Name
Affiliation
Papers
YUAN MA
Beijing Univ Posts & Telecommun, Beijing 100876, Peoples R China
24
Collaborators
Citations 
PageRank 
41
24
8.49
Referers 
Referees 
References 
80
198
111
Search Limit
100198
Title
Citations
PageRank
Year
Deep Learning-Based Spectrum Sensing in Space-Air-Ground Integrated Networks20.362021
Data-Driven Beam Tracking for Mobile Millimeter-Wave Communication Systems Without Channel Estimation00.342021
Dual-Net for Joint Channel Estimation and Data Recovery in Grant-free Massive Access00.342021
Optimal Linear Cooperation for Signal Classification in Cognitive Communication Networks.00.342020
Clock Synchronization in Wireless Networks Using Matrix Completion-Based Maximum Likelihood Estimation00.342020
TV White Space Spectrum Analysis Based on Machine Learning00.342019
Minimizing Misclassification for Cooperative Spectrum Sensing Using <inline-formula><tex-math notation="LaTeX">$M$</tex-math></inline-formula>-Ary Hypothesis Testing00.342019
Data-Driven Measurement of Receiver Sensitivity in Wireless Communication Systems10.412019
Low-Complexity Compressive Spectrum Sensing for Large-Scale Real-Time Processing.00.342018
Autonomous Compressive-Sensing-Augmented Spectrum Sensing.00.342018
Joint Sub-Nyquist Spectrum Sensing Scheme With Geolocation Database Over TV White Space.10.342018
Distributed Compressive Sensing Augmented Wideband Spectrum Sharing for Cognitive IoT30.382018
Real-Time Adaptively Regularized Compressive Sensing in Cognitive Radio Networks.00.342018
An Efficient Joint Sub-Nyquist Spectrum Sensing Scheme With Geolocation Database Over Tv White Space00.342017
Blind cooperating user selection for compressive spectrum sensing in cognitive radio networks.00.342017
Sparsity Independent Sub-Nyquist Rate Wideband Spectrum Sensing on Real-Time TV White Space.20.382017
Blind Compressive Spectrum Sensing in Cognitive Internet of Things.00.342017
Data-assisted sub-Nyquist spectrum sensing00.342016
Autonomous Compressive Spectrum Sensing Approach For 3.5 Ghz Shared Spectrum00.342016
Reliable and Efficient Sub-Nyquist Wideband Spectrum Sensing in Cooperative Cognitive Radio Networks.100.472016
Efficient Blind Cooperative Wideband Spectrum Sensing Based on Joint Sparsity.00.342016
Adaptively Regularized Compressive Spectrum Sensing from Real-Time Signals to Real-Time Processing.00.342016
Sub-Nyquist rate wideband spectrum sensing over TV white space for M2M communications30.382015
Optimization Of Collaborating Secondary Users In A Cooperative Sensing Under Noise Uncertainty20.352013