116 research outputs found
Multiple and single snapshot compressive beamforming
For a sound field observed on a sensor array, compressive sensing (CS)
reconstructs the direction-of-arrival (DOA) of multiple sources using a
sparsity constraint. The DOA estimation is posed as an underdetermined problem
by expressing the acoustic pressure at each sensor as a phase-lagged
superposition of source amplitudes at all hypothetical DOAs. Regularizing with
an -norm constraint renders the problem solvable with convex
optimization, and promoting sparsity gives high-resolution DOA maps. Here, the
sparse source distribution is derived using maximum a posteriori (MAP)
estimates for both single and multiple snapshots. CS does not require inversion
of the data covariance matrix and thus works well even for a single snapshot
where it gives higher resolution than conventional beamforming. For multiple
snapshots, CS outperforms conventional high-resolution methods, even with
coherent arrivals and at low signal-to-noise ratio. The superior resolution of
CS is demonstrated with vertical array data from the SWellEx96 experiment for
coherent multi-paths.Comment: In press Journal of Acoustical Society of Americ
Time- and Frequency-Varying -Factor of Non-Stationary Vehicular Channels for Safety Relevant Scenarios
Vehicular communication channels are characterized by a non-stationary time-
and frequency-selective fading process due to fast changes in the environment.
We characterize the distribution of the envelope of the first delay bin in
vehicle-to-vehicle channels by means of its Rician -factor. We analyze the
time-frequency variability of this channel parameter using vehicular channel
measurements at 5.6 GHz with a bandwidth of 240 MHz for safety-relevant
scenarios in intelligent transportation systems (ITS). This data enables a
frequency-variability analysis from an IEEE 802.11p system point of view, which
uses 10 MHz channels. We show that the small-scale fading of the envelope of
the first delay bin is Ricean distributed with a varying -factor. The later
delay bins are Rayleigh distributed. We demonstrate that the -factor cannot
be assumed to be constant in time and frequency. The causes of these variations
are the frequency-varying antenna radiation patterns as well as the
time-varying number of active scatterers, and the effects of vegetation. We
also present a simple but accurate bi-modal Gaussian mixture model, that allows
to capture the -factor variability in time for safety-relevant ITS
scenarios.Comment: 26 pages, 12 figures, submitted to IEEE Transactions on Intelligent
Transportation Systems for possible publicatio
Minimum-Energy Bandlimited Time-Variant Channel Prediction with Dynamic Subspace Selection
In current cellular communication systems the time-selective fading process is highly oversampled. We exploit this fact for time-variant flat-fading channel prediction by using dynamically selected predefined low dimensional subspaces spanned by discrete prolate spheroidal (DPS) sequences. The DPS sequences in each subspace exhibit a subspace-specific bandwidth matched to a certain Doppler frequency range. Additionally, DPS sequences are most energy concentrated in a time interval matched to the channel observation interval. Both properties enable the application of DPS sequences for minimum-energy (ME) bandlimited prediction. The dimensions of the predefined subspaces are in the range from one to five for practical communication systems. The subspace used for ME bandlimited prediction is selected based on a probabilistic bound on the reconstruction error. By contrast, time-variant channel prediction based on non-orthogonal complex exponential basis functions needs Doppler frequency estimates for each propagation path which requires high computational complexity. We compare the performance of this technique under the assumption of perfectly known complex exponentials with that of ME bandlimited prediction augmented with dynamic subspace selection. In particular we analyze the mean square prediction error of the two schemes versus the number of discrete propagation paths
In-vehicle channel sounding in the 5.8-GHz band
The article reports vehicular channel measurements in the frequency band of 5.8 GHz for IEEE 802.11p standard. Experiments for both intra-vehicle and out-of-vehicle environments were carried out. It was observed that the large-scale variations (LSVs) of the power delay profiles (PDPs) can be best described through a two-term exponential decay model, in contrast to the linear models which are suitable for popular ultra-wideband (UWB) systems operating in the 3- to 11-GHz band. The small-scale variations (SSVs) are separated from the PDP by subtracting the LSV and characterized utilizing logistic, generalized extreme value (GEV), and normal distributions. Two sample Kolmogorov-Smirnov (K-S) tests validated that the logistic distribution is optimal for in-car, whereas the GEV distribution serves better for out-of-car measurements. For each measurement, the LSV trend was used to construct the respective channel impulse response (CIR), i.e., tap gains at different delays. Next, the CIR information is fed to an 802.11p simulation testbed to evaluate the bit error rate (BER) performance, following a Rician model. The BER results strongly vouch for the suitability of the protocol for in-car as well as out-of-car wireless applications in stationary environments.The article reports vehicular channel measurements in the frequency band of 5.8 GHz for IEEE 802.11p standard. Experiments for both intra-vehicle and out-of-vehicle environments were carried out. It was observed that the large-scale variations (LSVs) of the power delay profiles (PDPs) can be best described through a two-term exponential decay model, in contrast to the linear models which are suitable for popular ultra-wideband (UWB) systems operating in the 3- to 11-GHz band. The small-scale variations (SSVs) are separated from the PDP by subtracting the LSV and characterized utilizing logistic, generalized extreme value (GEV), and normal distributions. Two sample Kolmogorov-Smirnov (K-S) tests validated that the logistic distribution is optimal for in-car, whereas the GEV distribution serves better for out-of-car measurements. For each measurement, the LSV trend was used to construct the respective channel impulse response (CIR), i.e., tap gains at different delays. Next, the CIR information is fed to an 802.11p simulation testbed to evaluate the bit error rate (BER) performance, following a Rician model. The BER results strongly vouch for the suitability of the protocol for in-car as well as out-of-car wireless applications in stationary environments
Propagation aspects of vehicle-to-vehicle communications - an overview
Vehicle-to-vehicle (VTV) wireless communications have many envisioned applications in traffic safety, congestion avoidance, etc., but the development of suitable communications systems and standards requires accurate models for the VTV propagation channel. This paper provides an overview of existing VTV channel measurement campaigns, describing the most important environments, and the delay spread and Doppler spreads obtained in them. Statistical as well as geometry-based channel models have been developed based on measurements and intuitive insights. A key characteristic of VTV channels is the nonstationarity of their statistics, which has major impact on the system performance. Extensive references are provided
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