Results 41 to 50 of about 856,367 (318)

Research on OFDM channel estimation of mine based on improved SRCNN

open access: yesMeikuang Anquan
Aiming at the problem of low accuracy of traditional channel estimation algorithms in the harsh environment of underground coal mines, this paper proposes an improved Super Resolution Convdutional Network (SRCNN) for channel estimation.
Anyi WANG, Yan LIANG
doaj   +1 more source

Deep Learning-Based Wireless Channel Estimation for MIMO Uncoded Space-Time Labeling Diversity

open access: yesIEEE Access, 2020
Uncoded space-time labeling diversity (USTLD) is a space-time block coded (STBC) system with labeling diversity applied to it to increase wireless link reliability without compromising the spectral efficiency.
Bhekisizwe Mthethwa, Hongjun Xu
doaj   +1 more source

Channel Estimation for Millimeter-Wave Massive MIMO with Hybrid Precoding over Frequency-Selective Fading Channels

open access: yes, 2016
Channel estimation for millimeter-wave (mmWave) massive MIMO with hybrid precoding is challenging, since the number of radio frequency (RF) chains is usually much smaller than that of antennas.
Dai, Linglong   +3 more
core   +1 more source

Artificial intelligence for channel estimation in multicarrier systems for B5G/6G communications: a survey

open access: yesEURASIP Journal on Wireless Communications and Networking, 2022
Multicarrier modulation allows for deploying wideband systems resilient to multipath fading channels, impulsive noise, and intersymbol interference compared to single-carrier systems.
Evandro C. Vilas Boas   +4 more
doaj   +1 more source

Detection of Channel Variations to Improve Channel Estimation Methods [PDF]

open access: yesCircuits, Systems, and Signal Processing, 2014
“The final publication is available at Springer via http://dx.doi.org/[10.1007/s00034-014-9767-8]” [Abstract] In current digital communication systems, channel information is typically acquired by supervised approaches that use pilot symbols included in the transmit frames.
Dapena, Adriana   +3 more
openaire   +4 more sources

Improved Blind Channel Estimation Performance by Nearby Channel Estimation

open access: yes, 2019
To obtain channel information for further data transmission, the blind channel estimation needs no pilot signal in advance is a considerable algorithm. To improve performance of the blind channel estimation schemes, we have employed the channel estimation with pilot signals by adjacent users; the acquired estimation channel information of the adjacent ...
Wu, Jia-Chyi, Kao, Zhen-Wei
openaire   +2 more sources

Compressive sensing based channel estimation for NC-OFDM systems in cognitive radio context

open access: yesTongxin xuebao, 2011
A new channel estimation based on compressive sensing(CS)in non-contiguous orthogonal frequency division multiplexing(NC-OFDM)system was proposed.As for NC-OFDM systems in cognitive radio context,the infrastructure of CS-based channel estimation,the ...
Xue-yun HE, Rong-fang SONG, Ke-qin ZHOU
doaj   +2 more sources

Infection Models for Pine Wilt Disease on the Basis of Vector Behaviors

open access: yesPopulation Ecology, EarlyView.
Infection models for pine wilt disease without vector density were built to estimate the transmission coefficient of the pathogenic nematode. The models successfully simulated the annual change in the density of infected trees for four pine stands. ABSTRACT Pine wilt disease is caused by the pinewood nematode (Bursaphelenchus xylophilus Steiner et ...
Katsumi Togashi
wiley   +1 more source

Wireless channel estimation for high-speed rail communications: Challenges, solutions and future directions

open access: yesHigh-Speed Railway, 2023
With the development of High-Speed Rail (HSR), countries and individual passengers alike have enjoyed far ranging benefits as a result – economic, social, environment and in added convenience.
Xuying Chen   +4 more
doaj   +1 more source

From omics to AI—mapping the pathogenic pathways in type 2 diabetes

open access: yesFEBS Letters, EarlyView.
Integrating multi‐omics data with AI‐based modelling (unsupervised and supervised machine learning) identify optimal patient clusters, informing AI‐driven accurate risk stratification. Digital twins simulate individual trajectories in real time, guiding precision medicine by matching patients to targeted therapies.
Siobhán O'Sullivan   +2 more
wiley   +1 more source

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