Results 81 to 90 of about 839,900 (174)
This paper addresses channel estimation in mmWave (millimetre wave) hybrid MIMO (multiple‐input multiple‐output) systems impaired by residual transceiver hardware nonidealities, modelled as additive non‐Gaussian noise via Bussgang decomposition. A hyperparameter‐free maximum Versoria criterion (MVC)‐based channel estimator is proposed, featuring a ...
Rangeet Mitra +5 more
wiley +1 more source
This research proposes a Regularised Hyperparameter Bilevel Optimisation with Continual Learning‐based Deep Neural Network (RHBO‐CLDNN) for beamforming in an Ultra‐Wide Band (UWB) system. The RHBO ensures the hyperparameter efficiency at both upper and lower levels, which allows DNN to fine‐tune the unique characteristics of the UWB system, which leads
Pradeep Kumar Siddanna +2 more
wiley +1 more source
Deep‐Learned Channel Estimation for MIMO‐OFDM System by Exploiting Frequency‐Space Correlation
In massive MIMO–OFDM systems, accurate channel state information acquisition is vital for reliable transmission. Traditional methods fail to fully exploit sparse channel correlation, so an attentive residual autoencoder network is proposed. It uses an autoencoder with attention and residual connections to capture frequency–space correlation, and ...
Yiming Wei +5 more
wiley +1 more source
Joint user grouping and antenna selection based massive MIMO beamforming
In massive MIMO systems,when the number of users is larger as that of antennas at base station(BS),the various channels may be significantly different.A new zero-forcing beamformer design algorithm was proposed based on joint user grouping and antenna ...
Qian WANG +3 more
doaj +2 more sources
FDA‐MIMO Range and Angle Estimation Based on Hybrid Tensor Ring and CP Decomposition
The graphical abstract illustrates the RMSE performance of range and angle estimation versus SNR for different array configurations. The proposed method consistently achieves lower estimation error than existing approaches and closely matches the Cramér‐Rao bound across the entire SNR range, demonstrating its superior accuracy.
Junyuan Yue +3 more
wiley +1 more source
An overview of the CSI feedback based on deep learning for massive MIMO systems
The massive multiple-input multiple-output (MIMO) technology is considered to be one of the core technologies of the next generation communication system.To fully utilize the potential gains of MIMO systems,the base station should accurately acquire the ...
Muhan CHEN, Jiajia GUO, Xiao LI, Shi JIN
doaj +2 more sources
Low‐Complexity DOA Estimation: Combining VSSLMS With FFT Spectrum Estimation
This letter presents a novel, low‐complexity framework for DOA estimation. The proposed method achieves a significant reduction in computational complexity—from O(ML) to O(M log L)—compared to conventional SSE methods. Crucially, as illustrated in the accompanying figure, the method maintains high estimation accuracy, outperforming standard SSE‐based ...
Lei Sun +4 more
wiley +1 more source
A Generalized Sum-Rate Optimizer for Cooperative Multiuser Massive MIMO Link Topologies
Large-scale, or massive, multiple-input multiple-output (MIMO) systems are typified by the number of antennas contributing to a communication link.
Adam L. Anderson, Michael A. Jensen
doaj +1 more source
A Fair User Selection Algorithm for Multi-User Massive MIMO System
Massive Multiple-input Multiple-output (Massive MIMO) system is one of the most potential candidates for the fifth-generation wireless communication.
Dhoni Putra Setiawan
doaj
Scalability of MIMO Antennas: Assessing Gain and HPBW for Different Antenna Element Configurations
The design of Massive MIMO Antennas presents challenges due to their large size, which can impede the design process. Additionally, the arrangement of multiple antenna elements in Massive MIMO Antennas poses a challenge, as it surpasses the capabilities ...
Salwa Salsabila +3 more
doaj +1 more source

