Folgen
Sicong Liu (刘思聪)
Titel
Zitiert von
Zitiert von
Jahr
Double kill: Compressive-sensing-based narrow-band interference and impulsive noise mitigation for vehicular communications
S Liu, F Yang, W Ding, J Song
IEEE Transactions on Vehicular Technology 65 (7), 5099-5109, 2015
1042015
Novel visible light communication approach based on hybrid OOK and ACO-OFDM
F Yang, J Gao, S Liu
IEEE photonics technology letters 28 (14), 1585-1588, 2016
1002016
Reinforcement learning-based downlink interference control for ultra-dense small cells
L Xiao, H Zhang, Y Xiao, X Wan, S Liu, LC Wang, HV Poor
IEEE Transactions on Wireless Communications 19 (1), 423-434, 2019
922019
Deep reinforcement learning-enabled secure visible light communication against eavesdropping
L Xiao, G Sheng, S Liu, H Dai, M Peng, J Song
IEEE transactions on communications 67 (10), 6994-7005, 2019
912019
Design and optimization on training sequence for mmWave communications: A new approach for sparse channel estimation in massive MIMO
X Ma, F Yang, S Liu, J Song, Z Han
IEEE Journal on Selected Areas in Communications 35 (7), 1486-1497, 2017
882017
UAV anti-jamming video transmissions with QoE guarantee: A reinforcement learning-based approach
L Xiao, Y Ding, J Huang, S Liu, Y Tang, H Dai
IEEE Transactions on Communications 69 (9), 5933-5947, 2021
702021
Block sparse Bayesian learning-based NB-IoT interference elimination in LTE-advanced systems
S Liu, F Yang, J Song, Z Han
IEEE Transactions on Communications 65 (10), 4559-4571, 2017
682017
Sparse channel estimation for MIMO-OFDM systems in high-mobility situations
X Ma, F Yang, S Liu, J Song, Z Han
IEEE Transactions on Vehicular Technology 67 (7), 6113-6124, 2018
612018
Channel estimation for wideband underwater visible light communication: a compressive sensing perspective
X Ma, F Yang, S Liu, J Song
Optics express 26 (1), 311-321, 2018
522018
Eliminating NB-IoT interference to LTE system: A sparse machine learning-based approach
S Liu, L Xiao, Z Han, Y Tang
IEEE Internet of Things Journal 6 (4), 6919-6932, 2019
512019
Narrowband interference cancelation based on priori aided compressive sensing for DTMB systems
S Liu, F Yang, J Song
IEEE Transactions on Broadcasting 61 (1), 66-74, 2014
442014
An optimal interleaving scheme with maximum time-frequency diversity for PLC systems
S Liu, F Yang, J Song
IEEE Transactions on Power Delivery 31 (3), 1007-1014, 2014
382014
Learning based power control for mmWave massive MIMO against jamming
Z Xiao, B Gao, S Liu, L Xiao
2018 IEEE Global Communications Conference (GLOBECOM), 1-6, 2018
372018
Sparsity-aware channel estimation for mmWave massive MIMO: A deep CNN-based approach
S Liu, X Huang
China Communications 18 (6), 162-171, 2021
352021
Spectrally efficient CSI acquisition for power line communications: A Bayesian compressive sensing perspective
W Ding, Y Lu, F Yang, W Dai, P Li, S Liu, J Song
IEEE Journal on Selected Areas in Communications 34 (7), 2022-2032, 2016
352016
Structured compressive sensing-based channel estimation for time frequency training OFDM systems over doubly selective channel
X Ma, F Yang, S Liu, W Ding, J Song
IEEE Wireless Communications Letters 6 (2), 266-269, 2017
332017
Change detection from multi-temporal remote sensing images by integrating multiple features
P Du, S Liu
Yaogan Xuebao- Journal of Remote Sensing 16 (4), 663-677, 2012
332012
Nonorthogonal time–frequency training-sequence-based CSI acquisition for MIMO systems
W Ding, F Yang, S Liu, X Wang, J Song
IEEE Transactions on Vehicular Technology 65 (7), 5714-5719, 2015
322015
Two-dimensional structured-compressed-sensing-based NBI cancelation exploiting spatial and temporal correlations in MIMO systems
S Liu, F Yang, W Ding, X Wang, J Song
IEEE Transactions on Vehicular Technology 65 (11), 9020-9028, 2016
312016
Firefly algorithm-based cellular automata for reproducing urban growth and predicting future scenarios
Q Li, Y Feng, X Tong, Y Zhou, P Wu, H Xie, Y Jin, P Chen, S Liu, X Xv, ...
Sustainable Cities and Society 76, 103444, 2022
302022
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20