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Power Allocation for Sum Rate Maximization in 5G NOMA System with Imperfect SIC: A Deep Learning Approach
Author(s)
Saetan, Worawit
Thipchaksurat, Sakchai
Date Issued
October 1, 2019
Type
Conference Paper
Abstract
Non-orthogonal multiple access (NOMA) is regarded as a promising technology for enhancing the spectral efficiency (SE) in 5G communication system. In this paper, we propose a power allocation scheme for maximizing sum rate for downlink NOMA system in the presence of imperfect successive interference cancellation (SIC). The proposed scheme uses deep learning to predict the optimal power allocation through exhaustive search. Simulation results reveal that the proposed scheme can achieve the sum rate performance close to the optimal scheme but with much lower computational complexity.
Citation
Proceedings of 2019 4th International Conference on Information Technology Encompassing Intelligent Technology and Innovation Towards the New Era of Human Life Incit 2019, 195-198, 2019