no code implementations • 9 Jul 2024 • Lu Zhang, Sangarapillai Lambotharan, Gan Zheng, Guisheng Liao, Ambra Demontis, Fabio Roli
Motivated by the superior performance of deep learning in many applications including computer vision and natural language processing, several recent studies have focused on applying deep neural network for devising future generations of wireless networks.
no code implementations • 9 Nov 2022 • Dawei Gao, Qinghua Guo, Ming Jin, Guisheng Liao, Yonina C. Eldar
Choosing the values of hyper-parameters in sparse Bayesian learning (SBL) can significantly impact performance.
no code implementations • 8 Oct 2022 • Dawei Gao, Qinghua Guo, Guisheng Liao, Yonina C. Eldar, Yonghui Li, Yanguang Yu, Branka Vucetic
Modelling the MIMO system with NN enables the design of NN architectures based on the signal flow of the MIMO system, minimizing the number of NN layers and parameters, which is crucial to achieving efficient training with limited pilot signals.
no code implementations • 29 Sep 2019 • Yuwen Yang, Feifei Gao, Cheng Qian, Guisheng Liao
Specifically, we first propose the eigenvalue based regression network (ERNet) and classification network (ECNet) to estimate the number of non-coherent sources, where the eigenvalues of the received signal covariance matrix and the source number are used as the input and the supervise label of the networks, respectively.