no code implementations • 23 Oct 2023 • Xinliang Zhang, Mojtaba Vaezi
The proposed structure significantly enhances the performance of the ZIC both for the perfect and imperfect CSI.
no code implementations • 11 May 2023 • Mojtaba Vaezi, Xingqin Lin, Hongliang Zhang, Walid Saad, H. Vincent Poor
In this paper, we propose leveraging deep reinforcement learning for interference management to tackle this shortcoming.
no code implementations • 15 Nov 2021 • Yousef Mafi, Fakhreddin Amirhosseini, Seied Ali Hosseini, Amin Azari, Meysam Masoudi, Mojtaba Vaezi
As this module continuously monitors the received ambient energy for potential paging of the device, its contribution to WuR's power consumption is crucial.
no code implementations • 3 Nov 2021 • Xinliang Zhang, Mojtaba Vaezi, Timothy J. O'Shea
SVDembedded DAE largely outperforms theoretic linear precoding in terms of BER.
no code implementations • 14 Oct 2021 • Jordan Pauls, Mojtaba Vaezi
A novel signaling design for secure transmission over two-user multiple-input multiple-output non-orthogonal multiple access channel using deep neural networks (DNNs) is proposed.
no code implementations • 6 Jul 2020 • Xinliang Zhang, Mojtaba Vaezi
Numerical results demonstrate that, compared to the conventional solutions, the proposed DNN-based precoder reduces on-the-fly computational complexity more than an order of magnitude while reaching near-optimal performance (99. 45\% of the averaged optimal solutions).
no code implementations • 24 Sep 2019 • Khai Nguyen Doan, Mojtaba Vaezi, Wonjae Shin, H. Vincent Poor, Hyundong Shin, Tony Q. S. Quek
To address the power allocation problem, two novel methods are proposed.
no code implementations • 17 Sep 2019 • Xinliang Zhang, Mojtaba Vaezi
A novel precoding method based on supervised deep neural networks is introduced for the multiple-input multiple-output Gaussian wiretap channel.