Xia, W;
Zheng, G;
Wong, K-K;
Zhu, H;
(2020)
Model-Driven Beamforming Neural Networks.
IEEE Wireless Communications
, 27
(1)
pp. 68-75.
10.1109/MWC.001.1900239.
Preview |
Text
BeamingDL-v3.pdf - Accepted Version Download (419kB) | Preview |
Abstract
Beamforming is evidently a core technology in recent generations of mobile communication networks. Nevertheless, an iterative process is typically required to optimize the parameters, making it ill-placed for real-time implementation due to high complexity and computational delay. Heuristic solutions such as zero-forcing are simpler but at the expense of performance loss. Alternatively, DL is well understood to be a generalizing technique that can deliver promising results for a wide range of applications at much lower complexity if it is sufficiently trained. As a consequence, DL may present itself as an attractive solution to beamforming. To exploit DL, this article introduces general data- and model-driven BNNs, presents various possible learning strategies, and also discusses complexity reduction for DL-based BNNs. We also offer enhancement methods such as training- set augmentation and transfer learning in order to improve the generality of BNNs, accompanied by computer simulation results and testbed results showing the performance of such BNN solutions.
Type: | Article |
---|---|
Title: | Model-Driven Beamforming Neural Networks |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1109/MWC.001.1900239 |
Publisher version: | https://doi.org/10.1109/MWC.001.1900239 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | Array signal processing, Complexity theory, Signal to noise ratio, Training data, Interference, Supervised learning, Artificial neural networks |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
URI: | https://discovery.ucl.ac.uk/id/eprint/10094220 |
Archive Staff Only
![]() |
View Item |