Use this example as part of a complete deep learning workflow: The Capture and Label NR and LTE Signals for AI Training (Wireless Testbench) example shows how to scan, capture, and label bandwidths with 5G NR and LTE signals using a SDR. This example shows how to train a semantic...
deep recurrent reinforced learningmultihop cognitive radio networkQ-routingspectrum sensingCognitive radio network (CRN) is a promising technology that mitigates the scarcity of spectrum. The main challenge faced in the opportunistic CRN is the spectrum sensing (SS). The traditional methods of SS use ...
利用LSTM结构来挖掘PU活动模式;(2)提出的CNN-LSTM检测器不受信号噪声模型假设的影响;(3)仿真结果表明,在有噪声不确定性(NU)的场景和没有NU的场景下,CNN-LSTM检测器的性能优于基准检测器。
Spectrum Sensing Using Optimized Deep Learning Techniques in Reconfigurable Embedded Systems The exponential growth of Internet of Things (IoT) and 5G networks has resulted in maximum users, and the role of cognitive radio has become pivotal in han... P Kumar,P Selvan - 《Intelligent Automation ...
In this paper, the problem of dynamic spectrum sensing and aggregation is investigated in a wireless network containing N correlated channels, where these channels are occupied or vacant following an unknown joint 2-state Markov model. At each time slot, a single cognitive user with certain bandwid...
摘要 The state-of-the-art goodness-of-fit (GoF) test algorithms for spectrum sensing directly make decisions based on temp... 关键词 Cognitive radio / spectrum sensing / goodness-of-fit test / random...
the works by big companies likeGoogle,Microsoft, and IBM, but these only cover a small portion of the spectrum, or use high cost sensing stations limiting their ability to be deployed on a wide scale. Electrosense solves these problems by using low cost RTL-SDRs, and a crowd sourcing ...
Deep learning using an LSTM recurrent neural network As mobility state prediction requires sequential analysis as well as the ability to learn long-term dependencies, the model of choice for DL-MSS was a bidirectional Long Short Term Memory (LSTM) network45,54. Using a bidirectional network increa...
Xie L, Wan Q (2017) Cyclic feature based modulation recognition using compressive sensing. IEEE Wirel Commun Lett 6(3):402–405 Google Scholar Wei Y, Fang S, Wang X (2019) Automatic modulation classification of digital communication signals using SVM based on hybrid features, cyclostationary, ...
Deep Learning based Cooperative Spectrum Sensing with Crowd Sensors using Data Cleansing Algorithm M N Giri PrasadD Raghunatha RaoT Jayachandra Prasad Oct 2022 Cooperative sensing is a solution to augment the performance of detection, in which Secondary Users (SU) cooperate with each other for sens...