• The Journal of the Acoustical Society of Korea
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• v.20 no.2
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• pp.52-57
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• 2001

The passive ranging estimation techniques using a focused beamformer have been studied under the water. It is well known that the passive ranging estimation method using a focused beamformer is excellently evaluated. Among these, the passive ranging sonar is known to have a good performance under low signal-to-noise. ratio. However, its performance is degraded in multi-source environments. In this paper, we proposed the technique using dual focused beamformers to estimate the range. And when the sampling frequency is low, it is very difficult to steer the focused beam to the desired direction, as a result of this, the low performance occurs because of a distorted beam pattern. In this paper, we study the effect of sampling rate on passive ranging by using focused beamformer. And we verified the performance of the proposed method via computer simulation.

• Proceedings of the Acoustical Society of Korea Conference
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• 1996.06a
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• pp.13-17
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• 1996

다수의 신호를 동시에 사용하는 경우에 나타나는 광대역 신호나 센서의 수와 형성하고자 하는 빔의 수가 많은 경우를 다루기 위해서는 주파수 영역 기법이 필요하다. FFT를 사용하는 낮은 샘플링 주파수에서도 시간 영역에서의 보간 방법보다 빠르게 정확한 시간 지연을 줄 수 있어 코히어런트 신호처리가 가능하다. 또한 특정 센서가 불량인 경우 보정이 상대적으로 용이하다는 장점을 가진다. 여러 가지 주파수 영역 빔형성 기법 중 계산량과 저장 용량면으로 효율적인 방법은 CZT와 FIR interpolation 방법이다. 또한, 공액 빔을 형성할 경우에는 Goertzel의 알고리듬을 이용하는 방법도 효율적이다.

• The Journal of the Acoustical Society of Korea
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• v.30 no.8
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• pp.474-481
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• 2011

Conventional beamforming is ineffective in producing directional information in system with sparse degree of the freedom such as DIFAR (DIrectional Frequency Analysis and Recording) sonobuoy and in the presence of high directional noise. In this paper, Adaptive beamforming techniques are applied to produce directional spectra from a small number of sensors in highly directional noise environment. Conventional method as well as minimum variance and eigenvectors as adaptive method are evaluated via numerical test and real data.

• The Journal of the Acoustical Society of Korea
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• v.39 no.3
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• pp.179-190
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• 2020

In this paper, we estimated the Direction of Arrival (DOA) using Conventional BeamForming (CBF), adaptive beamforming and compressive beamforming. Minimum Variance Distortionless Response (MVDR) and Multiple Signal Classification (MUSIC) are used as the adaptive beamforming, and grid-free compressive sensing is applied for the compressive sensing beamforming. Theoretical background and limitations of each technique are introduced, and the performance of each technique is compared through simulation and real experiments. The real experiments are conducted in the presence of reflected signal, transmitting a sound using two speakers and receiving acoustic data through a linear array consisting of eight microphones. Simulation and experimental results show that the adaptive beamforming and the grid-free compressive beamforming have a higher resolution than conventional beamforming when there are uncorrelated signals. On the other hand, the performance of the adaptive beamforming is degraded by the reflected signals whereas the grid-free compressive beamforming still improves the conventional beamforming resolution regardless of reflected signal presence.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.1A
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• pp.25-33
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• 2012

Random beamforming (RBF) uses the signal to interference plus noise ratio (SINR) feedback to select users in multiple-input multiple-output (MIMO) systems. A large number of users are required to obtain the gain of multi-user diversity for a downlink transmission. However, if the number is not large enough, it may be difficult to obtain multi-user diversity, leading to a rapid degradation in performance. To resolve this problem, we propose the beamforming matrix transformation and the user scheduling method. The beamforming matrix transformation scheme uses the SINRs of each users and have a better performance than conventional schemes over a small number of users. In addition, we propose the user scheduling scheme corresponding to the beamforming matrix transformation. In simulation results, we demonstrate that the sum-rate can be improved according to the number of users.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2A
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• pp.147-154
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• 2009

Antenna grouping algorithm is hybrid of beamforming and spatial multiplexing. In antenna grouping system, we partition $N_t$ transmit antennas into $N_r$ groups and use beamforming in a group, spatial multiplexing between groups. We can transmit $N_r$ data streams in the $N_t{\times}N_r$ antenna grouping system. With antenna grouping, we can achieve diversity gain through beamforming, and high spectral efficiency through spatial multiplexing. But if channel is ill-conditioned or there are some correlations between antennas, the performance of antenna grouping is seriously degraded and in that case, beamforming is the best transmit strategy. By selecting the antenna grouping mode when channel is well-conditioned and by selecting the beamforming mode when channel is ill-conditioned, we can prevent serious fluctuation of BER performance caused by varying channel condition and achieve the best BER performance. In this paper, we investigate mode selection algorithm which can select antenna grouping mode or beamforming mode. we also propose a simple mode selection criterion.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.3-8
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• 2013

Conventional MMSE beamforming scheme shows better performance than ZF or MF beamforming, but it does not aim increase of sum rate. This paper proposes sum rate maximizing scheme by representing sum rate as a function of weighted MSE. Proposed scheme increases sum rate iteratively by updating weights and beam whose initial form is conventional MMSE beam. Simulation result shows sum rate of proposed scheme is higher than those of conventional schemes and increases as the number of users increases.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.1
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• pp.24-31
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• 2009

In this paper, the new technique combing power control with Pre-FFT beamforming is proposed for MIMO(multi-input multi-output)-OFDM(orthogonal frequency division multiplexing) system. As combining the proposed power control with beamforming, we can iteratively control the transmittingpower and update the weight of beamformer together. And then, the beam is formed toward the desired direction and SNIR of each subcarrier is converged to target SNIR. Therefore, the performance of MIMO-OFDM system is very improved. BER performance improvement of the proposed approach is investigated through computer simulation by combining power allocation algorithm with MIMO-OFDM system using Pre-FFT beamformer

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.16-22
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• 2015

This paper proposes a power allocation method for multiple node beamforming with uniform circular array antennas to increase SIR of nodes in wireless mesh network. The proposed method calculates beamforming power allocation vectors that maximizes SIR satisfied with power constraint of HPA. The simulation results demonstrate the proposed method achieves the enhanced SIR of nodes than that of beamforming method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8A
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• pp.775-783
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• 2006

In this paper, the new technique combining beamforming with space-time coding is proposed for an orthogonal frequency division multiplexing(OFDM) system with multi-input multi-output(MIMO). When MIMO-OFDM system is employing Nt(the number of transmitterantenna) beamfomers and one S-T decoder at Nr receiver antennas, Nt signals removed CCI are outputted at the beamformer and then diversity gain can be got through space-time decoding. As the proposed technique can reduce cochannel interference and get diversity gain in the multi-user environment, the performance of MIMO-OFDM system is very improved. BER performance improvement and convergence behavior of the proposed approach are investigated through computer simulation by applying it to MIMO-OFDM system in the multi-user environment.