Abstract
MU-MIMO beamforming is a key technology for 5G networks, relying on Channel State Information (CSI). However, in practice, the estimated CSI in reality is prone to uncertainty. Further, a MU-MIMO beamforming solution must be derived within a millisecond to be useful for real-time 5G applications. We present ReDBeam - a real-time data-driven beamforming solution for MU-MIMO using limited CSI data samples. The main novelties of ReDBeam are a parallel algorithm and an optimized GPU implementation. ReDBeam delivers a MU-MIMO beamforming solution within 1 millisecond to meet the probabilistic data rate requirements from the users, and minimize a base station's power consumption. Through extensive experiments, we show that ReDBeam consistently meets the stringent 1-millisecond real-time requirement and is orders of magnitude faster than other state-of-the-art algorithms. ReDBeam conclusively demonstrates that MU-MIMO beamforming with data rate requirements can be achieved in real-time using only limited CSI data samples. © 2002-2012 IEEE.
| Original language | English |
|---|---|
| Pages (from-to) | 13549-13566 |
| Number of pages | 18 |
| Journal | IEEE Transactions on Mobile Computing |
| Volume | 24 |
| Issue number | 12 |
| Online published | 25 Jul 2025 |
| DOIs | |
| Publication status | Published - Dec 2025 |
| Externally published | Yes |
Funding
This work was supported in part by NSF under Grant CNS-2312447 and Grant CMMI-2246414, in part by ONR under MURI under Grant N00014-19-1-2621, and in part by Commonwealth Cyber Initiative (CCI).
Research Keywords
- 5G
- beamforming
- Channel uncertainty
- GPU
- limited data samples
- MU-MIMO
- real-time
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