Asymptotic Behavior Analysis of Antenna Selection via Sparsity-Induced Precoder

This work provides a precise performance analysis of a joint antenna selection and precoding technique for massive multiple-input-single-output (MISO) multi-user systems with limited dynamic range power amplifiers. The proposed precoder is formulated as an optimization problem that aims to minimize distortion error power while incorporating an ℓ<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</inf>-regularization term to promote sparsity and enable antenna selection. It also includes constraints to ensure that the maximum power at each antenna remains within the permissible range for low-dynamic range power amplifiers. Utilizing the convex-Gaussian min-max theorem framework, we offer a precise characterization of the proposed solution’s performance as the number of users and antennas at the base station simultaneously increases. Through extensive numerical experiments, we evaluate the accuracy of our results and derive valuable insights into the effectiveness of the proposed joint antenna selection and precoding approach.