Blind Adaptive Beamforming Algorithm Research Articles

Blind Adaptive Beamforming for a Global Navigation Satellite System Array Receiver Based on Direction Lock Loop

The adaptive beamforming algorithm can realize interference suppression and navigation signal enhancement, and has been widely used. However, achieving high-precision real-time estimation of the direction of arrival (DOA) parameters of navigation signals in strong-interference scenarios with low complexity is still a challenge. In this paper, a blind adaptive beamforming algorithm for a Global Navigation Satellite System (GNSS) array receiver based on direction lock loop is proposed without using the prior information of the DOA parameter. The direction lock loop is used for DOA tracking and estimation after interference suppression, which uses the spatial correlation of the array beam pattern to construct a closed direction-tracking loop. The DOA estimation value is adjusted in real time based on the loop errors. A blind beamformer is constructed using the DOA estimation results to provide gain by forming a beam in the satellite direction. This method improves the accuracy and dynamic adaptability of DOA estimation while significantly reducing the computational complexity. The theoretical analysis and simulation results verify the effectiveness of the proposed algorithm.

Robust adaptive beamforming using modified constant modulus algorithms

Abstract This paper addresses the self-nulling phenomenon also known as the self-cancellation in adaptive beamformers. Optimum beamforming requires knowledge of the desired signal characteristics, either its statistics, its direction-of-arrival, or its response vector. Inaccuracies in the required information lead the beamformer to attenuate the desired signal as if it were interference. Self-nulling is caused by the desired signal having large power (high SNR) relative to the interference signal in case of the minimum variance distortion less response beamformer, and low power desired signal in the case of the constant modulus algorithm (CMA) beamformer, which leads the beamformer to suppress the desired signal and lock onto the interference signal. The least-square constant modulus algorithm is a prominent blind adaptive beamforming algorithm. We propose two CMA-based algorithms which exploit the constant modularity as well as power or DOA of the desired signal to avoid self-nulling in beamforming. Simulations results verify the effectiveness of the proposed algorithms.

Far-Field RF Wireless Power Transfer with Blind Adaptive Beamforming for Internet of Things Devices

Wireless power transfer (WPT) has long been one of the main goals of Nikola Tesla, the forefather of electromagnetic applications. In this paper, we investigate radio-frequency beamforming in the radiative far field for WPT. First, an analytical model of the channel fading is presented, and a blind adaptive beamforming algorithm is adapted to the WPT context. The algorithm is computationally light, because we need not explicitly estimate the channel state information. Then, a testbed with a multiple-antenna software-defined radio configuration on the transmitting side and a programmable energy harvester on the receiving side is developed in order to validate the algorithm in this specific power application. From the results, it can be seen that the implementation of this version of beamforming indeed improves the harvested power. Specifically, at various distances from 50 cm to 1.5 m, the algorithm converges with two, three, and four antennas with an increasing gain as we increase the number of antennas. These encouraging results could have far-reaching consequences in providing wireless power to Internet of Things devices, our target application.

A Multiantenna RFID Reader With Blind Adaptive Beamforming

A passive ultra-high frequency (UHF) RF identification (RFID) system is proposed that employs multiple antennas at the reader and single antenna at each tag. The gain due to multiple antennas in terms of the maximum reader interrogation range is first quantified. Then, a blind adaptive beamforming (BABF) algorithm that does not require the channel state information (CSI) is presented to improve both the interrogation range and the data transmission performance of the system in both the full- and half-duplex configurations. Moreover, an estimator for the number of tags within the reader interrogation range is proposed to enhance the system throughput. Simulation results show that both the interrogation range and the packet error rate (PER) performance for data transmission can be improved significantly using multiple antennas at the reader. A Universal Software Radio Peripheral (USRP)-based prototype system is implemented to validate the interrogation range improvement by employing multiple-antenna readers with several beamforming schemes. The proposed multiantenna RFID reader with the BABF complies with the existing RFID standard and can be readily implemented in existing systems.

A low-complexity variable forgetting factor constant modulus RLS algorithm for blind adaptive beamforming

In this paper, a recursive least squares (RLS) based blind adaptive beamforming algorithm that features a new variable forgetting factor (VFF) mechanism is presented. The beamformer is designed according to the constrained constant modulus (CCM) criterion, and the proposed adaptive algorithm operates in the generalized sidelobe canceler (GSC) structure. A detailed study of its operating properties is carried out, including a convexity analysis and a mean squared error (MSE) analysis of its steady-state behavior. The results of numerical experiments demonstrate that the proposed VFF mechanism achieves a superior learning and tracking performance compared to other VFF mechanisms.

