Konu "Machine Learning" için Bildiri Koleksiyonu listeleme
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Centralized and decentralized ml-enabled integrated terrestrial and non-terrestrial networks
(2023)Non-terrestrial networks (NTNs) are a critical enabler of the persistent connectivity vision of sixth-generation networks, as they can service areas where terrestrial infrastructure falls short. However, the integration ... -
Compressed spectrum sensing using sparse recovery convergence patterns through machine learning classification
(Institute of Electrical and Electronics Engineers Inc., 2019)Despite the well-known success of sub-Nyquist sampling in reducing the hardware and computational costs of spectrum sensing, it still has the shortcoming of requiring a pre-determined spectrum sparsity level. This paper ... -
Estimating multi-dimensional sparsity level for spectrum sensing
(Institute of Electrical and Electronics Engineers Inc., 2023)Identifying spectrum opportunities is a crucial element of efficient spectrum utilization for future wireless networks. Spectrum sensing offers a convenient means for revealing such opportunities. Studies showed that usage ... -
Selection of waveform parameters using machine learning for 5G and beyond
(Institute of Electrical and Electronics Engineers Inc., 2019)Flexibility is one of the essential requirements for future cellular communications technologies. Providing customized communications solutions for each user and service type cannot be possible without the flexibility in ...