frequency allocation; hidden Markov models; learning (artificial intelligence); radio access networks; telecommunication computing; DSA network; HMM; SOM; dynamic spectrum access radio identification; hidden Markov models; licensed spectrum; machine learning; primary users; radiofrequency environment; secondary users; self organizing maps; spectral crowding; static frequency allocation; two operating modes; Cognitive radio; Hidden Markov models; Neurons; Radio frequency; Sensors; Training; Vectors; Cognitive Radio; Dynamic Spectrum Access; Machine Learning;
机译:动态频谱访问的认知无线电-动态频谱访问的多相多径无线电电路
机译:认知无线电网络中基于机器学习的机会频谱访问
机译:基于大数据分析和机器学习的长期频谱监测,用于基于云的无线电接入网络
机译:动态频谱接入无线电识别的机器学习方法
机译:基于学习的自适应设计,用于认知无线电网络中的动态频谱访问。
机译:基于增强学习的认知无线电传感器网络动态频谱接入框架
机译:使用机器学习的认知无线电的新型QoS感知主动频谱访问技术