For deep learning detection networks in the multiple-input-multiple-output (MIMO) channel,
deepening the network does not significantly improve performance beyond a certain number …

Designing a massive multiple-input multiple-output (M-MIMO) system is complex, time-
consuming, and challenging. Conventional MIMO decoders are either inefficient or complex …

Neural network has been applied into MIMO detection problem and has achieved the state-
of-the-art performance. However, it is hard to deploy these large and deep neural network …

In this letter, an efficient massive multiple-input multiple-output (MIMO) detector is proposed
by employing a deep neural network (DNN). Specifically, we first unfold an existing iterative …

Massive multiple-input multiple-output (MIMO) is a crucial technology in fifth-generation (5G)
and beyond 5G (B5G). However, the huge number of antennas used in massive MIMO …

The paper introduces principles of Belief Propagation (BP) algorithm and Damped BP
algorithm firstly. Then, with the BP algorithm and machine learning, this paper proposes a …

Multi-input multi-output (MIMO) technology becomes one of the most popular technologies
for the fifth-generation (5G) wireless networks due to the advantages in terms of spectrum …

In this paper, simple methodologies of deep learning application to conventional multiple-
input multiple-output (MIMO) communication systems are presented. The deep learning …

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 …

Multiple-Input Multiple-Output (MIMO) is a key technology due to its high spectral efficiency
and data rate in communication systems. Due to the high complexity of linear Minimum …