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.

In conjunction with a first-order Taylor series approximation of the spatial scanning vector, this letter presents an iterative multiple signal classification (MUSIC) direction-of-arrival (DOA) estimation for code-division multiple access signals. This approach leads to a simple one-dimensional optimization problem to find each iterative optimal search grid. It can not only accurately estimate DOA, but also speed up the estimating process. Computer results demonstrate the effectiveness of the proposed algorithm.

This Letter deals with the problem of non-line-of-sight (NLOS) in cellular systems devoted to location purposes. In conjugation with a variable loading technique, we present an efficient technique to make covariance shaping least squares estimator has robust capabilities against the NLOS effects. Compared with other methods, the proposed improved estimator has high accuracy under white Gaussian measurement noises and NLOS effects.

This letter presents an improved hybrid direction of arrival (DOA) estimation scheme with computational efficiency for massive uniform linear array. In order to enhance the resolution of DOA estimation, the initial estimator based on the discrete Fourier transform is applied to obtain coarse DOA estimates by a virtual array extension for one snapshot. Then, by means of a first-order Taylor series approximation to the direction vector with the one initially estimated in a very small region, the iterative fine estimator can find a new direction vector which raises the searching efficiency. Simulation results are provided to demonstrate the effectiveness of the proposed scheme.

In this letter, we present a blind carrier frequency offset (CFO) estimator by exploiting the subspace-based technique for multicarrier-code division multiple access (MC-CDMA) systems. Relative high accuracy and low-complexity to the CFO estimation can be achieved by rooting a polynomial. Simulation results are provided for illustrating the effectiveness of the proposed blind polynomial rooting estimator.

In this letter, standard particle swarm optimization (PSO) with the center-symmetric trimmed correlation matrix and the orthogonal projection technique is firstly presented for blind carrier frequency offset estimation under interleaved orthogonal frequency division multiple access (OFDMA) uplink systems. It doesn't require eigenvalue decomposition and only needs a single OFDMA data block. Second, this letter also presents adaptive multiple inertia weights with Newton method to speed up the convergence of standard PSO iteration process. Meanwhile, the advantage of inherent interleaved OFDMA signal structure also is exploited to conquer the problems of local optimization and the effect of ambiguous peaks for the proposed approaches. Finally, several simulation results are provided for illustration and comparison.

This paper deals with adaptive array beamforming based on stochastic gradient descent independent component analysis (ICA) for suppressing interference with robust capabilities. The approach first uses estimates of the interested source directions to construct the multiple regularized constraints, which form an efficient ICA-based beamformer to achieve fast convergence and more robust capabilities than existing MCMV and ESB beamformers. In conjunction with the regularization parameters of the high-order derivative constraints, the width of the main beam for remaining the desired signal and the depth of nulls for suppressing interferers can be adjusted. Several computer simulation examples are provided for illustration and comparison.

In this letter, an efficient hybrid direction-of-arrival (DOA) estimation scheme is devised for massive uniform rectangular array. In this scheme, the DOA estimator based on a two-dimensional (2D) discrete Fourier transform is first applied to acquire coarse initial DOA estimates for single data snapshot. Then, the fine DOA is accurately estimated through using the iterative search estimator within a very small region. Meanwhile, a Nyström-based method is utilized to correctly compute the required noise-subspace projection matrix, avoiding the direct computation of full-dimensional sample correlation matrix and its eigenvalue decomposition. Therefore, the proposed scheme not only can estimate DOA, but also save computational cost, especially in massive antenna arrays scenarios. Simulation results are included to demonstrate the effectiveness of the proposed hybrid estimate scheme.