In this paper, we propose an angle of arrival (AOA)-based beamforming structure with strong interference resistant capability for OFDM systems. First, we present novel interference resistant angle of arrival (AOA) estimation schemes for each multipath without training sequences or symbols as the pre-processing of the proposed structure. The generalized sidelobe canceler (GSC) structure is thus applied with the AOA information to avoid calculating the beamforming weight vector individually on a per subcarrier basis, wherein the GSC structure with the reduced-rank multistage Wiener filter (MSWF) is adopted. We also propose a signal transformation scheme to improve performance before the signals are fed into the GSC receiver. The proposed receiver offers better performance than the GSC form of the constrained Wiener filter-based receiver due to the faster convergence property of reduced rank processing and the signal transformation scheme.

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.

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.

This paper presents two types of two-dimensional (2-D) adaptive beamforming algorithm which have high rate of convergence. One is a linearly constrained minimum variance (LCMV) beamforming algorithm which minimizes the average output power of a beamformer, and the other is a generalized sidelobe canceler (GSC) algorithm which generalizes the notion of a linear constraint by using the multiple linear constraints. In both algorithms, we apply a 2-D lattice filter to an adaptive filtering since the 2-D lattice filter provides excellent properties compared to a transversal filter. In order to evaluate the validity of the algorithm, we perform computer simulations. The experimental results show that the algorithm can reject interference signals while maintaining the direction of desired signal, and can improve convergent performance.

The sidelobe canceler in radar systems is a highly computational demanding problem. It can be efficiently tackled by resorting to the QR decomposition mapped onto a systolic array processor. The paper reports several mapping strategies by using massive parallel computers available on the market. MIMD as well as SIMD machines have been used, specifically MEIKO Computing Surface, nCUBE2, Connection Machine CM-200, and MasPar MP-1. The achieved data throughput values have been measured for a number of operational situations of practical interest.