This letter deals with multiuser detection under imprecise knowledge of the received signature code of desired user. In order to improve the revision capability for spread-signature mismatch, an enhanced subspace-based (SSB) technique is developed. By incorporating the orthogonal property of spreading codes into the SSB algorithm, the proposed technique not only can correct the spread-signature mismatch, but also can decorrelate the spreading codes in asynchronous DS-CDMA system. Significant performance improvement of the enhanced SSB technique is demonstrated by simulation results.

This letter deals with mobile location estimation based on a minimax mean-squared error (MSE) algorithm using time-of-arrival (TOA) measurements for mitigating the nonline-of-sight (NLOS) effects in cellular systems. Simulation results are provided for illustrating the minimax MSE estimator yields good performance than the other least squares and weighted least squares estimators under relatively low signal-to-noise ratio and moderately NLOS conditions.

This letter deals with the carrier frequency offsets (CFO) estimation problem for orthogonal frequency division multiple access (OFDMA) uplink systems. Combined with centro-symmetric (CS) trimmed autocorrelation matrix and weighting subspace projection, the proposed estimator has better estimate performance than MVDR, MUSIC, CS-MUSIC, and ESPRIT estimators, especially in relatively less of OFDMA blocks and low SNR situations. Simulation results are presented to verify the efficiency of the proposed estimator.

This letter presents an effective direction of arrival (DOA) estimator that is based on the orthogonal projection (OP) technique. When an OP matrix is attained, the proposed estimator, which dispenses with spatial smoothing (SS) preprocessing, can form the maximizing orthogonality for a single snapshot. Since this technique does not need to perform eigen-decomposition while maintaining better DOA estimates, it also has real-time DOA estimation capability. Numerical results are presented to illustrate the efficiency of this method.

In this letter, we present a normalized least-mean-square algorithm of blind estimator for carrier frequency offset estimation of orthogonal frequency division multiplexing systems. In conjunction with the closed-loop estimate structure, the proposed efficient algorithm eliminates the inter-carrier interference for time varying carrier frequency offset. The proposed algorithm offers faster convergence speed and more accuracy to the carrier frequency offset estimate. Several computer simulation examples are presented for illustrating and effectiveness of the proposed algorithm.

In this letter, two types of blind adaptive frequency offset estimator for multicarrier code division multiple access systems are proposed that do not need any specific training sequence. It can not only accurately estimate the frequency offset, but also improve the revision capability and convergence rate. Several computer simulations confirm the effectiveness of the blind estimate approaches.

Using eigenstructure approach to form interference canceler is very sensitive to pointing error, especially when the interference number is overestimated. This Letter presents an effective technique to correct the pointing error by the projection matrix of noise subspace. Based on the corrected steering angle, a proper blocking matrix of the eigenstructure interference canceler can be obtained to suppress the leakage of desired signal. Therefore, signal cancellation does not occur, even the interference number is overestimated in constructing the interference subspace.

This letter deals with direction-of-arrival (DOA) estimate problem based on gravitational search algorithm (GSA) with multiple signal classification (MUSIC) criterion for code-division multiple access (CDMA) signals. It has been shown that the estimate accuracy of the searching-based MUSIC estimator strictly depends on the number of search grids used during the search process, which is time consuming and the required number of search grids is not clear to determine. In conjunction with the GSA-based optimization, the high resolution DOA estimation can be obtained; meanwhile the searching grid size is no need to know previously. In this letter, we firstly present a GSA-based DOA estimator with MUSIC criterion under high interferer-to-noise ratio circumstances. Second, for the purpose to increase the estimation accuracy, we also propose an improved GSA with adaptive multiple accelerations, which depend on Newton-Raphson method. Several computer simulations are provided for illustration and comparison.

In this Letter, we propose a least mean square (LMS) with adaptive step-size (AS) algorithm for adaptive blind carrier frequency offset (CFO) estimation in the orthogonal frequency division multiplexing system. In conjunction with the closed-loop estimate structure, the proposed algorithm eliminates the inter-carrier interference caused by time varying CFO. To improve the convergence performance of the fixed step-size LMS estimator, the regular AS LMS algorithm offers faster convergence speed and more accuracy to the CFO estimate. Several computer simulation examples are presented for illustrating the effectiveness of the proposed algorithm.

In this letter, the orthogonal projection (OP) estimation of the direction of arrival (DOA) and direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output radars is addressed. First, a two-dimensional direction finding estimator based on OP technique with automatic pairing is developed. Second, this letter also presents a modified reduced-dimension estimator by utilizing the characteristic of Kronecker product, which only performs two one-dimensional angle estimates. Furthermore, the DOA and DOD pairing is given automatically. Finally, simulation results are presented to verify the efficiency of the proposed estimators.

This letter realizes direction of arrival (DOA) estimation by exploiting the noise subspace based estimator. Since single subspace feature extraction fails to achieve satisfactory results under unknown noise fields, we propose a two-step subspace feature extraction technique that is effective even in these fields. When a new noise subspace is attained, the proposed estimator without prewhitening can form the maximizing orthogonality especially for unknown noise fields. Simulation results confirm the effectiveness of the proposed technique.

