This paper proposes a novel learning to learn method, called learning to learn iterative
search algorithm (LISA), for signal detection in a multi-input multi-output (MIMO) system. The …

This work examines the use of two-way training to efficiently discriminate the channel
estimation performances at a legitimate receiver (LR) and an unauthorized receiver (UR) in …

Channel estimation with received signal-to-noise ratio (SNR) feedback is promising and
effective for practical wireless multiple-input multiple-output (MIMO) systems. In this paper …

In a-best detector for multiple-input-multiple-output (MIMO) systems, the value of needs to be
sufficiently large to achieve near-maximum-likelihood (ML) performance. By treating as a …

Channel estimation plays a critical role in the system performance of wireless networks. In
addition, deep learning has demonstrated significant improvements in enhancing the …

This paper considers a nonlinear multi-hop multi-user multiple-input multiple-output (MU-
MIMO) relay channel, in which multiple users send information symbols to a multi-antenna …

Recently, deep learning has been proposed as a potential technique for improving the
physical layer performance of radio receivers. Despite the large amount of encouraging …

Baek et al. proposed a deep learning-based signal detector for conventional MIMO systems,
which is a pioneering work of applying artificial intelligence into wireless communications …

Recently, convolutional neural network (CNN)-based channel estimation (CE) for massive
multiple-input multiple-output communication systems has achieved remarkable success …