Phase Coherent EM Array Measurements in a Refractive Environment

Wagner, Mark; Groll, Herbert; Dormiani, Ali; Sathyanarayanan, Venkatesh; Mecklenbräuker, Christoph F.; Gerstoft, Peter

doi:10.1109/tap.2021.3069516

Cited by 5 publications

(2 citation statements)

References 48 publications

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“…However, the distance of remote interference will far exceed this range. The atmospheric duct, which results from non-standard meteorological conditions, captures the electromagnetic wave and induces the signal to propagate in the ducting layer [ 4 ]. The atmospheric duct captures the signal and allows the signal to propagate beyond the GP maximum protection distance with low path loss [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Remote Interference Discrimination Testbed Employing AI Ensemble Algorithms for 6G TDD Networks

Zhang

Zhou

et al. 2023

Sensors

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The Internet-of-Things (IoT) massive access is a significant scenario for sixth-generation (6G) communications. However, low-power IoT devices easily suffer from remote interference caused by the atmospheric duct under the 6G time-division duplex (TDD) mode. It causes distant downlink wireless signals to propagate beyond the designed protection distance and interfere with local uplink signals, leading to a large outage probability. In this paper, a remote interference discrimination testbed is originally proposed to detect interference, which supports the comparison of different types of algorithms on the testbed. Specifically, 5,520,000 TDD network-side data collected by real sensors are used to validate the interference discrimination capabilities of nine promising AI algorithms. Moreover, a consistent comparison of the testbed shows that the ensemble algorithm achieves an average accuracy of 12% higher than the single model algorithm.

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Section: Introductionmentioning

confidence: 99%

Remote Interference Discrimination Testbed Employing AI Ensemble Algorithms for 6G TDD Networks

Zhang

Zhou

et al. 2023

Sensors

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“…An extension to nonuniform linear arrays via irregular Vandermonde decomposition is shown in [31]. The application of ANM for real array measurements is shown in [32]. DOA estimation with deep learning methods from single delay-Doppler snapshots in automotive radar is investigated in [33].…”

Section: Introductionmentioning

confidence: 99%

Scatterer Identification by Atomic Norm Minimization in Vehicular mm-Wave Propagation Channels

et al. 2022

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Sparse scatterer identification with atomic norm minimization (ANM) techniques in the delay-Doppler domain is investigated for a vehicle-to-infrastructure millimeter wave propagation channel. First, a two-dimensional ANM is formulated for jointly estimating the time-delays and Doppler frequencies associated with individual multipath components (MPCs) from short-time Fourier transformed measurements. The two-dimensional ANM is formulated as a semi-definite program and promotes sparsity in the delay-Doppler domain. The numerical complexity of the two-dimensional ANM limits the problem size which results in processing limitations on the time-frequency sample matrix size. Subsequently, a decoupled form of ANM is used together with a matrix pencil, allowing a larger sample matrix size. Simulations show that spatial clusters of a point-scatterers with small cluster spread are suitable to model specular reflection which result in significant MPCs and the successful extraction of their delay-Doppler parameters. The decoupled ANM is applied to vehicle-to-infrastructure channel sounder measurements in a sub-urban street in Vienna at 62 GHz. The obtained results show that the decoupled ANM successfully extracts the delay-Doppler parameters in high resolution for the channel's significant MPCs.INDEX TERMS Beyond 5G mobile communication, millimeter wave propagation, multipath channels, time-varying channels, vehicle-to-infrastructure connectivity

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Empiric Bayesian Inversion of Evaporation Ducts From Synthetic Phased-Array Data

Rogers

Gerstoft

2023

2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)

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Phase Coherent EM Array Measurements in a Refractive Environment

Cited by 5 publications

References 48 publications

Remote Interference Discrimination Testbed Employing AI Ensemble Algorithms for 6G TDD Networks

Remote Interference Discrimination Testbed Employing AI Ensemble Algorithms for 6G TDD Networks

Scatterer Identification by Atomic Norm Minimization in Vehicular mm-Wave Propagation Channels

Empiric Bayesian Inversion of Evaporation Ducts From Synthetic Phased-Array Data

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