Study on Precoding Optimization Algorithms in Massive MIMO System with Multi-Antenna Users
Abstract
The paper studies the multi-user precoding problem as a non-convex optimization problem for wireless multiple input and multiple output (MIMO) systems. In our work, we approximate the target Spectral Efficiency function with a novel computationally simpler function. Then, we reduce the precoding problem to an unconstrained optimization task using a special differential projection method and solve it by the Quasi-Newton L-BFGS iterative procedure to achieve gains in capacity. We are testing the proposed approach in several scenarios generated using Quadriga - open-source software for generating realistic radio channel impulse response. Our method shows monotonic improvement over heuristic methods with reasonable computation time. The proposed L-BFGS optimization scheme is novel in this area and shows a significant advantage over the standard approaches. The proposed method has a simple implementation and can be a good reference for other heuristic algorithms in this field.
Cite
@article{arxiv.2107.13440,
title = {Study on Precoding Optimization Algorithms in Massive MIMO System with Multi-Antenna Users},
author = {Evgeny Bobrov and Dmitry Kropotov and Sergey Troshin and Danila Zaev},
journal= {arXiv preprint arXiv:2107.13440},
year = {2022}
}
Comments
16 pages, 6 figures, 6 tables, the work has been accepted for publication in Optimization Methods and Software, comments are welcome