An ℓ0-norm-constrained adaptive algorithm for joint beamforming and antenna selection

This paper presents a new adaptive algorithm for joint beamforming and antenna selection in mobile communication systems. Such an algorithm is of particular interest for massive multiple-input multiple-output (mMIMO) antenna systems along with limited number of available radio-frequency chains. The proposed algorithm is based on introducing an ℓ 0 -norm constraint to an established adaptive-projection beamforming optimization scheme. In doing so, a real-time beamforming optimization can be carried out, resulting in a beamforming vector that tends to be sparse. The higher-magnitude elements of such a vector point out to the antenna-array elements that have the largest contribution to the output signal-to-interference-plus-noise ratio (SINR). Consequently, an effective antenna selection can be achieved directly by considering the magnitude of the beamforming coefficients. Simulation results confirm the effectiveness of the proposed algorithm in enhancing the output SINR. • A new adaptive algorithm for joint beamforming and antenna selection is proposed. • The proposed algorithm is targeted for massive MIMO antenna systems. • A limited number of RF chains is considered. • An ℓ 0 -norm constraint is used for developing the proposed algorithm. • Simulation results show the effectiveness of the proposed algorithm.