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.

This letter deals with robust interference suppression based on eigenanalysis interference canceller (EIC) with the joint code-aid and noise subspace-based correcting approach. It has been shown that the EIC is very sensitive to pointing error, especially when the interference number is overestimated. Based on the corrected steering angle, a proper blocking matrix of the EIC can be obtained to suppress the leakage of desired signal. Therefore, desired signal cancellation does not occur; even if the interference number is overestimated in constructing the interference subspace. Several computer simulations are provided to demonstrate the effectiveness of the proposed approach.

In this letter, blind adaptive H multiuser detection is developed by employing a generalized sidelobe canceler (GSC) with and without subweight partition scheme. It is shown that the adaptive H algorithm with subweight approach has the advantages of fast convergence speed, insensitivity of dynamic estimate error, and suitability for arbitrary ambient noise over the conventional H and the RLS-based adaptive algorithms.

In this paper, a new adaptive method is suggested using the complementally transformed minimum variance technique for the purpose of suppressing interference in additive white and colored Gaussian noise channels. The method is based on interference suppression by way of the resulting projection weight. The multiple access causes an interference problem in the code-division multiple access systems. An efficient adaptive algorithm should be used to suppress this interference for the improvement of system performance. Analytical and simulation results show that the new adaptive method has fast convergence rate and offers significant performance gain over the conventional detector, the MMSE detector, and the linear decorrelator. Finally, multipath fading induced performance loss, which leads to error probability floor, is established for the proposed method with combining schemes and shown by computer simulation.

In this letter, a generalized sidelobe canceller (GSC) with robustness against carrier frequency offset (CFO) is proposed for the uplink MC-CDMA system. It has been shown that a CFO will cause the spreading code mismatch and desired signal cancellation. By incorporating the corrected quiescent weight of the upper branch and blocking matrix of the lower branch, we create an efficient GSC that offers strongly counters the effect of the CFO. Significant performance improvement of the proposed GSC is demonstrated by simulation results.

This letter presents an efficient hybrid direction of arrival (DOA) estimation scheme for massive uniform linear array. In this scheme, the DOA estimator based on a discrete Fourier transform (DFT) is first applied to acquire coarse initial DOA estimates for single data snapshot. And then, the fine DOA is accurately estimated through using the iterative search estimator within a very small region. It iteratively searches for correct DOA vector by minimizing the objective function using a Taylor series approximation of the DOA vector with the one initially estimated. Since the proposed scheme does not need to perform eigen-decomposition and spectrum search while maintaining better DOA estimates, it also has low complexity and real-time capability. Simulation results are presented to demonstrate the efficiency of the proposed scheme.

This letter presents a subspace-based technique with generalized sidelobe canceler structure, which can be utilized to deal with the desired user's SNR < 0 dB. With an estimate scheme of the desired user code, the proposed method offers more robustness against spreading code mismatch. Computer simulations show that the effectiveness of the proposed detector.

A minor component analysis approach based on the generalized sidelobe canceler is presented to realize the blind suppression of multiple-access interference in multicarrier code division multiple access systems. With a rough user-code and timing estimations, this proposed method of less computation performs the same as minimum mean square error detectors and outperforms existing blind detectors. Simulation results illustrate the effectiveness of the blind multiuser detection.

Localization of mobile terminals has received considerable attention in wireless communications. In this letter, we present a covariance shaping least squares (CSLS) estimator using time-of-arrival measurements of the signal from the mobile station received at three or more base stations. It is shown that the CSLS estimator yields better performance than the other LS estimators at low signal-to-noise ratio conditions.

This letter deals with blind multiuser detection based on the multi-channel linearly constrained constant modulus algorithm (MLCCMA) for asynchronous code division multiple access (CDMA) systems over frequency-selective Rayleigh fading channels. In conjunction with the decision-feedback generalized sidelobe canceller (DFGSC), we present an efficient approach to combat multiple access interference and intersymbol interference. Computer simulations confirm that the proposed MLCCMA-based DFGSC can significantly speed up convergence and improve the output performance.

This paper deals with carrier frequency offset (CFO) estimation based on the minimum variance distortionless response (MVDR) criterion without using specific training sequences for interleaved orthogonal frequency division multiple access (OFDMA) uplink systems. In the presence of large CFOs, the estimator is proposed to find a new CFO vector based on the first-order Taylor series expansion of the one initially given. The problem of finding the new CFO vector is formulated as the closed form of a generalized eigenvalue problem, which allows one to readily solve it. Since raising the accuracy of residual CFO estimation can provide more accurate residual CFO compensation, this paper also present a decision-directed MVDR approach to improve the CFO estimation performance. However, the proposed estimator can estimate CFOs with less computation load. Several computer simulation results are provided for illustrating the effectiveness of the proposed blind estimate approach.