• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38C no.6
• /
• pp.497-502
• /
• 2013

In this paper, we aim to evaluate the performance of the digital signal processing (DSP) algorithm used in [8] in order to improve the resolution of spectrometers with fixed number of low-cost, non-ideal filters. In such spectrometers, the resolution is limited by the number of filters. We aim to demonstrate via new experiments that the resolution improvement by six times over the conventional limit is possible by using the DSP algorithm as claimed by [8].

• Journal of the Institute of Electronics and Information Engineers
• /
• v.49 no.9
• /
• pp.138-144
• /
• 2012

In this paper, we introduce the time-domain equalizer in orthogonal frequency division multiplexing (OFDM) systems using orthogonal matching pursuit (OMP) algorithm. Since OFDM system inserts guard intervals, it shows robust performance against multi-path fading. However, in Doppler channel, inter-carrier interference (ICI) occurs because an orthogonality of sub-carriers does not maintain. A least squares (LS) algorithm is common method of time-domain equalizer, but if a channel length is longer, the performance deteriorates by noise. The multi-path fading is a summation of the different delay signal. And that has sparse properties in time-domain. Because the OMP algorithm of the compressive sensing (CS) algorithm restores the channel by choosing the important elements of sparse channel, it can reduce the influence of noise. We simulate the performance of time-domain equalizer in OFDM system with various channel environments using OMP algorithm compared with other equalization method.

• Journal of Broadcast Engineering
• /
• v.10 no.2
• /
• pp.166-173
• /
• 2005

In this paper, we propose a mobile channel estimation algorithm using matching pursuit algorithm for orthogonal frequency division multiplexing (OFDM) systems. Least square (LS) algorithm, which is used as a conventional channel estimation algorithm for OFDM systems, has error probability of channel estimation affected by effects of noise. By estimating the channel of sparse type, the proposed algorithm reduces effects of noise during time intervals that multi-path signal doesn't exist. The proposed algorithm estimates a mobile receivingchannel using pilot information transmitted consequently. We compare performance of the proposed algorithm with the LS algorithm by measuring symbol error rate with 64QAM under a mobile multi-path fading channel model.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.28 no.8
• /
• pp.636-645
• /
• 2017

A scanning radar is exploited widely such as for ground surveillance, disaster rescue, and etc. However, the range resolution is limited by transmitted bandwidth and cross-range resolution is limited by beam width. In this paper, we propose a method for super-resolution radar imaging. If the distribution of reflectivity is sparse, the distribution is called sparse signal. That is, the problem could be formulated as compressive sensing problem. In this paper, 2D super-resolution radar image is generated via reweighted ${\ell}_1-Minimization$. In the simulation results, we compared the images obtained by the proposed method with those of the conventional Orthogonal Matching Pursuit(OMP) and Synthetic Aperture Radar(SAR).

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.11 no.1
• /
• pp.171-182
• /
• 2015

The general wavelet transform has profitable property in non-stationary signal analysis specially. The tunable Q-factor wavelet transform is a fully-discrete wavelet transform for which the Q-factor Q and the asymptotic redundancy r, of the transform are easily and independently specified. In particular, the specified parameters Q and r can be real-valued. Therefore, by tuning Q, the oscillatory behavior of the wavelet can be chosen to match the oscillatory behavior of the signal of interest, so as to enhance the sparsity of a sparse signal representation. The TQWT is well suited to fast algorithms for sparsity-based inverse problems because it is a Parseval frame, easily invertible, and can be efficiently implemented. The transform is based on a real valued scaling factor and is implemented using a perfect reconstruction over-sampled filter bank with real-valued sampling factors. The transform is parameterized by its Q-factor and its over-sampling rate, with modest over-sampling rates being sufficient for the analysis/synthesis functions to be well localized. This paper describes filter design of 2D discrete-time wavelet transform for which the Q-factor is easily specified. With the advantage of this transform, perfect reconstruction filter design and implementation for performance improvement are focused in this paper. Hence, the 2D transform can be tuned according to the oscillatory behavior of the image signal to which it is applied. Therefore, application for performance improvement in multimedia communication field was evaluated.

