• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7C
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• pp.687-695
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• 2005

A bandpass sampling technique, which is a method directly downconverting a bandpass signal to a baseband or a low IF signal without analog mixers, can be an alterative choice for the SDR system to minimize the RF front-end. In this paper, a complex bandpass sampling technique for two bandpass-filtered signals is proposed. We derived generalized formulae for the available sampling range, the signal's IF and the minimum sampling frequency taking into consideration the guard-bands for the multiple RE signals. Thru the simulation experiments, the advantages of the . complex bandpass sampling over the pre-reported real bandpass sampling are investigated for applications in the SDR design.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9C
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• pp.913-921
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• 2005

A complex bandpass sampling technique can provide a more flexible architecture for designing a software- defined radio(SDR) system, because it has several advantageous features of larger sampling range and lower minimum sampling frequency than a real bandpass sampling method. In spite of the potential advantages of the complex bandpass sampling, solid investigation for the direct downconversion of multiple signals by the complex sampling theory has not been reported yet. Thus, we propose in this paper a novel scheme for the downconversion of multiple signals using the complex bandpass sampling, and develop the formulae related to the complex bandpass sampling for practical usage, such as the valid sampling range, the intermediate frequency (If), and the minimum sampling frequency of the downconversion of multiple RE signals. Such derived formulae are verified from simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1249-1256
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• 2006

This paper proposes, based on a bandpass sampling theory, a novel method to find valid sampling frequency range and minimum sampling rate with low computational complexity for downconversion of multiple bandpass radio frequency (RF) signals. Guard-bands or spacing between adjacent downconverted signal spectrums are also taken into consideration in determining sampling frequency for practical implementation. Moreover, we verify through comparison with other method that the proposed method has more advantageous properties.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.8
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• pp.1805-1812
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• 2011

Bandpass sampling technique has an advantage that it uses lower sampling frequency than Nyquist criterion. But special care is required in choosing sampling frequency to avoid self-image overlapping in the first Nyquist region. Recently, the second-order BPS techniques which can suppress possible self-image by using an additional ADC and by employing digital signal processing have been proposed. This paper addresses a complex BPS based SDR front-end. Unlike general second-order BPS, it needs simple FIR filter to compensate delay in the second ADC. We show a method to find proper sampling frequencies to down convert RF signals selected by tunable RF filter operating in arbitrary frequency range.

• Journal of Communications and Networks
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• v.10 no.1
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• pp.55-62
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• 2008

Bandpass sampling (BPS) techniques for the direct down-conversion of RF bandpass signals have become an essential technique for software defined radio (SDR), due to their advantage of minimizing the radio frequency (RF) front-end hardware dependency. This paper proposes an algorithm for finding the minimum BPS frequency for simultaneously down-converting multiple RF signals through full permutation over all the valid sampling ranges found for the multiple RF signals. We also present a scheme for reducing the computational complexity resulting from the large scale of the purmutation calculation involved in searching for the minimum BPS frequency. In addition, we investigate the BPS frequency allowing for the guard-band between adajacent down-converted signals, which help lessen the severe requirements in practical implementations. The performance of the proposed method is compared with those of other pre-reported methods to prove its effectiveness.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12A
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• pp.1286-1295
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• 2007

This paper proposes, based on a bandpass sampling theory, a novel method to find valid sampling frequency range and minimum sampling rate with low computational complexity for downconversion of N bandpass radio frequency(RF) signals, under application of all possible signal placements(full permutations) in a IF stage. Additionally, we have developed a complexity-reducing method to obtaine the opttimal and minimal sampling rate for supporting the user-wanted guard-band or spacing between adjacent downconverted signal spectrums. Moreover, we have verified through comparisons with other methods that the proposed methods have more advantageous properties.

• Journal of Advanced Navigation Technology
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• v.4 no.1
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• pp.36-44
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• 2000

A frequency-shifting technique that uses a digital filter in order to interpolate a bandpass-sampled signal at a low-pass position is investigated. The discussion focuses on the derivation of the required digital filter. It is shown that second-order bandpass sampling offers more flexibility than first-order bandpass sampling in the sense of sampling frequency choice. It is also shown that the well-known quadrature-sampling method for frequency-shifting is a special case of the general second-order sampling technique. The advantages of the mixer-free digital quadrature demodulations are increased flexibility for sampling frequency choice and high precision for I/Q component extraction, and this type of modulation can be applied for modern radar signal processing with high performance.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.225-230
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• 2013

In a bandpass sampling (BPS), the frequency of the sampler is lower than that of the signal being sampled. In this method, the baseband spectrum directly appears by the sampling operation, so that it is not necessary to use any frequency down-converter, which makes the receiver's hardware simpler. The second-order BPS uses two identical BPS samplers, of which sampling times are offset by each other. By exploiting the relationship between two sampled signals, it can be possible to cancel the aliased signal component or the interference due to the bandpass sampling. In order to cancel the interference, an interpolant filter is used to manipulate the phase characteristics of the BPS sampled signal. In this paper, it is introduced a multiband interpolant filter which can simultaneously cancel multiple interference signals that have been aliased from multiple frequency bands. In case of no need of interference cancellation, another method is suggested to enhance the signal quality by 3dB. A computer simulation has been performed, and the feasibility of the suggested methods has been verified.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.69-72
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• 2012

In the bandpass sampling(BPS), the sampling frequency is lower than the frequency of the RF(radio frequency) signal being sampled. In this method, the baseband spectrum directly appears by the sampling itself, so that it is not necessary to use any down converter, making the receiver's hardware simpler. The second-order BPS uses two identical BPS samplers operating with an offset timing to each other. By a processing with their two sampled signals, it can be possible to cancel the aliasing or interference component if any due to the bandpass sampling. The interpolant filter, which is to manipulate the phase characteristics of the sampled signal, affects the performance of the cancellation. In this paper, a multiband interpolant filter is introduced, with which multiple interference signals from multiple RF bands can be cancelled simultaneously. We suggest several phase characteristics for the interpolant filter and have evaluated their performances through computer simulations. It has been shown that the filter with a continuous phase function gives the better performance.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.132-139
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• 2016

In the bandpass sampling(BPS), the sampling frequency for the analog-to-digital converter is lower than that of the signal to be sampled. Since the BPS operation results in the signal spectrum to be copied on the baseband, it is possible for the frequency down-converter to be conveniently omitted. The second-order BPS system is introduced in order to cancel the aliased interference components from the BPS output that may be generated by the BPS processing. In this paper, we introduce a design method for the optimal phase of the interpolant filter in the second-order BPS system which enables to maximally cancel the aliased components. Being mathematically derived, this method can always be applied independently to the spectral characteristics of the BPS input signal. The performance improvements by the suggested method has been measured statistically with various power spectra of the received signal, and it has been shown that the maximal amount of the improvements reaches up to 5~20 [dB] in comparison with the previous suboptimal algorithm.