Deep neural network: an alternative to traditional channel estimators in massive MIMO systems
A Melgar, A de la Fuente, L Carro-Calvo… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Fifth-generation (5G) requires a highly accurate estimate of the channel state information
(CSI) to exploit the benefits of massive multiple-input-multiple-output (MaMIMO) systems. 5G …
(CSI) to exploit the benefits of massive multiple-input-multiple-output (MaMIMO) systems. 5G …
Exploiting low-rank tensor-train deep neural networks based on Riemannian gradient descent with illustrations of speech processing
This work focuses on designing low-complexity hybrid tensor networks by considering trade-
offs between the model complexity and practical performance. Firstly, we exploit a low-rank …
offs between the model complexity and practical performance. Firstly, we exploit a low-rank …
SubTTD: DOA estimation via sub-Nyquist tensor train decomposition
Conventional tensor direction-of-arrival (DOA) estimation methods for sparse arrays apply
canonical polyadic decomposition (CPD) to the high-order coarray covariance tensor for …
canonical polyadic decomposition (CPD) to the high-order coarray covariance tensor for …
Guaranteed nonconvex factorization approach for tensor train recovery
In this paper, we provide the first convergence guarantee for the factorization approach.
Specifically, to avoid the scaling ambiguity and to facilitate theoretical analysis, we optimize …
Specifically, to avoid the scaling ambiguity and to facilitate theoretical analysis, we optimize …
A low-complexity neural normalized min-sum ldpc decoding algorithm using tensor-train decomposition
Compared with traditional low-density parity-check (LDPC) decoding algorithms, the current
model-driven deep learning (DL)-based LDPC decoding algorithms face the disadvantage …
model-driven deep learning (DL)-based LDPC decoding algorithms face the disadvantage …
Mitigating clipping distortion in multicarrier transmissions using tensor-train deep neural networks
Multicarrier transmissions, such as orthogonal frequency/chirp division multiplexing
(OF/CDM), offer high spectral efficiency and low complexity equalization in multipath fading …
(OF/CDM), offer high spectral efficiency and low complexity equalization in multipath fading …
Joint-way compression for ldpc neural decoding algorithm with tensor-ring decomposition
In this paper, we propose low complexity joint-way compression algorithms with Tensor-
Ring (TR) decomposition and weight sharing to further lower the storage and computational …
Ring (TR) decomposition and weight sharing to further lower the storage and computational …
A novel channel estimation method based on deep neural network for otfs system
Q Li, Y Gong, F Meng, L Han… - 2022 15th International …, 2022 - ieeexplore.ieee.org
Orthogonal time-frequency space (OTFS) is a waveform technology designed in recent
years, which can be applied to wireless communication scenarios with high Doppler …
years, which can be applied to wireless communication scenarios with high Doppler …
Semi-data-aided channel estimation for MIMO systems via reinforcement learning
Data-aided channel estimation is a promising solution to improve channel estimation
accuracy by exploiting data symbols as pilot signals for updating an initial channel estimate …
accuracy by exploiting data symbols as pilot signals for updating an initial channel estimate …
Swarm intelligence‐based deep ensemble learning machine for efficient channel estimation in MIMO communication systems
BMR Manasa, VP - International journal of communication …, 2022 - Wiley Online Library
Multiple‐input multiple‐output (MIMO) technology is much significant for achieving high data
rates while considering the multiuser communication. For this purpose, the estimation of …
rates while considering the multiuser communication. For this purpose, the estimation of …