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.

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 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, 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.

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.