Results 121 to 130 of about 308,154 (181)

Deep learning approach for hybrid beamforming design in MU-MISO mmWave systems. [PDF]

Sci Rep
Ghaith E, Mekkawy T, Abouelfadl AA, Mahran A.   +3 more
europepmc   +1 more source

A Low-Cost Two-Dimensional Scalable Active Receive Phased Array with 8 Simultaneously Reconfigurable Beams. [PDF]

Micromachines (Basel)
Zhang H, Guo LX, Dun S, Li X, Mei W, Xu X, Bu D.   +6 more
europepmc   +1 more source

Low-latency jamming mitigation in SWaP-constrained GNSS analog CRPAs via hierarchical dithered null steering. [PDF]

NPJ Wirel Technol
Elaraby M, Massoud A, Hassan M, Elghamrawy H, Noureldin A.   +4 more
europepmc   +1 more source

Next-generation antenna beamforming via caterpillar fungus optimization for enhanced wireless communication. [PDF]

Sci Rep
Farghaly SI, Gafar M, Shaheen AM, Alwakeel AS, Sarhan S.   +4 more
europepmc   +1 more source

Improving spectral efficiency in distributed massive MIMO in multi-user downlink millimeter wave. [PDF]

Sci Rep
Rajaganapathi R, Senthilkumar S, Alabdulkreem E, Alruwais N.   +3 more
europepmc   +1 more source

MMU-STCNN-BDQ: a deep reinforcement learning framework for secure and energy-efficient beamforming in 6G mMIMO networks. [PDF]

Sci Rep
Ramudu K, Medasani S, Addepalli T, Sharma M, Pandey A, Srinubabu M.   +5 more
europepmc   +1 more source

Joint Beamforming Design for Active RIS-Assisted ISAC Systems with Transmitter Hardware Impairments. [PDF]

Sensors (Basel)
Li Z, Hu J, Xing J.
europepmc   +1 more source

Coordinated beamforming with neural networks

reservedBeamforming algorithms have a huge importance in modern wireless communication systems. They allow an important improvement in the final performance, but complex iterative algorithms might be required to solve the beamforming design problem. This
CONCA, GIULIO
core  

System-Level Hardware-Waveform Co-Design for Micro-UAV Radar Sensors: Suppressing Noise Folding in Extreme SWaP-C SSDBF Arrays. [PDF]

Sensors (Basel)
Dai X, Xie K, Wang Y.
europepmc   +1 more source

SINR-Based User Clustering for Downlink NOMA Systems with Limited Channel Information. [PDF]

Sensors (Basel)
Kim W, Nguyen NT, Jeon T.
europepmc   +1 more source