Massive multiple-input multiple-output (MIMO) is a key technology for fifth generation (5G) communication system. MIMO symbol detection is one of the most computationally intensive tasks for a massive MIMO baseband receiver. In this paper, we analyze matrix decomposition algorithms for massive MIMO systems, which were traditionally used for small-scale MIMO detection due to their numerical stability and modular design. We present the computational complexity of linear detection mechanisms based on QR, Cholesky and LDL-decomposition algorithms for different massive MIMO configurations. We compare them with the state-of-art approximate inversion-based massive MIMO detection methods. The results provide important insights for system and very large-scale integration (VLSI) designers to select appropriate massive MIMO detection algorithms according to their requirement.
@article{arxiv.2009.11172,
title = {Matrix Decomposition for Massive MIMO Detection},
author = {Shahriar Shahabuddin and Muhammad Hasibul Islam and Mohammad Shahanewaz Shahabuddin and Mahmoud A. Albreem and Markku Juntti},
journal= {arXiv preprint arXiv:2009.11172},
year = {2020}
}