Channel Models for Performance Evaluation of Wireless Systems in Railway Environments

Berbineau, Marion; Behaegel, Romain; García-Loygorri, Juan Moreno; Torrego, Raúl; D’Errico, Raffaele; Sabra, Ali; Yan, Ying; Soler, José

doi:10.1109/access.2021.3066112

Cited by 15 publications

(10 citation statements)

References 73 publications

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“…This approach is straightforward and practical, particularly when combined with the estimation of the SNR (Signal-to-Noise Ratio) in the equalization algorithm MMSE (Minimum Mean Square Error) [3,4]. More advanced equalization techniques can be found in the literature [5][6][7], but the most popular methods rely on prior estimation of channel characteristics in the frequency or time domain [8][9][10][11].…”

Section: Motivationmentioning

confidence: 99%

“…Equation (1) does not rely on specific details about the physical characteristics of the channel. Previous studies [10,21,22] have shown that actual transmission channels can be accurately modeled as short FIR (Finite Impulse Response) filters, where the coefficients represent the different paths through which the signal propagates. Based on our measurements and information collected from the literature, it was determined that six paths adequately represent the channel.…”

Section: Problem Statementmentioning

confidence: 99%

“…The selectivity of the sensing matrix primarily deteriorates in neighboring elements. Despite the apparent conclusion from Equation (10), we can still utilize the provided matrix by considering the following guidelines: (1) The sparse algorithm cannot distinguish between paths that are closer than the system's sampling period, and (2) if the search algorithm detects paths that are closer than the sampling period, they may be the result of the blurring of the same path.…”

Section: Sensing Matrixmentioning

confidence: 99%

See 2 more Smart Citations

Equalizer Parameters’ Adjustment Based on an Oversampled Channel Model for OFDM Modulation Systems

Kucharczyk,

Dziwoki,

Izydorczyk

et al. 2024

Electronics

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A physical model of a wireless transmission channel in the time domain usually consists of the main propagation path and only a few reflections. The reasonable assumptions made about the channel model can improve its parameters’ estimation by a greedy OFDM (Orthogonal Frequency Division Multiplexing) equalizer. The equalizer works flawlessly if delays between propagation paths are in the sampling grid. Otherwise, the channel impulse response loses its compressible characteristic and the number of coefficients to find increases. It is possible to get back to the simple channel model by data oversampling. The paper describes how the above idea helps the OMP (Orthogonal Matching Pursuit) algorithm estimate channel coefficients. The authors analyze the oversampling algorithm on the one hand to assess the influence of filtering function and signal resolution on the quality of the channel impulse response reconstruction. On the other hand, the abilities of the OMP algorithm are analyzed to distinguish components of the oversampled signal. Based on these analyses, we proposed modifications to the compressible channel’s impulse response reconstruction algorithm to minimize the number of transmission errors. A distinction was made between the filters used in the OMP search and channel reconstruction stages before calculating equalizer coefficients. Additionally, the results of the search stage were considered as elements within the groups.

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Section: Motivationmentioning

confidence: 99%

Section: Problem Statementmentioning

confidence: 99%

Section: Sensing Matrixmentioning

confidence: 99%

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Equalizer Parameters’ Adjustment Based on an Oversampled Channel Model for OFDM Modulation Systems

Kucharczyk,

Dziwoki,

Izydorczyk

et al. 2024

Electronics

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“…Since the bearers are independent they need to be investigated independently. For instance, channel investigations on 3GPP technologies have been performed by [7] and general train channel emulation has been investigated by [8]. Both traditional and SDN devices can be used in the onboard and trackside networks (either as part of the ACS like a virtual switch or a physical switch within the LAN).…”

Section: Acs Architecturementioning

confidence: 99%

Next-Generation Connectivity in A Heterogenous Railway World

et al. 2023

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Global System for Mobile communication -Railway (GSM-R) is widely used for operational communications between train and signaler. However, there is a need to define a successor that addresses: obsolescence, radio spectrum demand and the enabling of a range of emerging digital applications such as radiobased signaling and Automatic Train Control (ATC). Therefore, the International Union of Railways (UIC) started the initiative to develop the Future Railway Mobile Communication System (FRMCS). This paper describes an Adaptable Communication System (ACS) that is being developed jointly by industry and railway operators as a possible successor covering all types of railways and all aspects of the FRMCS. A pragmatic approach is suggested that considers diverse railway settings and makes use of various radio access technologies. Countries, geographical regions and infrastructure managers differ concerning available radio technologies, but use of a suitable ACS could pave the way towards innovation in the railway sector. For this adaptive concept we discuss several network models and enhancements including satellite communications (SatCom), Software-Defined Networking (SDN) integration and antenna systems that support multiple bearers in one. For SatCom a software defined radio (SDR) prototype using random access is presented that is able to fulfill the requirements of ETCS. We found that SDN can be used for dynamically changing the access technology for critical and noncritical railway use cases. Furthermore, we present an antenna prototype that can be used for 5G, GSM, WLAN and LTE in parallel which saves limited mounting surface on the train.

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“…Most of the studies considered V2I or V2V [13][14][15][16][17][18]. Only a few previous studies considered Train-to-Train (T2T) [19,20] or Train-to-Infrastructure (T2I) [21] environments. Interestingly, their interested frequency bands were different: 2.4 GHz [22], 2.1-2.6 GHz [21], 5.2 GHz [19], 5.9 GHz [14][15][16], etc.…”

Section: Introductionmentioning

confidence: 99%

A 5.9 GHz Channel Characterization at Railroad Crossings for Train-to-Infrastructure (T2I) Communications

Choi

Ahn

2023

Electronics

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Intelligent transport systems (ITSs) rely on wireless communications that provide many services to ground and aerial vehicles. We believe that vehicular communication protocols can evolve the train communication systems into the next generation. However, we found that channel models in train track environments at the 5.9 GHz frequency band are scarcer than in vehicular environments. Therefore, we conduct channel measurements at the 5.86–5.91 GHz ITS band at various railroad crossings in the United States. This allows us to extract the channel parameters and evaluate the propagation channel characteristics. The evaluations show a certain similarity between the train track channel characteristics and the vehicular communications channel characteristics. The railroad channel with an omnidirectional antenna is similar to a suburban environment in the vehicular channel, and with a bidirectional antenna, it is similar to a highway LoS environment in the vehicular channel. However, more importantly, the population of the surrounding buildings and the size of the LoS window can highly affect the RF propagation characteristics.

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Channel Models for Performance Evaluation of Wireless Systems in Railway Environments

Cited by 15 publications

References 73 publications

Equalizer Parameters’ Adjustment Based on an Oversampled Channel Model for OFDM Modulation Systems

Equalizer Parameters’ Adjustment Based on an Oversampled Channel Model for OFDM Modulation Systems

Next-Generation Connectivity in A Heterogenous Railway World

A 5.9 GHz Channel Characterization at Railroad Crossings for Train-to-Infrastructure (T2I) Communications

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