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 …
Channel estimation for semi-passive reconfigurable intelligent surfaces with enhanced deep residual networks
Reconfigurable intelligent surface (RIS) is envisioned as an essential paradigm for realizing
the sixth-generation networks, due to the use of low-cost reflecting elements for establishing …
the sixth-generation networks, due to the use of low-cost reflecting elements for establishing …
Channel estimation for mmWave massive MIMO with convolutional blind denoising network
Channel estimation is one of the foremost challenges for realizing practical millimeter-wave
(mmWave) massive multiple-input multiple-output (MIMO) systems. To circumvent this …
(mmWave) massive multiple-input multiple-output (MIMO) systems. To circumvent this …
Quasi-static and time-selective channel estimation for block-sparse millimeter wave hybrid MIMO systems: Sparse Bayesian learning (SBL) based approaches
This paper develops schemes for block-sparse channel estimation in millimeter wave
(mmWave) multiple-input multiple-output (MIMO) systems that exploit the spatial sparsity …
(mmWave) multiple-input multiple-output (MIMO) systems that exploit the spatial sparsity …
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 …
Deep learning assisted adaptive index modulation for mmWave communications with channel estimation
The efficiency of link adaptation in wireless communications relies greatly on the accuracy of
channel knowledge and transmission mode selection. In this paper, a novel deep learning …
channel knowledge and transmission mode selection. In this paper, a novel deep learning …
Clustered sparse Bayesian learning based channel estimation for millimeter-wave massive MIMO systems
In this article, we present two clustered sparse Bayesian learning (Cluster-SBL) channel
estimation algorithms for millimeter-wave (mmWave) massive multiple-input-multiple-output …
estimation algorithms for millimeter-wave (mmWave) massive multiple-input-multiple-output …
Channel estimation and hybrid precoding for distributed phased arrays based MIMO wireless communications
Distributed phased arrays based multiple-input multiple-output (DPA-MIMO) is a newly
introduced architecture that enables both spatial multiplexing and beamforming while …
introduced architecture that enables both spatial multiplexing and beamforming while …
Self-Adaptive Measurement Matrix Design and Channel Estimation in Time-Varying Hybrid MmWave Massive MIMO-OFDM Systems
Channel estimation in hybrid massive multiple input multiple output (MIMO) orthogonal
frequency division multiplexing (OFDM) systems is challenging as only low-dimensional …
frequency division multiplexing (OFDM) systems is challenging as only low-dimensional …
Channel Estimation with Dynamic Metasurface Antennas via Model-Based Learning
Dynamic Metasurface Antenna (DMA) is a cutting-edge antenna technology offering
scalable and sustainable solutions for large antenna arrays. The effectiveness of DMAs …
scalable and sustainable solutions for large antenna arrays. The effectiveness of DMAs …