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2020 Index IEEE Transactions on Wireless Communications Vol. 19
2020
IEEE Transactions on Wireless Communications
Preserved Fulltext
., Machine Learning-Enabled LOS/NLOS Identification for MIMO Systems in Dynamic Environments; TWC June 2020 3643-3657 Huang, C., see Yang, M., TWC Sept. 2020 5860-5874 Huang, D., Tao, X., Jiang, C., ...
., +, TWC Jan. 2020 547-562
Multi-Mode OAM Radio Waves: Generation, Angle of Arrival Estimation
and Reception With UCAs. ...
Lv, L., +, TWC Oct. 2020 6486-6503 Multi-Mode OAM Radio Waves: Generation, Angle of Arrival Estimation and Reception With UCAs. ...
doi:10.1109/twc.2020.3044507
fatcat:ie4rwz4dgvaqbaxf3idysubc54
2020 Index IEEE Transactions on Vehicular Technology Vol. 69
2020
IEEE Transactions on Vehicular Technology
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., Toward Swarm Coordination: Topol-ogy-Aware Inter-UAV Routing Optimization; TVT Sept. 2020 10177-10187 Hong, P., see Li, R., TVT April 2020 4006-4018 Hong, P., see Xu, J., TVT June 2020 6688-6698 Hong ...
., TVT Oct. 2020 11743-11755 A MIMO Detector With Deep Learning in the Presence of Correlated Interference. ...
Xiong, Y., TVT June 2020 6838-6842 A MIMO Detector With Deep Learning in the Presence of Correlated Interference. ...
doi:10.1109/tvt.2021.3055470
fatcat:536l4pgnufhixneoa3a3dibdma
2021 Index IEEE Transactions on Vehicular Technology Vol. 70
2021
IEEE Transactions on Vehicular Technology
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., +, TVT Dec. 2021 13340-13350 Deep Learning. Wu, Y., +, TVT Jan. 2021 158-172 Connectivity-Aware 3D UAV Path Design With Deep Reinforcement Learn-ing. ...
Gong, M., +, TVT Oct. 2021 9634-9645 AoA Estimation for OAM Communication Systems With Mode-Frequency Multi-Time ESPRIT Method. ...
doi:10.1109/tvt.2022.3151213
fatcat:vzuzqu54irebpibzp3ykgy5nca
2020 Index IEEE Photonics Journal Vol. 12
2020
IEEE Photonics Journal
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., +, JPHOT April 2020
3900113
Deep learning
Model-Aware End-to-End Learning for SISO Optical Wireless Communi-
cation Over Poisson Channel. ...
., +, JPHOT Dec. 2020
7103507
Interference (signal)
Phase Calibration of On-Chip Optical Phased Arrays via Interference Tech-
nique. ...
doi:10.1109/jphot.2021.3050278
fatcat:lbfms2rznnhurdanu5rfora5pe
A Survey on Machine Learning for Optical Communication [Machine Learning View]
[article]
2019
arXiv
pre-print
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Machine Learning (ML) for Optical Communication (OC) is certainly a hot topic emerged recently and will continue to raise interest at least for the next few years. ...
Accordingly, tutorial investigations are quiet necessary in this filed to help researchers be aware about the last progressions and cavities of this field. ...
The inter-band cross phase modulations between users [42] as well as inter-user interference [43] could severely degrade the performance of multi-user OC systems. ...
arXiv:1909.05148v1
fatcat:t635duaufrhohb4mteophpjqra
2020 Index Journal of Lightwave Technology Vol. 38
2020
Journal of Lightwave Technology
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., Latency-Aware Task Peer Offloading on Overloaded Server in Multi-Access Edge Computing System Interconnected by Metro Optical Networks; 5949-5961 Huang, S., see Tan, T., JLT Dec. 1, 2020 6591-6599 ...
2734 -2739 Nomoto, H., see Matsuura, M., JLT Jan. 15, 2020 401-408 Noor, S.L., Dens, K., Reynaert, P., Catthoor, F., Lin, D., Van Dorpe, P., and Naeemi, A., Modeling and Optimization of Plasmonic Detectors ...
Huang, N., +, JLT Oct. 15, 2020 5695-5707 Dimming-Aware Deep Learning Approach for OOK-Based Visible Light Communication. ...
doi:10.1109/jlt.2021.3055125
fatcat:u7gqk2ifxrdhrpzjh5uzgv3j6q
Retrofitting FSO Systems in Existing RF Infrastructure: A Non-Zero-Sum Game Technology
2021
IEEE Open Journal of the Communications Society
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Diversity is not restricted to OAM-only modes derived from LG mode basis but can cover modes from different mode bases, such as LG and HG modes. ...
