Application of reinforcement learning and deep learning in multiple-input and multiple-output (MIMO) systems
The current wireless communication infrastructure has to face exponential development in
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …
Overview of deep learning-based CSI feedback in massive MIMO systems
Many performance gains achieved by massive multiple-input and multiple-output depend on
the accuracy of the downlink channel state information (CSI) at the transmitter (base station) …
the accuracy of the downlink channel state information (CSI) at the transmitter (base station) …
Convolutional neural network-based multiple-rate compressive sensing for massive MIMO CSI feedback: Design, simulation, and analysis
Massive multiple-input multiple-output (MIMO) is a promising technology to increase link
capacity and energy efficiency. However, these benefits are based on available channel …
capacity and energy efficiency. However, these benefits are based on available channel …
Deep learning-driven wireless communication for edge-cloud computing: opportunities and challenges
Future wireless communications are becoming increasingly complex with different radio
access technologies, transmission backhauls, and network slices, and they play an …
access technologies, transmission backhauls, and network slices, and they play an …
Pruning the pilots: Deep learning-based pilot design and channel estimation for MIMO-OFDM systems
MB Mashhadi, D Gündüz - IEEE Transactions on Wireless …, 2021 - ieeexplore.ieee.org
With the large number of antennas and subcarriers the overhead due to pilot transmission
for channel estimation can be prohibitive in wideband massive multiple-input multiple-output …
for channel estimation can be prohibitive in wideband massive multiple-input multiple-output …
Deep learning-based CSI feedback for beamforming in single-and multi-cell massive MIMO systems
The potentials of massive multiple-input multiple-output (MIMO) are all based on the
available instantaneous channel state information (CSI) at the base station (BS). Therefore …
available instantaneous channel state information (CSI) at the base station (BS). Therefore …
Downlink CSI feedback algorithm with deep transfer learning for FDD massive MIMO systems
In this paper, a channel state information (CSI) feedback method is proposed based on deep
transfer learning (DTL). The proposed method addresses the problem of high training cost of …
transfer learning (DTL). The proposed method addresses the problem of high training cost of …
Deep learning-based denoise network for CSI feedback in FDD massive MIMO systems
Channel state information (CSI) feedback is critical for frequency division duplex (FDD)
massive multi-input multi-output (MIMO) systems. Most conventional algorithms are based …
massive multi-input multi-output (MIMO) systems. Most conventional algorithms are based …
Distributed deep convolutional compression for massive MIMO CSI feedback
MB Mashhadi, Q Yang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Massive multiple-input multiple-output (MIMO) systems require downlink channel state
information (CSI) at the base station (BS) to achieve spatial diversity and multiplexing gains …
information (CSI) at the base station (BS) to achieve spatial diversity and multiplexing gains …
A Markovian model-driven deep learning framework for massive MIMO CSI feedback
Z Liu, M del Rosario, Z Ding - IEEE Transactions on Wireless …, 2021 - ieeexplore.ieee.org
Channel state information (CSI) plays a vital role in scheduling and capacity-approaching
transmission optimization of massive MIMO communication systems. In frequency division …
transmission optimization of massive MIMO communication systems. In frequency division …