This letter deals with adaptive array beamforming based on a minimum variance distortionless response (MVDR) technique with robust capabilities for code-division multiple access signals. It has been shown that the MVDR beamformer suffers from the drawback of being very sensitive to pointing error over the eigenspace-based beamformers. For the purpose of efficient estimation and calibration, a highly efficient approach has been proposed that is implemented on polynomial rooting rather than spectral searching. However, this rooting method is suboptimal in the presence of the noise and multiple access interference (MAI). In this letter, we propose an improved polynomial rooting calibration method that is robust in both of the low signal-to-noise ratio and large MAI scenarios. Several computer simulations are provided for illustrating the effectiveness of the proposed method.

This letter deals with multiuser detection under imprecise knowledge of the received signature codes of all active users for multicarrier code division multiple access (MC-CDMA) systems. The weight vector of the modified multiple constrained minimum variance (MMCMV) is found by projecting the multiple constrained minimum variance (MCMV) weight vector onto a vector subspace constructed from the eigenstructure of the correlation matrix. However, MMCMV still cannot handle the large code-mismatch. Shaping the noise subspace with all estimated active spreading codes, we present an effective approach to achieve more robust capabilities than the MMCMV. Computer simulations show the effectiveness of the proposed detector.

It is well known that the performance of CDMA systems may degrade in the presence of spreading code mismatch. The diagonal loading multiple constrained minimum variance (DL-MCMV) approaches have been proposed to deal with the mismatch problem. However, they still cannot improve the robust capability efficiently due to the spreading code mismatch. In this letter, a detector based on the variable DL technique is presented that offers more robust capabilities than the MCMV and DL-MCMV detectors. Computer simulation results are provided that illustrate the effectiveness of the proposed detector.

The letter deals with direction-of-arrival (DOA) estimation under nonuniform white noise and moderately small signal-to-noise ratios. The proposed approach first uses signal subspace projection for received data vectors, which form an efficient iterative quadratic maximum-likelihood (IQML) approach to achieve fast convergence and high resolution capabilities. In conjunction with a signal subspace selection technique, a more exact signal subspace can be obtained for reducing the nonuniform noise effect. The performance improvement achieved by applying the proposal to the classic IQML method is confirmed by computer simulations.

The performance of the least-mean-square (LMS) beamformer is heavily dependent on the choice of the step-size, for it governs the convergence rate and steady-state excess mean squared error. To meet the conflicting requirement of low misadjustment, especially for the beamformer being modified in response to the multipath environmental changes, it needs to be controlled in a proper way. In this letter, we present an efficient adaptive step-size subarray LMS to achieve good performance. Simulation results are provided for illustrating the effectiveness of the proposed scheme.

This letter presents an adaptive H∞ array beamforming scheme based on a generalized sidelobe canceller with lower computational load. It is shown that the adaptive H∞-based beamformer offers the advantages of faster convergence speed, insensitivity to dynamic estimation modeling error, and less sensitivity to pointing error over the conventional adaptive H∞ algorithm. Simulations confirm that the proposed technique achieves similar array performance of the adaptive H∞-based algorithm [4].

It was previously shown that the number of array elements must exceed the number of sources for multiple target direction of arrival (DOA) tracking. This is clearly not practical for code-division multiple access (CDMA) communications since the number of mobile users is very large. To overcome the restriction, adaptive angle tracking approaches employing the code-matched filters and parallel Kalman/H∞ algorithms are presented in this paper. The proposed approaches are applied to the base station of a mobile communication system. Different from Kalman prediction algorithm which minimize the squared tracking error, the adaptive H∞ filtering algorithm is a worst case optimization. It minimizes the effect of the worst disturbances (including modeling error of direction matrix models and array structure imperfection, process noise, and measurement noise). Hence, the difficult problem of tracking the crossing mobiles can be successfully handled by using the code-matched filters. Computer simulation is provided for illustrating the effectiveness of the adaptive angle tracking approaches.

This letter deals with eigenspace-based (ESB) beamforming based on the decision-directed (DD) correction with robust capability. It has been shown that the output of the ESB beamformer includes the desired signal and noise under small pointing errors. In conjugation with DD and soft decision decoding scheme, the proposed approach can be used to form a robust DD-ESB beamformer without any specific training sequence. Computer simulations are provided to illustrate the effectiveness of the proposed beamformer.

This letter deals with blind carrier frequency offset estimation by exploiting the minimum variance distortionless response (MVDR) criterion for interleaved uplink orthogonal frequency division multiple access (OFDMA). It has been shown that the complexity and estimation accuracy of MVDR strictly depend on the grid size used during the search. For the purpose of efficient estimation, we present an improved polynomial rooting estimator that is robust in low signal-to-noise ratio scenario. Simulation results are provided for illustrating the effectiveness of the proposed estimator.