Deep neural network based channel estimation for massive MIMO-OFDM systems with imperfect channel state information
Massive multi-input multi-output (MIMO) has aroused extensive interest in communication
industry, as it can effectively increase communication system capacity and reduce transmit …
industry, as it can effectively increase communication system capacity and reduce transmit …
Structured turbo compressed sensing for downlink massive MIMO-OFDM channel estimation
Compressed sensing has been employed to reduce the pilot overhead for channel
estimation in wireless communication systems. Particularly, structured turbo compressed …
estimation in wireless communication systems. Particularly, structured turbo compressed …
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 …
Blind channel estimation for massive MIMO: A deep learning assisted approach
Large scale multiple-input multiple-output (MIMO) or Massive MIMO is one of the pivotal
technologies for future wireless networks. However, the performance of massive MIMO …
technologies for future wireless networks. However, the performance of massive MIMO …
Channel estimation using LS and MMSE channel estimation techniques for MIMO-OFDM systems
The conventional strategies utilized for channel assessment don't exploit the multipath lack.
In MIMO-OFDM frameworks, channel assessment is critical for computing framework …
In MIMO-OFDM frameworks, channel assessment is critical for computing framework …
Deep learning for joint channel estimation and signal detection in OFDM systems
X Yi, C Zhong - IEEE Communications Letters, 2020 - ieeexplore.ieee.org
In this letter, we propose a novel deep learning based approach for joint channel estimation
and signal detection in orthogonal frequency division multiplexing (OFDM) systems by …
and signal detection in orthogonal frequency division multiplexing (OFDM) systems by …
Efficient machine learning-enhanced channel estimation for OFDM systems
Recently much research work has focused on employing deep learning (DL) algorithms to
perform channel estimation in the upcoming 6G communication systems. However, these DL …
perform channel estimation in the upcoming 6G communication systems. However, these DL …
Joint channel estimation and data detection in MIMO-OFDM systems: A sparse Bayesian learning approach
The impulse response of wireless channels between the Nt transmit and Nr receive
antennas of a MIMO-OFDM system are group approximately sparse (ga-sparse), ie, the NtNr …
antennas of a MIMO-OFDM system are group approximately sparse (ga-sparse), ie, the NtNr …
Sparse, group-sparse, and online Bayesian learning aided channel estimation for doubly-selective mmWave hybrid MIMO OFDM systems
S Srivastava, CSK Patro… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Sparse, group-sparse and online channel estimation is conceived for millimeter wave
(mmWave) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing …
(mmWave) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing …
Soft-Output Deep LAS Detection for Coded MIMO Systems: A Learning-Aided LLR Approximation
The multiple-input-multiple-output-orthogonal frequency division multiplexing (MIMO-OFDM)
receiver aims to softly decode the transmitted information from the observed received signal …
receiver aims to softly decode the transmitted information from the observed received signal …