Frequency-Domain In-Vehicle UWB Channel Modeling

Chandra, Aniruddha; Prokeš, Aleš; Mikulasek, Tomas; Blumenstein, Jiří; Kukolev, Pavel; Zemen, Thomas; Mecklenbräuker, Christoph F.

doi:10.1109/tvt.2016.2550626

Cited by 40 publications

(12 citation statements)

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“…The path-loss is obtained from the measured data in the VNA. This result is the average in the entire frequency range (26.5-40 GHz) [13]. equals 1601 which is the number of dots…”

Section: Channel Modelmentioning

confidence: 89%

Wideband Channel Modeling for mm‐Wave inside Trains for 5G‐Related Applications

García-Loygorri

Briso-Rodríguez

Arnedo

et al. 2018

Wireless Communications and Mobile Computing

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Passenger trains and especially metro trains have been identified as one of the key scenarios for 5G deployments. The wireless channel inside a train car is reported in the frequency range between 26.5 GHz and 40 GHz. These bands have received a lot of interest for high-density scenarios with a high-traffic demand, two of the most relevant aspects of a 5G network. In this paper we provide a full description of the wideband channel estimating Power-Delay Profiles (PDP), Saleh-Valenzuela model parameters, time-of-arrival (TOA) ranging, and path-loss results. Moreover, the performance of an automatic clustering algorithm is evaluated. The results show a remarkable degree of coherence and general conclusions are obtained.

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“…The path-loss is obtained from the measured data in the VNA. This result is the average in the entire frequency range (26.5-40 GHz) [13]. equals 1601 which is the number of dots…”

Section: Channel Modelmentioning

confidence: 89%

Wideband Channel Modeling for mm‐Wave inside Trains for 5G‐Related Applications

García-Loygorri

Briso-Rodríguez

Arnedo

et al. 2018

Wireless Communications and Mobile Computing

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“…2) Frequency Domain Phase Measurement: For a wideband signal, it is difficult to measure the phase for multiple frequencies in the time domain. Frequency domain measurement has been widely used for ultrawideband (UWB) signal processing in TOA estimation [10], doppler radar [11], synthetic aperture radar (SAR) [12] and channel modeling [13]. To measure the phase of sampled electric and magnetic signal, we can use the discrete Fourier transform (DFT) [14],…”

Section: ) Signal Generationmentioning

confidence: 99%

Wideband Signal Based Near-Field Electromagnetic Ranging for Indoor Localizatio

Wang¹,

Liu²,

Zhang³

et al. 2018

Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)

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The near-field electromagnetic ranging (NFER) technology exploits the near-field phase behavior of low frequency signals to measure the distance and can provide better ranging performance than the high frequency signal based methods in the cluttered environments. However, the currently existing NFER system uses the mono-frequency signals and can not obtain same ranging accuracy at different distances. In addition, low signal-to-noise ratio (SNR) seriously impacts the ranging accuracy. In this paper, we proposed a wideband signal based NFER system to improve the ranging performance. Instead of the mono-frequency signals, the proposed wideband system transmits the wideband signals. We use frequency domain phase measurement (FDPM) to detect the phase difference between received electric field signal and magnetic field signal. Then the least squares method is used to estimate the distance. Simulation results show that the proposed wideband NFER system can improve the ranging performance at low SNR environment and within a wide range of distances.

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“…Other possibility to perform the channel sounding is to utilize the frequency domain channel sounders, where the sounder usually needs some time to sweep the band of interest. Subsequently, sounder stores the channel transfer functions [14]. In the time domain channel sounding, a broadband pulse or sequence is transmitted and the need for the channel sweep time is reduced.…”

Section: A Principle Of the Correlative Channel Soundermentioning

confidence: 99%