GAN is a deep neural network that learns to generate new data with the same statistics of the learning set [111] . ...
doi:10.1109/ojcoms.2021.3130645
fatcat:klbaty7pe5gqlfj45offj775by
2019 Index IEEE Wireless Communications Letters Vol. 8
2019
IEEE Wireless Communications Letters
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Yang, S., +, LWC April 2019 608-611 Diagnosis of Calibration State for Massive Antenna Array via Deep Learning. ...
Wu, J., +, LWC Dec. 2019 1722-1726
Deep learning
Deep Learning for Spectrum Sensing. ...
doi:10.1109/lwc.2019.2961756
fatcat:bwxehcl4ejew7a6m66prb6s4z4
Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future
2019
IEEE Access
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However, shrinking the cell-size (e.g., tiny-cells) also requires suitable management of the increased inter-cell interference to the cell-edge users. ...
new modes of information processing. ...
doi:10.1109/access.2019.2909490
fatcat:27eqrqfadfcnfmultqjnykweai
On the Road to 6G: Visions, Requirements, Key Technologies and Testbeds
[article]
2023
arXiv
pre-print
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Finally, lessons learned to date concerning 6G networks are discussed. ...
scenario due to orthogonality between OAM modes compared with the conventional MIMO system. ...
Thus multiple OAM modes can coexist and transmit data simultaneously over a single communication link. ...
arXiv:2302.14536v1
fatcat:6hsm7tn4kvaqhnmabw3s5nf4ka
2021 Index Journal of Lightwave Technology Vol. 39
2021
Journal of Lightwave Technology
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., +, JLT April 1, 2021 1968-1975 Model-Aware Deep Learning Method for Raman Amplification in Few-Mode Fibers. ...
., +, JLT March 1, 2021 1243-1254 Model-Aware Deep Learning Method for Raman Amplification in Few-Mode Fibers. ...
doi:10.1109/jlt.2021.3139461
fatcat:exvpvueqifaezc36oxjrpywvl4
Implementation of Fog computing for reliable E-health applications
2015
2015 49th Asilomar Conference on Signals, Systems and Computers
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We will mathematically analyze the system accordingly and provide expressions for the capture probabilities of the underlying sparse multiuser detector. ...
The analysis focuses on inter-cell interference. ...
This leads to inter-symbol interference in the received signal. ...
doi:10.1109/acssc.2015.7421170
dblp:conf/acssc/CraciunescuMMKP15
fatcat:qm6mki5z6bcvrfimkmqjyrxaxm
A Review–Unguided Optical Communications: Developments, Technology Evolution, and Challenges
2023
Electronics
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discusses the complete evolution of free-space optical (FSO) communication, also known as unguided optical communication (UOC) technologies, all the way back to ancient man's fire to today's machine-learning-supported ...
Watnik proposed a machine-learning-based approach to demultiplex the OAM-carrying FSO beams at the receiver. ...
As an AI branch, machine learning (ML) or deep learning (DL) seeks a way to apply a data-driven approach to solving many conventional problems in vehicular networks. ...
doi:10.3390/electronics12081922
fatcat:foj2bviffbdjzktcutquh5wt4u
Ping-pong beam training for reciprocal channels with delay spread
2015
2015 49th Asilomar Conference on Signals, Systems and Computers
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We consider FDD systems for which implicit feedback via channel reciprocity is not available. ...
The proposed detector requires no training signals and outerforms conentional covariance matrix based detectors which require training. ...
The analysis focuses on inter-cell interference. ...
doi:10.1109/acssc.2015.7421451
dblp:conf/acssc/CarvalhoA15
fatcat:mqokuvnh3zg45licnfbgxyvxfu
Safeguarding Next Generation Multiple Access Using Physical Layer Security Techniques: A Tutorial
[article]
2024
arXiv
pre-print
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To address this specific challenge, the superimposed transmission of NOMA can be explored as new opportunities for security aware design, for example, multiuser interference inherent in NOMA can be constructively ...
Nevertheless, the support of massive access via NOMA leads to additional security threats, due to the open nature of the air interface, the broadcast characteristic of radio propagation as well as intertwined ...
A multi-user detector (MUD) and K decoder (DEC) make up the inter-SIC module. ...
arXiv:2403.16477v1
fatcat:jc3hu4bxgbfudibqp2nn334jdi
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