Miao Liu

Orcid: 0000-0003-1385-266X

Affiliations:

Nanjing University of Posts and Telecommunications, College of Telecommunications and Information Engineering, China
Southeast University, National Mobile Communications Research Laboratory, Nanjing, China

According to our database¹, Miao Liu authored at least 39 papers between 2016 and 2023.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

Legend:

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In proceedings

Article

PhD thesis

Dataset

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Bibliography

2023

Joint User Pairing and Resource Allocation in Air-to-Ground Communication-Caching-Charging Integrated Network Based on NOMA.

[BibT_eX]

[DOI]

IEEE Trans. Veh. Technol., December, 2023

Minimizing Delay for MIMO-NOMA Resource Allocation in UAV-Assisted Caching Networks.

[BibT_eX]

[DOI]

IEEE Trans. Veh. Technol., April, 2023

2022

Unsupervised Learning-Inspired Power Control Methods for Energy-Efficient Wireless Networks Over Fading Channels.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., 2022

2021

QoS-Oriented Dynamic Power Allocation in NOMA-Based Wireless Caching Networks.

[BibT_eX]

[DOI]

IEEE Wirel. Commun. Lett., 2021

Cross-Layer Resource Allocation for UAV-Assisted Wireless Caching Networks With NOMA.

[BibT_eX]

[DOI]

IEEE Trans. Veh. Technol., 2021

Joint UL/DL Resource Allocation for UAV-Aided Full-Duplex NOMA Communications.

[BibT_eX]

[DOI]

IEEE Trans. Commun., 2021

A weighted-beam-superposition method for mmWave massive MIMO-NOMA systems.

[BibT_eX]

[DOI]

Phys. Commun., 2021

Multiple Unmanned-Aerial-Vehicles Deployment and User Pairing for Nonorthogonal Multiple Access Schemes.

[BibT_eX]

[DOI]

IEEE Internet Things J., 2021

Joint Multislice and Cooperative Detection Aided Residual Network for Scenario Identification in Vehicle-to-Vehicle Communication Systems.

[BibT_eX]

[DOI]

Proceedings of the 94th IEEE Vehicular Technology Conference, 2021

Resource Allocation for UAV-Assisted MIMO-NOMA Wireless Caching Networks.

[BibT_eX]

[DOI]

Proceedings of the 21st IEEE International Conference on Software Quality, 2021

Complex Deep Neural Network Based Intelligent Signal Detection Methods for OFDM-IM Systems.

[BibT_eX]

[DOI]

Proceedings of the Joint European Conference on Networks and Communications & 6G Summit, 2021

2020

6G: Opening New Horizons for Integration of Comfort, Security, and Intelligence.

[BibT_eX]

[DOI]

IEEE Wirel. Commun., 2020

Secrecy Outage Analysis of Transmit Antenna Selection Assisted With Wireless Power Beacon.

[BibT_eX]

[DOI]

IEEE Trans. Veh. Technol., 2020

LightAMC: Lightweight Automatic Modulation Classification via Deep Learning and Compressive Sensing.

[BibT_eX]

[DOI]

IEEE Trans. Veh. Technol., 2020

Reconciliation Problem in Polar Integrated Navigation Considering Coordinate Frame Transformation.

[BibT_eX]

[DOI]

IEEE Trans. Veh. Technol., 2020

Semi-Supervised Machine Learning Aided Anomaly Detection Method in Cellular Networks.

[BibT_eX]

[DOI]

IEEE Trans. Veh. Technol., 2020

Smoothing-Aided Support Vector Machine Based Nonstationary Video Traffic Prediction Towards B5G Networks.

[BibT_eX]

[DOI]

IEEE Trans. Veh. Technol., 2020

Robust automatic modulation classification based on convolutional and recurrent fusion network.

[BibT_eX]

[DOI]

Phys. Commun., 2020

Toward Self-Adaptive Selection of Kernel Functions for Support Vector Regression in IoT-Based Marine Data Prediction.

