This letter presents an adaptive beamforming algorithm for an MC-CDMA system with adaptive antenna array. The proposed adaptive beamforming algorithm for the MC-CDMA systems is derived by (1) calculating the error signals between the pilot symbols of desired user and the received pilot signals in the frequency-domain, (2) transforming the frequency-domain error signals into time-domain error signals, (3) updating the filter coefficients of the adaptive beamformer in the direction of minimizing the MSE. Convergence behavior and user-capacity improvement of the proposed approach are demonstrated through computer simulation by applying it to the MC-CDMA system in the presence of interferences from other users.

In this paper, we present a new approach for the design of partially adaptive broadband beamformers with the generalized sidelobe canceller (GSC) as an underlying structure. The approach designs the blocking matrix involved by utilizing a set of P-regular, M-band wavelet filters, whose vanishing moment property is shown to meet the requirement of a blocking matrix in the GSC structure. Furthermore, basing on the subband decomposition property of these wavelet filters, we introduce a new dynamic subband selection scheme succeeding the blocking matrix. The scheme only retains the principal subband components of the blocking matrix outputs based on a prescribed statistical hypothesis test and thus further reduces the dimension of weights in adaptive processing. As such, the overall computational complexity, which is mainly dictated by the dimension of adaptive weights, is substantially reduced. The furnished simulations show that this new approach offers comparable performance as the existing fully adaptive beamformers but with reduced computations.

A new method of designing a microphone array with two outputs preserving binaural information is proposed in this paper. This system employs adaptive beamforming using multiple constraints. The binaural cues may be preserved in the two outputs by use of these multiple constraints with simultaneous beamforming to enhance target signals is also available. A computer simulation was conducted to examine the performance of the beamforming. The results showed that the proposed array can perform both the generation of the binaural cues and the beamforming as intended. In particular, beamforming with double-constraints exhibits the best performance; DI is around 7 dB and good interchannel (interaural) time/phase and level differences are generated within a target region in front. With triple-constraints, however, the performance of the beamforming becomes poorer while the binaural information is better realized. Setting of the desired responses to give proper binaural information seems to become critical as the number of the constraints increases.

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.

High-resolution algorithms for the detection and estimation of Directions Of Arrival (DOA) such as MUSIC, lead to accurate results but require the computation of the noise-subspace through an expensive covariance matrix eigendecomposition. Adaptive estimators of the noise-subspace can be very useful in a non-stationary environment when the convergence is possible with a few number of snapshots. Some adaptive methods are presented showing that an indirect noise-subspace estimation through a signal subspace estimation can be advantageous both in terms of convergence rate and computation complexity during each update. Some computer simulations examples showing performances are provided.