Adaptive beamformer

About: Adaptive beamformer is a research topic. Over the lifetime, 4934 publications have been published within this topic receiving 93100 citations.

Bi-Directional Training for Adaptive Beamforming and Power Control in Interference Networks

Abstract: We study distributed algorithms for adapting transmit beamformers and linear receiver filters in a Time-Division Duplex Multiple-Input Multiple-Output (MIMO) interference network Each transmitter transmits a single beam, and neither the transmitters nor receivers have a priori Channel State Information (CSI) Given a fixed set of powers, we present an adaptive version of the Max-SINR algorithm: pilot symbols are alternately transmitted in the forward direction (transmitters to receivers) and in the reverse direction (receivers to transmitters) Unlike previous channel estimation schemes, transmissions in each direction are synchronized across the source or destination nodes, and the pilots are used to update the filters/beams directly using a least squares criterion To improve the performance with limited training, we include exponential weighting of the least squares objective across data frames In addition, bi-directional training can be used to implement analog interference pricing for power control: training in the forward direction is used to measure received signal-to-interference plus noise ratios (SINRs) and interference prices, and those estimates combined with synchronous backward training are used to update the powers Given sufficient training this method achieves the same performance as interference pricing updates with perfect CSI Numerical results are presented that illustrate the performance of these methods in different settings

New Designs on MVDR Robust Adaptive Beamforming Based on Optimal Steering Vector Estimation

Abstract: The robust adaptive beamforming design problem based on estimation of the signal-of-interest (SOI) steering vector is considered in the paper. The common criteria to find the best estimate of the steering vector are the beamformer output signal-to-noise-plus-interference ratio (SINR) and output power, while the constraints assume as little as possible prior inaccurate knowledge about the SOI, the propagation media, and the antenna array. Herein, in order to find the optimal steering vector, a beamformer output power maximization problem is formulated and solved subject to a double-sided norm perturbation constraint, a similarity constraint, and a quadratic constraint that guarantees that the direction-of-arrival (DOA) of the SOI is away from the DOA region of all linear combinations of the interference steering vectors. The prior knowledge required is some allowable error norm bounds and approximate knowledge of the antenna array geometry and angular sector of the SOI. It turns out that the array output power maximization problem is a non-convex quadratically constrained quadratic programming problem with inhomogeneous constraints. However, we show that the problem is still solvable, and develop efficient algorithms for finding globally optimal estimate of the SOI steering vector. The results are generalized to the case when an ellipsoidal constraint is considered instead of the similarity constraint, and sufficient conditions for the global optimality are derived. In addition, a new quadratic constraint on the actual signal steering vector is proposed in order to improve the array performance. To validate our results, simulation examples are presented, and they demonstrate the improved performance of the new robust beamformers in terms of the output SINR as well as the output power.

An Improved Adaptive Sidelobe Blanker

Abstract: We propose a two-stage detector consisting of a subspace detector followed by the whitened adaptive beamformer orthogonal rejection test. The performance analysis shows that it possesses the constant false alarm rate property with respect to the unknown covariance matrix of the noise and that it can guarantee a wider range of directivity values with respect to previously proposed two-stage detectors. The probability of false alarm and the probability of detection (for both matched and mismatched signals) have been evaluated by means of numerical integration techniques.

Parallel spatial processing: A cure for signal cancellation in adaptive arrays

Abstract: A spatial processing algorithm with parallel structure is presented for the prevention of signal caneellation phenomena in conventional adaptive arrays. This algorithm basically uses a parallel structure with a spatial averaging effect to combat coherent jamming. It results in a spatially smoothed maximum-likelihood estimate of the desired signal when the adaptive beamformer converges. Simulations have been conducted which verify the effectiveness of the proposed structure.

Experimental evaluation of a nested microphone array with adaptive noise cancellers

Abstract: This paper proposes a near-field broadband adaptive beamforming scheme for intelligent computer telephony and teleconferencing applications, namely the nested microphone array with adaptive noise canceller (NMA-ANC). The NMA-ANC scheme incorporates an harmonically nested array with a nonuniformly subbanded multirate filter bank. Each subband array employs several near-field delay-filter-and-sum beamformers and an adaptive noise canceller (ANC). The proposed NMA-ANC is evaluated via a noise rejection experiment and dereverberation experiment performed in an anechoic chamber and a real conference room, respectively. The experiment data are recorded by a multichannel digital recording system developed using commercial off-the-shelf (COTS) equipments. A perceptual analysis/measurement system (PAMS) test is also carried out using a COTS digital speech level analyzer. The results of the experimental evaluation and PAMS test show that the proposed NMA-ANC scheme is able to improve the sound quality by adaptively rejecting multiple interfering signals and attenuating the reverberant noises and avoiding the desired signal cancellation.