[BibT_eX]

[DOI]

IEEE Internet Things J., 2020

UAV-Aided Air-to-Ground Cooperative Nonorthogonal Multiple Access.

[BibT_eX]

[DOI]

IEEE Internet Things J., 2020

Generalized Flight Delay Prediction Method Using Gradient Boosting Decision Tree.

[BibT_eX]

[DOI]

Proceedings of the 91st IEEE Vehicular Technology Conference, 2020

Convolutional Neural Network Aided Signal Modulation Recognition in OFDM Systems.

[BibT_eX]

[DOI]

Proceedings of the 91st IEEE Vehicular Technology Conference, 2020

Deep Learning Method for Generalized Modulation Classification under Varying Noise Condition.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Computing, Networking and Communications, 2020

2019

Data-Driven Deep Learning for Automatic Modulation Recognition in Cognitive Radios.

[BibT_eX]

[DOI]

IEEE Trans. Veh. Technol., 2019

Deep Learning-Inspired Message Passing Algorithm for Efficient Resource Allocation in Cognitive Radio Networks.

[BibT_eX]

[DOI]

IEEE Trans. Veh. Technol., 2019

Robust Resource Allocation and Power Splitting in SWIPT Enabled Heterogeneous Networks: A Robust Minimax Approach.

[BibT_eX]

[DOI]

IEEE Internet Things J., 2019

DSF-NOMA: UAV-Assisted Emergency Communication Technology in a Heterogeneous Internet of Things.

[BibT_eX]

[DOI]

Miao Liu

Jie Yang

Guan Gui

IEEE Internet Things J., 2019

Deep Cognitive Perspective: Resource Allocation for NOMA-Based Heterogeneous IoT With Imperfect SIC.

[BibT_eX]

[DOI]

Miao Liu

Tiecheng Song

Guan Gui

IEEE Internet Things J., 2019

Dynamic User Grouping-Based NOMA Over Rayleigh Fading Channels.

[BibT_eX]

[DOI]

IEEE Access, 2019

UL-CSI Data Driven Deep Learning for Predicting DL-CSI in Cellular FDD Systems.

[BibT_eX]

[DOI]

IEEE Access, 2019

2018

Anti-Shadowing Resource Allocation for General Mobile Cognitive Radio Networks.

[BibT_eX]

[DOI]

IEEE Access, 2018

Energy-efficient cooperative spectrum sensing for hybrid spectrum sharing cognitive radio networks.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Wireless Communications and Networking Conference, 2018

Resource Allocation for NOMA based Heterogeneous IoT with Imperfect SIC: A Deep Learning Method.

[BibT_eX]

[DOI]

Proceedings of the 29th IEEE Annual International Symposium on Personal, 2018

Multi-Efficiency Based Resource Allocation for Cognitive Radio Networks with Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the 10th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2018

2017

Robust Cooperative Spectrum Sensing against Probabilistic SSDF Attack in Cognitive Radio Networks.

[BibT_eX]

[DOI]

Proceedings of the 86th IEEE Vehicular Technology Conference, 2017

Two-Stage Credit Threshold on Cooperative Spectrum Sensing to Exclude Malicious Users in Mobile Cognitive Radio Networks.

[BibT_eX]

[DOI]

Proceedings of the 85th IEEE Vehicular Technology Conference, 2017

2016

Spectrum Sensing and the Utilization of Spectrum Opportunity Tradeoff in Cognitive Radio Network.

[BibT_eX]

[DOI]

IEEE Commun. Lett., 2016

Subchannel and power allocation for OFDMA-based mobile cognitive radio networks.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Wireless Communications & Signal Processing, 2016

Interference Minimization Approach for Joint Resource Allocation in Cognitive OFDMA Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE 83rd Vehicular Technology Conference, 2016

Miao Liu

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