A novel blind adaptive 3D beam steering algorithm for interference mitigation and performance enhancement in massive MIMO systems

This paper introduces an innovative blind adaptive 3D Beam steering algorithm designed to mitigate interference, ultimately improving the signal-to-interference and noise ratio (SINR) to enhance the overall performance of mMIMO (massive multiple-input multiple-output (MIMO)) networks. The proposed algorithm combines an optimized direction of arrival (DoA) estimation method with an inventive adaptive signal processing technique. To address the computational complexity associated with determining the 2D-DoA of incoming signals, an improved RD-MUSIC (Reduced Dimension — Multiple Signal Classification) estimator is proposed. This method streamlines the process into an efficient 1D search, significantly reducing computational overhead compared to conventional 2D-MUSIC and minimizing noise, maintaining superior accuracy over the conventional RD-MUSIC method. Leveraging the estimated 2D-DoAs, the proposed adaptive signal processing technique integrates the Dolph-Chebyshev weighting method with nulling constraints to calculate the optimal complex weig0hts necessary to accurately steer the main Beam toward the desired signal direction and create deep nulls in the directions of interfering signals, resulting in enhanced SINR. Compared to alternative algorithms, our approach demonstrates superior performance and offers an efficient solution without requiring a training signal or additional antenna elements. This is advantageous, particularly in environments with intense interference and high mobility, making it a promising candidate for future wireless systems.