Shengliang Peng
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View article: Deep Learning Based Modulation Classification in Radio Access Network
Deep Learning Based Modulation Classification in Radio Access Network Open
The growing demand for traffic shaping and manipulation for efficient last-mile coverage has driven extensive research using emerging artificial intelligence to overcome the capacity hurdle in next-generation wireless systems. In the radio…
View article: Radio spectrum awareness using deep learning: Identification of fading channels, signal distortions, medium access control protocols, and cellular systems
Radio spectrum awareness using deep learning: Identification of fading channels, signal distortions, medium access control protocols, and cellular systems Open
Radio spectrum awareness, including understanding radio signal activities, is crucial for improving spectrum utilization, detecting security vulnerabilities, and supporting adaptive transmissions. Related tasks include spectrum sensing, id…
View article: Deep Learning-Based Signal-To-Noise Ratio Estimation Using Constellation Diagrams
Deep Learning-Based Signal-To-Noise Ratio Estimation Using Constellation Diagrams Open
Signal-to-noise ratio (SNR) estimation is a fundamental task of spectrum management and data transmission. Existing methods for SNR estimation usually suffer from significant estimation errors when SNR is low. This paper proposes a deep le…
View article: Blind multiband spectrum sensing scheme by combining model order selection with clustering analysis
Blind multiband spectrum sensing scheme by combining model order selection with clustering analysis Open
This letter presents a robust blind multiband detection (BMD) scheme for cognitive radio (CR). In the proposed scheme, the BMD problem is firstly transformed into a model order selection (MOS) problem, and then an effective clustering meth…
View article: Adaptive Algorithms for Bayesian Spectrum Sensing Based on Markov Model
Adaptive Algorithms for Bayesian Spectrum Sensing Based on Markov Model Open
Spectrum sensing (SS) is one of the fundamental tasks for cognitive radio.In SS, decisions can be made via comparing the test statistics with a threshold.Conventional adaptive algorithms for SS usually adjust their thresholds according to …
View article: Prioritized Secondary User Access Control in Cognitive Radio Networks
Prioritized Secondary User Access Control in Cognitive Radio Networks Open
In cognitive radio networks, a secondary user access control (SUAC) technique has been utilized to improve network management and system security, in which a jamming signal is injected to degrade the spectrum sensing performance of unautho…
View article: Automatic Cashier System Based on Meal Plate Detection Using Deep Learning
Automatic Cashier System Based on Meal Plate Detection Using Deep Learning Open
Deep learning (DL) is an important branch of machine learning (ML) that has excellent performance in recognition and detection tasks.Currently, most self-service restaurants/canteens are utilizing traditional manual cashier approaches, whi…
View article: Fast Cooperative Energy Detection under Accuracy Constraints in Cognitive Radio Networks
Fast Cooperative Energy Detection under Accuracy Constraints in Cognitive Radio Networks Open
Cooperative energy detection (CED) is a key technique to identify the spectrum holes in cognitive radio networks. Previous study on this technique mainly aims at improving the detection accuracy, while paying little attention to the perfor…
View article: An Improved Design of Gallager Mapping for LDPC-coded BICM-ID System
An Improved Design of Gallager Mapping for LDPC-coded BICM-ID System Open
Gallager mapping uses different signal points with different probabilities by assigning several labels for one signal point, and thus provides a promising approach to achieving shaping gains. An important issue in Gallager mapping is how t…
View article: Analysis and optimization of sensing agility in cognitive radio
Analysis and optimization of sensing agility in cognitive radio Open
Cognitive radio (CR) technology provides a new approach to solve the problem of wireless spectrum resource scarcity by allowing secondary users (SUs) to access the licensed spectrum in case that SUs do not interfere primary user (PU).One o…
View article: Maximum Likelihood Estimation and Centroiding Hybrid RSSI-based Indoor Positioning
Maximum Likelihood Estimation and Centroiding Hybrid RSSI-based Indoor Positioning Open
RSSI-based positioning technology suffers from accuracy degradation due to complex indoor environment, and traditional weighted centroid algorithm hardly satisfies people's accuracy requirements.In this paper, a hybrid RSSI based positioni…
View article: Bayesian Energy Detection Based on Temporal Persistence
Bayesian Energy Detection Based on Temporal Persistence Open
Energy detection is one of the classical methods for spectrum sensing in Cognitive radio (CR).Previous research on energy detection is almost based on single time slot, while the communication process of the primary user (PU) is hardly com…
View article: Fast Two-Step Energy Detection for Spectrum Sensing
Fast Two-Step Energy Detection for Spectrum Sensing Open
Spectrum sensing is one of the key tasks in cognitive radio. This paper proposes a fast two-step energy detection (FED) algorithm for spectrum sensing via improving the sampling process of conventional energy detection (CED). The algorithm…