• International journal of advanced smart convergence
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• v.6 no.3
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• pp.1-8
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• 2017

In this paper, an improved ordered block minimum mean squared error (OB-MMSE) detector for generalized spatial modulation (GSM) systems is presented. It is based on an ordered successive interference cancellation (OSIC) technique. Its bit error rate (BER) performance and computational complexity are compared with those of the corresponding original OB-MMSE detector. It is shown that the proposed OSIC-based OB-MMSE detector outperforms the OB-MMSE detector in terms of BER without noticeable complexity increase.

• ETRI Journal
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• v.16 no.1
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• pp.17-34
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• 1994

In this paper, we present an architecture of the constant false alarm rate (CFAR) detector called the generalized order statistics (GOS) CFAR detector, which covers various order statistics (OS) and cell-averaging (CA) CFAR detectors as special cases. For the proposed GOS CFAR detector, we obtain unified formulas for the false alarm and detection probabilities. By properly choosing coefficients of the GOS CFAR detector, one can utilize any combination of ordered samples to estimate the background noise level. Thus, if we use a reference window of size N, we can realize $(2^N-1)$ kinds of CFAR processors and obtain their performances from the unified formulas. Some examples are the CA, the OS, the censored mean level, and the trimmed mean CFAR detectors. As an application of the GOS CFAR detector to multiple target detection, we propose an algorithm called the adaptive mean level detector, which censors adaptively the interfering target returns in a reference window.

• ETRI Journal
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• v.16 no.2
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• pp.15-25
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• 1994

In this paper we present a new formula which can predict the exact detection probability of a generalized order statistics (GOS) constant false alarm rate (DFAR) detector for a partially correlated Rayleigh target model (0 < $ \rho$< 1) in a closed form, where $\rho$ is the correlation coefficient between returned pulses. By simply substituting a set of specific coefficient into the derived formula, one can obtain the detection probability of any kind of CFAR detector. Detectors may include the order statistics CFAR detector, the censored mean level detector, and the trimmed mean CFAR detector, but are not necessarily restricted to them. The numerical result for the first order Markov correlation model as applied to some of the detectors shows that as $\rho$ increases from zero to one, higher signal-to-noise ratio is required to achieve the same detection probability.

• ETRI Journal
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• v.41 no.2
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• pp.145-159
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• 2019

To reduce the number of radio frequency (RF) chains in multiple input multiple output (MIMO) systems, generalized spatial modulation (GSM) techniques have been proposed in the literature. In this paper, we propose a zero-forcing (ZF)-based detector, which performs an initial pruning of the search tree that will be considered as the initial condition in a sphere decoding (SD) algorithm. The proposed method significantly reduces the computational complexity of GSM systems while achieving a near maximum likelihood (ML) performance. We analyze the performance of the proposed method and provide an analytic performance difference between the proposed method and the ML detector. Simulation results show that the performance of the proposed method is very close to that of the ML detector, while achieving a significant computational complexity reduction in comparison with the conventional SD method, in terms of the number of visited nodes. We also present some simulations to assess the accuracy of our theoretical results.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.687-690
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• 1998

The full Viterbi detector for EPRML read channel system needs large area due to complex computation. There are several conventional methods to reduce the complexity such as GVA(Generalized Viterbi Algorithm) and BMS(Branch Metric Shift). This paper proposes another method, FVD(Folding Viterbi Detector), that has state transition diagram folded with inverted states. Compared with GVA detector, FVD requires only 61% gates and has lower power consumption and better BER performance.

• Journal of Communications and Networks
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• v.8 no.3
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• pp.290-296
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• 2006

In this paper, a generalized blind adaptive algorithm is introduced for multi-user detection of direct sequence code division multiple access (OS-COMA) wireless communication systems. The main property of the proposed algorithm is its ability to resolve the multipath fading channel resulting in inter symbol interference (ISI) as well as multiple access interference (MAI). Other remarkable properties are its low complexity and mitigation to the near-far problem as well as its insensitivity to asynchronous transmission. The proposed system is based on the minimization of the output energy and convergence to the minimum mean square error (MMSE) detector. It is blind in the sense that it needs no knowledge of the other users' signatures, only the intended user signature and timing are required. Furthermore, the convergence of the minimum output energy (MOE) detector to the MMSE detector is analytically proven in case of M-ary PSK. Depicted results show that the performance of the generalized system dominates those previously considered. Further improvements are obtained when multiple input multiple output (MIMO) technique is employed.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1991.10a
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• pp.107-110
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• 1991

When the noise has both additive and signal-dependent components, locally optimum detector test statistics are obtained for detection of weak composite signals using the generalized Neyman-Pearson lemma. In order to consider the non-additive noise as well as purely-additive noise, a generalized observation model is used in this paper. The locally optimum detector test statistics are derived for several different cases according to the relative strengths of the known signal component, the random signal component, and the signal-dependent noise component. Schematic diagrams of the locally optimum detector structures are also included.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.3
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• pp.66-76
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• 1995

In this research, a mesh connected VLSI structure is proposed for the real time computation of the generalized Hough transform(GHT). The purpose of the research is to design a generalized Hough transformer that can be realized as a single chip processor. The GHT has been modified to yield a highly parallel structure consisting of simple processing elements(PEs) and communication networks. In the proposed structure, the GHT can be computed by first assigning an image pixel to a PE and performing shift and add operations. The result of the CAD circuit simulation shows that it can be computed in the time proportional to the number of pixels in the pattern. In addition to the Hough transformer, the peak detector has been designed to reduce 1)the number of the I/O operations between the transformer and the host computer and 2) the host computer's burden for peak detection by transmitting only the local peaks detected from the transformed accumulator. It is expected that the proposed single chip Hough transformer with peak detector makes a fast and inexpensive edge based object recognition systems possible for many industrial and military applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1769-1776
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• 2013

In this paper, we proposed the modified YL(Yi and Loizou) algorithm, using a VAD(voice activity detector) for enhancing speech corrupted by colored noise. The performance of the proposed algorithm has been compared to the YL algorithm and LS(Lee and Son, etc.) algorithm by computer simulation. The colored noises used in the experiment were a car noise and multi-talker babble from the AURORA data base and the used voices from the TIMIT data base. It is confirmed that the proposed algorithm shows better performance from SNR(signal to noise ratio) and SSD(speech spectral distortion) viewpoint over the previous two approach.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.731-738
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• 2017

In this paper, we proposed a modified ML detector for generalized spatial modulation which is a method among Multiple-input Multiple-output. This proposed method detects signal applying modified channel statement information based on priority. Complexity in conventional methods increases as increasing the number of active antennas. To solve this problem, we proposed a new ML method using static channel information decided by the number of transmit antennas and the number of receive antennas. This method detects active antennas one by one through priority. The proposed method has proved benefit on complexity compared with conventional method through simulations. When the number of transmit antennas is equal to 10, there is approximately 45% complexity reduction.