IET Communications

Papers
(The H4-Index of IET Communications is 21. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-08-01 to 2025-08-01.)
ArticleCitations
Secrecy performance of transmit antenna selection for underlay MIMO cognitive radio relay networks with energy harvesting152
A joint denoising and deep learning detector for OFDM‐IM131
104
Transmitter selection for secrecy against colluding eavesdroppers with backhaul uncertainty74
An enhanced method for dialect transcription via error‐correcting thesaurus59
IUG‐based beam selection for wideband millimetre wave massive MIMO systems58
Adaptive training‐feedback scheme for FDD in massive MIMO systems53
Computation rate optimization for double‐intelligent reflecting surface aided mobile edge computing system52
Queries allocation in WSNs with fuzzy control system52
Phase‐index correlation delay shift keying modulation44
Blind detection of cyclostationary signals based on multi‐antenna beamforming technology36
Spectrum sharing mechanisms in the unlicensed band: Performance limit and comparison35
Individual identification method of little sample radiation source based on SGDCGAN+DCNN35
RIS assisted wireless networks: Collaborative regulation, deployment mode and field testing35
Multi‐view synergistic enhanced fault recording data for transmission line fault classification34
Completion time minimization for UAV enabled data collection with communication link constrained34
Resource and trajectory optimization for secure communication in RIS assisted UAV‐MEC system31
A high efficient next generation reservoir computing to predict and generate chaos with application for secure communication26
Bat algorithm based semi‐distributed resource allocation in ultra‐dense networks25
Research and implementation of modulation recognition based on cascaded feature fusion24
Recurrent attention convolutional neural network optimise track foreign body detection22
Specific emitter identification by wavelet residual network based on attention mechanism21
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