We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Reconfigurable intelligent surface passive beamforming enhancement using unsupervised learning.
- Authors
Al-Shaeli, Intisar; Hburi, Ismail Sharhan; Majeed, Ammar A.
- Abstract
Reconfigurable intelligent surfaces (RIS) is a wireless technology that has the potential to improve cellular communication systems significantly. This paper considers enhancing the RIS beamforming in a RIS-aided multiuser multi-input multi-output (MIMO) system to enhance user throughput in cellular networks. The study offers an unsupervised/deep neural network (U/DNN) that simultaneously optimizes the intelligent surface beamforming with less complexity to overcome the non-convex sum-rate problem difficulty. The numerical outcomes comparing the suggested approach to the near-optimal iterative semi-definite programming strategy indicate that the proposed method retains most performance (more than 95% of optimal throughput value when the number of antennas is 4 and RIS’s elements are 30) while drastically reducing system computing complexity.
- Subjects
MULTIUSER computer systems; BEAMFORMING; SEMIDEFINITE programming; ANTENNAS (Electronics); COMPUTER systems
- Publication
International Journal of Electrical & Computer Engineering (2088-8708), 2023, Vol 13, Issue 1, p493
- ISSN
2088-8708
- Publication type
Article
- DOI
10.11591/ijece.v13i1.pp493-501