• Journal of electromagnetic engineering and science
• /
• v.15 no.1
• /
• pp.53-58
• /
• 2015

For the testing of nonlinear power amplifiers, this paper suggests an approach to design optimized multisine signals that could be substituted for the original modulated signal. In the design of multisines, complex coefficients should be determined to mimic the target signal as much as possible, but very few methods have been adopted as general solutions to the coefficients. Furthermore, no solid method for the phase of coefficients has been proven to show the best resemblance to the original. Therefore, in order to determine the phase of multisine coefficients, a time-domain nonlinear optimization method is suggested. A frequency-domain-method based on the spectral response of the target signal is also suggested for the magnitude of the coefficients. For the verification, multisine signals are designed to emulate the LTE downlink signal of 10 MHz bandwidth and are used to test a nonlinear amplifier at 1.9 GHz. The suggested phase-optimized multisine had a lower normalized error by 0.163 dB when N = 100, and the measurement results showed that the suggested multisine achieved more accurate adjacent-channel leakage ratio (ACLR) estimation by as much as 12 dB compared to that of the conventional iterative method.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.1
• /
• pp.1-11
• /
• 2016

We investigate compressive sensing techniques to estimate sparse channel in Orthogonal Frequency Division Multiplexing(OFDM) systems. In the case of large channel delay spread, compressive sensing may not be applicable because it is affected by length of measurement vectors. In this paper, we increase length of measurement vector adding pilot information to OFDM data block. The increased measurement vector improves probability of finding path delay set and Mean Squared Error(MSE) performance. Simulation results show that signal recovery performance of a proposed scheme is better than conventional schemes.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.10
• /
• pp.6296-6302
• /
• 2014

A new technique, which can increase the channel bandwidth in an optical wireless orthogonal frequency division multiplexing (OFDM) link based on a light emitting diode (LED), is proposed. The technique uses adaptive sampling to convert an OFDM signal to a sparse waveform. In compressive sensing (CS), a sparse signal that is sampled below the Nyquist/Shannon limit can be reconstructed successively with sufficient measurements. The data rate of the proposed CS-based visible light communication (VLC)-OFDM link increases from 30.72 Mb/s to 51.2 Mb/s showing an error vector magnitude (EVM) of 31 % at the quadrature phase shift keying (QPSK) symbol.

• ETRI Journal
• /
• v.35 no.2
• /
• pp.200-206
• /
• 2013

Most of the literature on compressed sensing has not paid enough attention to scenarios in which the number of acquired measurements is insufficient to satisfy minimal exact reconstruction requirements. In practice, encountering such scenarios is highly likely, either intentionally or unintentionally, that is, due to high sensing cost or to the lack of knowledge of signal properties. We analyze signal reconstruction performance in this setting. The main result is an expression of the reconstruction error as a function of the number of acquired measurements.

• Journal of Sensor Science and Technology
• /
• v.29 no.3
• /
• pp.141-148
• /
• 2020

To find food, homes, and mates, some animals have adapted special sensing capabilities. Rather than using a passive method, they discharge a signal and then extract the necessary information from the response. More importantly, they use the slope of the detected signal to find the destination of an object. In this paper, similar strategy is mathematically formulated. A perturbation and correlation-based gradient estimation method is developed and used as a sensing strategy. This method allows us to adaptively sense an object in a given environment effectively. The proposed strategy is based on the use of gradient values; rather than instantaneous measurements. Considering the gradient value, the sampling frequency is planned adaptively, i.e., sparse sampling is performed in slowly varying regions, while dense sampling is conducted in rapidly changing regions. Using a temperature sensor, the proposed strategy is verified and its effectiveness is demonstrated.