Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/NorCAS51424.2020.9264998 | 2020 IEEE Nordic Circuits and Systems Conference (NorCAS) |
Keywords | DocType | ISBN |
Massive-MIMO,approximate matrix inversion,matrix decomposition,QR,LDL,Cholesky | Conference | 978-1-7281-9227-7 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shahriar Shahabuddin | 1 | 0 | 1.01 |
| Muhammad Hasibul Islam | 2 | 0 | 0.34 |
| Mohammad Shahanewaz Shahabuddin | 3 | 0 | 0.68 |
| Mahmoud A. Albreem | 4 | 0 | 0.34 |
| Markku Juntti | 5 | 1 | 1.37 |