Efficient Robust Blind Beamforming Algorithm

Because blind adaptive beamforming algorithms do not depend on any reference signal, they have found numerous important applications in signal processing. However, the conventional constrained constant modulus algorithm (CMA) may suffer significant performance degradation in the presence of the slight mismatches between the actual and assumed signal steering vectors. In this paper, to combat the mismatches, a novel robust constrained CMA is proposed for implementing double constraints with recursive method updating, which is based on explicit modeling of uncertainties in the desired signal array response. The proposed robust constrained CMA provides an improved robustness against the signal steering vector mismatches, enhances the array system performance under random perturbations in sensor parameters and makes the mean output array SINR consistently close to the optimal one. The performance of the proposed algorithm is compared with that of linear constrained CMA algorithm by computer simulations, the results of which demonstrate a marked improvement in the robustness against signal steering vector mismatches.

Fast Blind Adaptive Beamforming Algorithm With Interference Suppression

A fast blind adaptive beamforming algorithm is proposed in code-division multiple-access wireless systems based on an array pattern synthesis approach. By incorporating an interference suppression mechanism in the iterative procedure, the proposed algorithm outperforms conventional blind algorithms. Two practical adaptive beamforming algorithms are further presented, which provide fast convergence speed with low complexity. The simulation results demonstrate the effectiveness of the proposed adaptive beamforming algorithms in various signal environments.

Fast Adaptive Blind Beamforming Algorithm for Antenna Array in CDMA Systems

In this paper, the maximum signal-to-interference-plus-noise ratio (MSINR) beamforming problem in antenna-array CDMA systems is considered. In this paper, a modified MSINR criterion presented in a previous paper is interpreted as an unconstrained scalar cost function. By applying recursive least squares (RLS) to minimize the cost function, a novel blind adaptive beamforming algorithm to estimate the beamforming vector, which optimally combines the desired signal contributions from different antenna elements while suppressing noise and interference, is derived. Neither the knowledge of the channel conditions (fading coefficients, signature sequences and timing of interferers, statistics of other noises, etc.) nor training sequence is required. Compared with previously published adaptive beamforming algorithms based on the stochastic-gradient method, it has faster convergence and better tracking capability in the time-varying environment. Simulation results in various signal environments are presented to show the performance of the proposed algorithm.

A novel blind adaptive space-time receiver for multi-code DS-CDMA

Abstract-The capacity of conventional wireless communications systems based upon Direct-Sequence Code Division Multiple Access (DS-CDMA) schemes, is mainly limited by Multiple Access Interference (MAI). Therefore, methods aimed at reducing MAI are mandatory solutions to increase the capacity of such systems. Smart Antennas are a promising technology for improving the performance of high capacity mobile communications systems, because they are expected to be able to increase the Signal to Interference plus Noise power Ratio (SINR) of the received signals by dynamically adapting the equivalent array beam pattern in order to track the movements of the users within the cell. In this paper we propose a novel blind adaptive beamforming algorithm tailored for the up-link of multi-code multi-rate DS-CDMA wireless communications systems. Our proposal is based upon a modified Constant Modulus (CM) criterion, whose fundamental feature is the capability to overcome the main drawback of the classic CM algorithm, which lies in its difficulty of ensuring the convergence toward the desired user. The proposed algorithm exploits user-specific information intrinsically known at the receiver, which is the code uniquely associated to each user, without requiring the knowledge of the spatiotemporal propagation channel nor any specific training sequence. Within this paper we present a broadband solution, designed to temporally re-align uncorrelated clusters of multipaths, as well as spatially recombine correlated multipaths belonging to the same cluster. Computer simulations show that our proposed technique can effectively exploit path diversity and multipath correlation, also in the presence of Doppler effect and time-variable propagation conditions.

Super-Exponential Blind Adaptive Beamforming

The objective of the beamforming with the exploitation of a sensor array is to enhance the signals of the sources from desired directions, suppress the noises and the interfering signals from other directions, and/or simultaneously provide the localization of the associated sources. In this paper, we present a higher order cumulant-based beamforming algorithm, namely, the super-exponential blind adaptive beamforming algorithm, which is extended from the super-exponential algorithm (SEA) and the inverse filter criteria (IFC). While both SEA and IFC assume noise-free conditions, this requirement is no longer needed, and all the noise components are taken into account in the proposed algorithm. Two special conditions are derived under which the proposed blind beamforming algorithm achieves the performance of the corresponding optimal nonblind beamformer in the sense of minimum mean square error (MMSE). Simulation results show that the proposed algorithm is effective and robust to diverse initial weight vectors; its performance with the use of the fourth-order cumulants is close to that of the nonblind optimal MMSE beamformer.

Fast adaptive super-exponential multistage beamforming for cellular base-station transceivers with antenna arrays

A new blind adaptive beamforming algorithm is introduced. We show how cumulants of the received signals can be used to obtain the weights of the beamformer that perform blind extraction. The method is based on a spatial interpretation of a deconvolution procedure known as the super-exponential algorithm. The basic block processing algorithm is attractive because it can be transformed in an efficient adaptive algorithm which exhibits good tracking capability. To prove the effectiveness of the idea, we show results for a typical mobile communications scenario where several cochannel interferers corrupt the signals of interest.