Fast adaptive blind beamforming algorithm for antenna array in CDMA systems

• Published in: IEEE transactions on vehicular technology Vol. 55; no. 2; pp. 549 - 558
• Main Authors: Yang, J., Xi, H., Yang, F., Zhao, Y.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.03.2006; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive algorithms; Adaptive arrays; Algorithms; Antenna arrays; Antennas; Applied sciences; Array signal processing; Beamforming; Blinds; Code division multiple access; code division multiple access (CDMA); Cost function; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; Fading; generalized eigenvector; Information, signal and communications theory; Interference suppression; Least squares approximation; maximum signal-to-interference-plus-noise ratio (MSINR) beamforming; Multiaccess communication; multiple access interference (MAI); Noise; Recursive estimation; Resonance light scattering; Signal and communications theory; Signal, noise; Telecommunications and information theory; code division multiple access (CDMA); Array signal processing; Adaptive algorithm; generalized eigenvector; Eigenvector; Wireless telecommunication; Adaptive arrays; Adaptive antenna arrays; Beam forming; Optimization; maximum signal-to- interference-plus-noise ratio (MSINR) beamforming; multiple access interference (MAI); Code division multiple access; Signal to interference plus noise ratio
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2005.863419

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.