 3D MIMO Channel Model for Vehicle-to-Vehicle Communications

Saleem

Khan

et al. 2022

Wireless Communications and Mobile Computing

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Spatial and temporal characteristics of the propagation channel have a significant influence on multiantenna method applicability for fifth-generation- (5G-) enabled Internet of Things (IoT). In this paper, the statistical characteristics of a novel three-dimensional (3D) geometric-based stochastic model for next-generation vehicle-to-vehicle (V2V) multiple-input multiple-output (MIMO) communications under the nonisotropic scattering environment are investigated. In both line-of-sight (LoS) and non-line-of-sight (NLoS) conditions, the proposed model investigates the spatial, frequency, and temporal domain statistical distribution of multipath received signals by using the time-variant transfer function for indoor environments. The probability density function (PDF) of separation distance between the transceiver antennas, angle-of-arrival (AoA), and angle-of-departure (AoD) in the azimuth and elevation planes is derived by using closed-form expressions. For the space, time, and frequency correlation function (STF-CF), a precise analytical expression is derived based on MIMO antenna system. We further determine the effects of several model parameters on the V2V channel performance, such as tunnel width, antenna array spacing, Ricean K -factor, and moving velocity. The statistical characteristics of the MIMO channel model are validated by simulation results, confirming the flexibility and effectiveness of our proposed model in the tunnel scenario.

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“…It is noteworthy that the code can been extended to accommodate for the investigated scenario and target application. As an example, it was validated in an older work with the characteristics of MIMO radio channels measured in tunnels at wireless mobile frequencies (i.e., 900 MHz) with various polarization states (Molina‐Garcia‐Pardo et al., 2012) or more recently at 60 GHz in an indoor scenario (Martinez‐Ingles et al., 2014). These characteristics include the relative received power, delay spread, and emitter/receiver angular spreads.…”

Section: D Ray‐tracing Tool and Scenariomentioning

confidence: 99%

Evaluation of an Antenna Selection Strategy for Reduced Massive MIMO Complexity

et al. 2021

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Mobile connectivity has become not only essential but a necessity for many network users. The number of mobile subscribers is growing rapidly and the demand for more bandwidth and higher data rates continues to increase (CISCO Global Cloud Index (GCI), 2018). To support this demand, 5G systems promise to deliver a major paradigm shift with respect to previous wireless communication systems using new technologies such as Massive MIMO (Andrews et al., 2014;Larsson et al., 2014). MIMO technology has been a breakthrough for wireless communication systems in terms of increased reliability and higher data throughput and it is imagined that more benefits could be harvested from scaled-up versions (Rusek et al., 2013).In Marzetta (2010), the author introduced the concept of Massive MIMO and demonstrated that an excessive number of radiating elements (M) at the transmitting side paired with a number of active users (K) permits the use of simple linear precoders and increases the overall spectrum efficiency. In Björnson et al. (2016), Lu et al. (2014), Ngo et al. (2013), Rusek et al. (2013, an overview of Massive MIMO technology is thoroughly presented alongside its main advantages and challenges. Massive MIMO systems can eliminate the effects of small-scale fading and uncorrelated noise thus reducing intercell interference. As a result, the corresponding channel is formed by a set of nearly perfect orthogonal subchannels (Narasimhan & Chockalingam, 2014). Even though MIMO systems are already operating worldwide, largescale MIMO has only been tested in labs (

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Wireless Communication in Tunnels

Cited by 8 publications

References 20 publications

Physics‐based wave propagation model assisted vehicle localisation in tunnels

Physics‐based wave propagation model assisted vehicle localisation in tunnels

Statistical Characteristics of 3D MIMO Channel Model for Vehicle-to-Vehicle Communications

Evaluation of an Antenna Selection Strategy for Reduced Massive MIMO Complexity

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