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FDD massive MIMO downlink channel estimation via selective sparse coding over AOA/AOD cluster dictionaries
(Institute of Electrical and Electronics Engineers Inc., 2018)
Sparse coding over a redundant dictionary has recently been used as a framework for downlink channel estimation in frequency division duplex massive multiple-input multiple-output antenna systems. This usage allows for ...
Iterative tap pursuit for channel shortening equalizer design
(Institute of Electrical and Electronics Engineers Inc., 2018)
In this work, an iterative tap pursuit algorithm for designing channel shortening equalizers is proposed. Similar to pursuit algorithms, a residual vector is initialized with a desired target impulse response, which is ...
Compressed spectrum sensing using sparse recovery convergence patterns through machine learning classification
(Institute of Electrical and Electronics Engineers Inc., 2019)
Despite the well-known success of sub-Nyquist sampling in reducing the hardware and computational costs of spectrum sensing, it still has the shortcoming of requiring a pre-determined spectrum sparsity level. This paper ...
Dictionary learning-based beamspace channel estimation in millimeter-wave massive mimo systems with a lens antenna array
(Institute of Electrical and Electronics Engineers Inc., 2019)
Recent research considers the application of a lens antenna array in order to provide efficient beam selection in beamspace massive MIMO. Achieving the advantages of this beam selection paradigm requires efficient channel ...
Deep learning-assisted detection of PUE and jamming attacks in cognitive radio systems
(Institute of Electrical and Electronics Engineers Inc., 2020)
Cognitive radio (CR)-based internet of things systems can be considered as an efficient solution for futuristic smart technologies. However, CRs are naturally vulnerable to two major security threats; primary user emulation ...
Spectrum occupancy prediction exploiting time and frequency correlations through 2D-LSTM
(Institute of Electrical and Electronics Engineers Inc., 2020)
The identification of spectrum opportunities is a pivotal requirement for efficient spectrum utilization in cognitive radio systems. Spectrum prediction offers a convenient means for revealing such opportunities based on ...
Sparse coding with enhanced atom selection for FDD massive MIMO channel estimation
(Institute of Electrical and Electronics Engineers Inc., 2021)
In sparse coding-based channel estimation, atom selection is based on jointly minimizing the sparsity and the error of the representation of the noisy measurement. However, this selection is not necessarily optimal in terms ...
Estimation and exploitation of multidimensional sparsity for MIMO-OFDM channel estimation
(Institute of Electrical and Electronics Engineers Inc., 2022)
Obtaining accurate channel state estimates at reasonable training overheads remains a big challenge for the applicability of multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM). Recently, ...
Deep RL-based spectrum occupancy prediction exploiting time and frequency correlations
(Institute of Electrical and Electronics Engineers Inc., 2022)
In cognitive radio systems, predicting spectrum occupancies is a convenient alternative way to continuous spectrum sensing. It can provide information on spectrum usage and so empty spectrum bands can be used by secondary ...
Deep learning-based optimal ris interaction exploiting previously sampled channel correlations
(IEEE - Institute of Electrical and Electronics Engineers, Inc, 2021)
The reconfigurable intelligent surface (RIS) technology has attracted interest due to its promising coverage and spectral efficiency features. However, some challenges need to be addressed to realize this technology in ...