Active user identification based on asynchronous sparse Bayesian learning with SVM
In this paper, an asynchronous sparse Bayesian learning (ASBL) algorithm-based receiver
for uplink (UL) grant-free transmission is proposed. The time-domain channel estimation is …
for uplink (UL) grant-free transmission is proposed. The time-domain channel estimation is …
Modulation and detection for simple receivers in rapidly time-varying channels
KS Gomadam, SA Jafar - IEEE transactions on communications, 2007 - ieeexplore.ieee.org
We investigate the performance degradation of basic modulation schemes in a rapidly time-
varying channel using a first-order autoregressive channel model. Various performance …
varying channel using a first-order autoregressive channel model. Various performance …
Channel prediction with time-varying Doppler spectrum in high-mobility scenarios: A polynomial Fourier transform based approach and field measurements
Beamforming for multi-antenna wireless communication systems has been widely studied
and applied in practice. However, its performance in high mobility scenarios deteriorates …
and applied in practice. However, its performance in high mobility scenarios deteriorates …
Blind Recognition of 5G LDPC Codes Over a Candidate Set
Y Wang, S Che - IEEE Communications Letters, 2024 - ieeexplore.ieee.org
Blind recognition of channel codes is an important technology in Adaptive Modulation and
Coding (AMC) systems. Shortening and puncturing have been adopted to achieve flexible …
Coding (AMC) systems. Shortening and puncturing have been adopted to achieve flexible …
Multi-component feature extraction for few-sample automatic modulation classification
With the rapid development of deep learning (DL), Automatic Modulation Classification
(AMC) has also taken a huge leap forward. The DL-based AMC methods are able to achieve …
(AMC) has also taken a huge leap forward. The DL-based AMC methods are able to achieve …
Multi-task learning approach for modulation and wireless signal classification for 5G and beyond: Edge deployment via model compression
A Jagannath, J Jagannath - Physical Communication, 2022 - Elsevier
Future communication networks must address the scarce spectrum to accommodate
extensive growth of heterogeneous wireless devices. Efforts are underway to address …
extensive growth of heterogeneous wireless devices. Efforts are underway to address …
Automatic modulation classification in time-varying channels based on deep learning
Automatic modulation classification (AMC) is an important technology in military signal
reconnaissance and civilian communications such as cognitive radios. Most of the existing …
reconnaissance and civilian communications such as cognitive radios. Most of the existing …
Lattice reduction-based approximate MAP detection with bit-wise combining and integer perturbed list generation
For iterative detection and decoding (IDD) in multiple-input multiple-output (MIMO) systems,
the log-likelihood ratio (LLR) of each coded bit can be found by an optimal bit-wise …
the log-likelihood ratio (LLR) of each coded bit can be found by an optimal bit-wise …
Online hybrid likelihood based modulation classification using multiple sensors
B Dulek - IEEE Transactions on Wireless Communications, 2017 - ieeexplore.ieee.org
Hybrid likelihood-based approaches equipped with the expectation-maximization (EM)
algorithm have received attention in the modulation classification literature during recent …
algorithm have received attention in the modulation classification literature during recent …
Performance of iterative data detection and channel estimation for single-antenna and multiple-antennas wireless communications
In iterative data-detection and channel-estimation algorithms, the channel estimator and the
data detector recursively exchange information in order to improve the system performance …
data detector recursively exchange information in order to improve the system performance …