Super-resolution of pulsed multipath channels for delay spread characterization

Vaughan, Rodney G.; Scott, N.L.

doi:10.1109/pimrc.1996.568387

Cited by 12 publications

(15 citation statements)

References 6 publications

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“…Subsequently, a deconvolution process is necessary in order to extract the discrete CIR ( ) h n . In this paper, the well-known CLEAN algorithm [9] is employed to perform this function. After antenna calibration, windowing and de-convolution, discrete UWB CIRs were obtained.…”

Section: A Data Pre-processingmentioning

confidence: 99%

Statistical characterization of UWB propagation channel in ship cabin environment

Zhai

Jiang

et al. 2012

2012 IEEE International Conference on Communications (ICC)

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This paper presents a statistical characterization of Ultra-Wideband (UWB) channel for ship cabin environment based on measurements carried out in the frequency-domain and covered the frequency band of 6-9GHz. According to the results of measurement, it is observed that rays arrive in clusters, so we describe the multipath propagation with the classical S-V model. The main purpose is to study multipath propagation behavior, particularly the phenomenon of clustered multipath components. An efficient cluster automatic identification algorithm based on wavelet analysis is employed for clusters identification of the discrete UWB channel impulse responses (CIRs). Then, the statistical characterizations of multi-path components (MPCs) are examined. Finally, simulation results of the proposed statistical model are compared to measured data demonstrating reasonable agreement. The results are helpful to model the UWB propagation channel in such environment.

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Section: A Data Pre-processingmentioning

confidence: 99%

Statistical characterization of UWB propagation channel in ship cabin environment

Zhai

Jiang

et al. 2012

2012 IEEE International Conference on Communications (ICC)

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“…Templates of different AoE are labeled 0°, 45° and 90°, where 0° refers to the case in which the planes of the transmitting and receiving antennas are parallel. Besides, the first arrived pulse of the 2 LOS measurements at F1 (3,4) and F2 (3,5) are also recorded as the templates. We use …”

Section: B Multi-template Cs-mpmentioning

confidence: 99%

“…With a proper measurement setup, it can be straightforward to obtain both the large-scale and small-scale channel parameters. However, if highresolution channel modeling is required, a deconvolution algorithm, such as CLEAN algorithm [3] or its variations [4], can be used to obtain the details of channel impulse response (CIR) [5]. High-resolution means that the delay resolution is better than the inverse bandwidth.…”

Section: Introductionmentioning

confidence: 99%

A multi-template deconvolution algorithm based on compressed sensing for UWB channel modeling

Zhou

et al. 2011

2011 6th International ICST Conference on Communications and Networking in China (CHINACOM)

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Deconvolution is a key operation for the postprocessing of ultra-wideband (UWB) channel modeling. Due to the wideband of the radio channel sounding pulse, the nature of the UWB channel can be frequency selective. This paper presents a multi-template compressed sensing (CS) based high-resolution deconvolution algorithm for time-domain UWB channel modeling, considering the pulse distortion. UWB channels are a prime example of long and sparse channel impulse response (CIR). Furthermore, the design of a multi-template dictionary of parameterized waveforms that closely matches the waveform of multipath leads to that the UWB channel measurement signal is more compactly represented. The multi-path can be better identified by a multi-template dictionary. The Matching Pursuit (MP) algorithm is used as the signal reconstruction method of CS and outputs the CIR directly. Simulation results show that compared to CLEAN, the proposed multi-template CS-MP deconvolution algorithm can achieve a comparable performance with much fewer samplings.

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“…Some attempts to fit this modified specular multipath channel model to measurement data have been reported in [4], [5]. The subtractive deconvolution approach [6] is employed to extract the model parameters from measurement data. In [4], a known set of In [5], the received pulse shapes are parameterized assuming known delays and the parameters are obtained from leastsquare estimation.…”

Section: Introductionmentioning

confidence: 99%

Multipath Model Selection for UWB Channels

Wong

Lee

2006

2006 IEEE International Conference on Ultra-Wideband

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In this paper, we develop an algorithm to extract the parameters of a multipath model of an UWB channel from measurement/simulated data. To this end, we cast the parameter estimation problem into a standard model selection problem and apply the well known minimum description length principle to solve the model selection problem. Numerical results obtained based on the CM1 and CM2 models suggest that the proposed algorithm is effective. I. INTRODUCTIONIt is well known that ultra-wideband (UWB) channels have characteristics that are different from traditional wideband channels. This is in fact the main thrust behind many recent research efforts on UWB systems. There have be a significant volume of measurement and modeling works aiming to characterize the UWB channels. An excellent tutorial contribution that summarizes many of the recent such activities can be found in [1].A traditional frequency selective channel is adequately modeled by a tapped delay line with taps spacing set at the duration of the reciprocal of the system bandwidth [2]. In most traditional communication systems, since the symbol rate (or the chip rate for spread spectrum systems) roughly equals the system bandwidth, the received signal approximately consists of replicas of the transmitted pulses, scaled by the channel taps and separated at the tap spacings. This model is usually referred to as the specular multipath model.For a typical UWB channel, a number of measurement studies [1], [3], [4] have shown that the specular multipath model is inadequate. Other physics-based channel models [1], such as those obtained based on ray-tracing analysis, suggest a much finer resolution than the symbol (or chip) spacing in the tapped delay line is needed. Unfortunately many of the physics-based models are not convenient for UWB system design and analysis. As a result, there have been modifications of the standard specular multipath model to better describe the characteristics of an UWB channel.A common modification involves allowing the received pulses at different delays to vary in shape [3]. We will refer to this model as the modified specular multipath model and describe it in detail in Section 11. Some attempts to fit this modified specular multipath channel model to measurement data have been reported in [4], [5]. The subtractive deconvolution approach [6] is employed to extract the model parameters from measurement data. In [4], a known set of

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Super-resolution of pulsed multipath channels for delay spread characterization

Cited by 12 publications

References 6 publications

Statistical characterization of UWB propagation channel in ship cabin environment

Statistical characterization of UWB propagation channel in ship cabin environment

A multi-template deconvolution algorithm based on compressed sensing for UWB channel modeling

Multipath Model Selection for UWB Channels

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