… issue that successive interference cancellation (SIC) decoding is imperfect in the real-world …
system based on deep learning. In this scheme, both precoding and SIC decoding of the …

… of the NOMA systems under the assumption of perfect SIC (pSIC). Nevertheless, the pSIC is
… of users during the SIC process. Accordingly, the impacts of imperfect SIC (iSIC) may profess …

… with imperfect successive interference cancellation, imperfect … -time configurations, we
also design a deep learning (DL) … Our results show that the deep neural network exhibits the …

… -power energy harvesting mechanism under imperfect successive interference cancellation.
… Toward real-time configurations in IoT networks, we design a deep learning framework for …

… In [10], deep learning is used to learn exhaustive search pilot allocation. In order to reduce
the effect of imperfect SIC, In this paper, we propose the application of deep learning to energy…

… In practical scenarios, the SIC decoding is difficult to be achieved perfectly. … the imperfect
SIC condition in this paper. If we define as the residual power parameter for the imperfect SIC, …

… alleviate the impact of imperfect SIC in practical systems, In this paper, we apply the deep
learning to fairness-based power allocation for downlink NOMA system with imperfect SIC. We …

… With this framework, training and learning are performed by designing rational neural network
… In this letter, two deep neural networks (DNNs) are built to calculate the access vector and …

… a deep learning-based RA scheme for implementation. In recent years, deep learning has
… have been some excellent researches on deep learning-based traffic load prediction and …

… SIC is compared with RNN based DL/ML model for NOMA detection in [37] and it is shown
that the deep learning … In this paper, we propose a machine learning-based framework for …