• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1A
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• pp.84-92
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• 2004

Eigenstructure-based adaptive beamfoming has advantages of fast convergence and the insentivity to errors in the arrival angle of the desired signal. Eigen-decomposing the sample matrix to extract a basis for the Sl (signal plus interference) subspace, however, is very computationally expensive. In this paper, we present a simple subspace based beamforming which utilizes off-diagonal elements of the sample matrix to estimate the Sl subspace. The outputs of overlapped subarrays are combined to produce the final adaptive output, which improves SINR (signal-to-interference-plus-noise ratio) comapred to exploiting a single subarray. The proposed adaptive beamformer, which employs an efficient angle estimation is very roubust to errors in both the arrival angles and the number of the incident signals, while the eigenstructure-based beamforer suffers from severe performance degradation.

• Journal of Industrial Technology
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• v.31 no.B
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• pp.3-7
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• 2011

This paper addresses a computationally simple adaptive beamforming method to cancel interferences arriving onto a sensor array. In the proposed method, an estimate of the interference subspace is extracted from a submatrix of the sample covariance matrix and an orthonormal basis for the estimated subspace is efficiently found, one basis vector being updated every sample. Its computational burden is just $O(M{\eta})$ in an M-sensor array when ${\eta}$ directional signals are present. The new method does not make any premises of the geometrical structure of arrays, and can be applied to arbitrary arrays.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4A
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• pp.269-277
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• 2012

When there are mismatches between the beamforming steering vector and the array response vector for the desired signal, the performance can be severely degraded as the adaptive array attempts to suppress the desired signal as well as interferences. In this paper, an robust method is proposed for the adaptive array in the presence of both direction errors and random errors in the steering vector. The proposed method first finds a signal-plus-interference subspace (SIS) from the correlation matrix, which in turn is exploited to extract an interference subspace based on the structure of a uniform linear array (ULA), the effect of the desired signal direction vector being reduced as much as possible. Then, the weight vector is attained to be orthogonal to the interference subspace. Simulation shows that the proposed method, in terms of signal-to-interference plus noise ratio (SINR), outperforms existing ones such as the doubly constrained robust Capon beamformer (DCRCB).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.162-170
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• 2010

Adaptive arrays reject interferences while preserving the desired signal, exploiting a priori information on its arrival angle. Subspace-based adaptive arrays, which adjust their weight vectors in the signal subspace, have the advantages of fast convergence and robustness to steering vector errors, as compared with the ones in the full dimensional space. However, the complexity of theses subspace-based methods is high because the eigendecomposition of the covariance matrix is required. In this paper, we present a simple subspace-based method based on the PASTd (projection approximation subspace tracking with deflation). The orignal PASTd algorithm is modified such that eigenvectora are orthogonal to each other. The proposed method allows us to significantly reduce the computational complexity, substantially having the same performance as the beamformer with the direct eigendecomposition. In addition to the simple beamforming method, we present theoretical analyses on the SINR (signal-to-interference plus noise ratio) of subspace beamformers to see their behaviors.

• Phonetics and Speech Sciences
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• v.4 no.3
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• pp.103-110
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• 2012

In this paper, a target signal detection method using multiple signal classification (MUSIC) algorithm is proposed. The MUSIC algorithm is a subspace-based direction of arrival (DOA) estimation method. Using the inverse of the eigenvalue-weighted eigen spectra, the algorithm detects the DOAs of multiple sources. To apply the algorithm in target signal detection for GSC-based beamforming, we utilize its spectral response for the DOA of the target source in noisy conditions. The performance of the proposed target signal detection method is compared with those of the normalized cross-correlation (NCC), the fixed beamforming, and the power ratio method. Experimental results show that the proposed algorithm significantly outperforms the conventional ones in receiver operating characteristics (ROC) curves.

• The Journal of the Acoustical Society of Korea
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• v.35 no.5
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• pp.395-402
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• 2016

In this paper, a wideband adaptive beamforming approach for an acoustic vector sensor linear array is presented. It is a very important issue to estimate the stable covariance matrix for adaptive beamforming. In the conventional wideband adaptive beamforming based on coherent signal-subspace (CSS) processing, the error of bearing estimates is resulted from the focusing matrix estimation and the large number of data snapshot is necessary. To alleviate the estimation error and snapshot deficiency in estimating covariance matrix, the steered covariance matrix method in the pressure sensor is extended to the vector sensor array, and the subarray technique is incorporated. By this technique, more accurate azimuth estimates and a stable covariance matrix can be obtained with a small number of data snapshot. Through simulation, the azimuth estimation performance of the proposed beamforming method and a wideband adaptive beamforming based on CSS processing are assessed.

• ETRI Journal
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• v.40 no.6
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• pp.714-725
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• 2018

Destination-assisted jamming (DAJ) is usually used to protect confidential information against untrusted relays and eavesdroppers in wireless networks. In this paper, a DAJ-based untrusted relay network with multiple antennas installed is presented. To increase the secrecy, a joint optimization of beamforming and power allocation at the source and destination is studied. A matched-filter precoder is introduced to maximize the cooperative jamming signal by directing cooperative jamming signals toward untrusted relays. Then, based on generalized singular-value decomposition (GSVD), a novel transmitted precoder for confidential signals is devised to align the signal into the subspace corresponding to the confidential transmission channel. To decouple the precoder design and optimal power allocation, an iterative algorithm is proposed to jointly optimize the above parameters. Numerical results validate the effectiveness of the proposed scheme. Compared with other schemes, the proposed scheme shows significant improvement in terms of security performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.306-314
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• 2004

Some receiver(and most transmit) beamforming algorithms with an array antenna at a cellular CDMA base stations require accurate internal and external calibrations. The external calibration, which usually needs to be done only once, determines the array manifolds, i.e. the complex response of each antenna as a function of DOA(Directions of Arrival). The internal calibrations are necessary because characteristics of RF/IF circuity of each receiver chain vary differently in response to temperature or humidity changes. We propose an iterative subspace-based calibration algorithm for an asynchronous CDMA-based antenna away in the presence of unknown gain and phase error is presented. We verify the subspace-based calibration algorithms by performing the experiment using measured data. Also, we propose an efficient algorithm using the simulated annealing technique. This algorithm overcomes the problem of the initial guessing in the subspace-based approach.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.2
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• pp.580-592
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• 2012

In this paper, a new compressive feedback (CF) scheme based on distributed compressed sensing (DCS) for time-corrected MIMO channel is proposed. First, the channel state information (CSI) is approximated by using a subspace matrix, then, the approximated CSI is compressed using a compressive matrix. At the base station, the approximated CSI can be robust recovered with simultaneous orthogonal matching pursuit (SOMP) algorithm by using forgone CSIs. Simulation results show our proposed DCS-CF method can improve the reliability of system without creating a large performance loss.

• Journal of the Korea Society of Computer and Information
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• v.9 no.2
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• pp.97-104
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• 2004

As a channel of a DS-CDMA system is shared among several users, the receivers face the problem of MAI. Also the bandlimited channel leads to ISI. Both components are undesired, but unlike the additive noise process, which is usually completely unpredictable, their space-time structure helps to estimate and remove them. This paper investigates a DS-CDMA system with a fading multipath channel. The investigations have been separated into a channel estimation part and a reception part. In the estimation part of seperated two parts, the multipath parameters such as DOA and TOA are evaluated in this paper. In the part of receiver. we used these parameters and tested the performance of this receiver about space-time beamformers. To assess many different estimation techniques and beamformers, the simulation compared with theoretical values is performed.