[HTML][HTML] 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 …
CAnet: Uplink-aided downlink channel acquisition in FDD massive MIMO using deep learning
In frequency-division duplexing systems, the downlink channel state information (CSI)
acquisition scheme leads to high training and feedback overhead. In this work, we propose …
acquisition scheme leads to high training and feedback overhead. In this work, we propose …
CSI feedback with model-driven deep learning of massive MIMO systems
J Guo, L Wang, F Li, J Xue - IEEE Communications Letters, 2021 - ieeexplore.ieee.org
In order to achieve reliable communication with a high data rate of massive multiple-input
multiple-output (MIMO) systems in frequency division duplex (FDD) mode, the estimated …
multiple-output (MIMO) systems in frequency division duplex (FDD) mode, the estimated …
Learning the CSI denoising and feedback without supervision
V Rizzello, W Utschick - 2021 IEEE 22nd International …, 2021 - ieeexplore.ieee.org
In this work, we develop a joint denoising and feedback strategy for channel state
information in frequency division duplex systems. In such systems, the biggest challenge is …
information in frequency division duplex systems. In such systems, the biggest challenge is …
AI enlightens wireless communication: Analyses, solutions and opportunities on CSI feedback
H Xiao, Z Wang, W Tian, X Liu, W Liu… - China …, 2021 - ieeexplore.ieee.org
In this paper, we give a systematic description of the 1st Wireless Communication Artificial
Intelligence (AI) Competition (WAIC) which is hosted by IMT-2020 (5G) Promotion Group …
Intelligence (AI) Competition (WAIC) which is hosted by IMT-2020 (5G) Promotion Group …
Knowledge distillation-aided end-to-end learning for linear precoding in multiuser MIMO downlink systems with finite-rate feedback
K Kong, WJ Song, M Min - IEEE Transactions on Vehicular …, 2021 - ieeexplore.ieee.org
We propose a deep learning-based channel estimation, quantization, feedback, and
precoding method for downlink multiuser multiple-input and multiple-output systems. In the …
precoding method for downlink multiuser multiple-input and multiple-output systems. In the …
Model-driven learning for generic MIMO downlink beamforming with uplink channel information
Accurate downlink channel information is crucial to the beamforming design, but it is difficult
to obtain in practice. This paper investigates a deep learning-based optimization approach …
to obtain in practice. This paper investigates a deep learning-based optimization approach …
AI empowered resource management for future wireless networks
Resource management plays a pivotal role in wireless networks, which, unfortunately, leads
to challenging NP-hard problems. Artificial Intelligence (AI), especially deep learning …
to challenging NP-hard problems. Artificial Intelligence (AI), especially deep learning …
AI-enhanced codebook-based CSI feedback in FDD massive MIMO
In frequency-division duplexing systems, the downlink channel state information (CSI)
should be fed back through an uplink transmission to reap the benefits of the massive …
should be fed back through an uplink transmission to reap the benefits of the massive …
Two-sample tests for validating the UL-DL conjecture in FDD systems
V Rizzello, N Turan, M Joham… - 2021 17th International …, 2021 - ieeexplore.ieee.org
In this work, we present a two-sample tests analysis based on the maximum mean
discrepancy metric to validate the recently proposed uplink-downlink conjecture for …
discrepancy metric to validate the recently proposed uplink-downlink conjecture for …