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A survey on machine-learning techniques in cognitive radios
In this survey paper, we characterize the learning problem in cognitive radios (CRs) and
state the importance of artificial intelligence in achieving real cognitive communications …
state the importance of artificial intelligence in achieving real cognitive communications …
A survey on radio resource allocation in cognitive radio sensor networks
Wireless sensor networks (WSNs) use the unlicensed industrial, scientific, and medical
(ISM) band for transmissions. However, with the increasing usage and demand of these …
(ISM) band for transmissions. However, with the increasing usage and demand of these …
Reinforcement learning algorithms with function approximation: Recent advances and applications
X Xu, L Zuo, Z Huang - Information sciences, 2014 - Elsevier
In recent years, the research on reinforcement learning (RL) has focused on function
approximation in learning prediction and control of Markov decision processes (MDPs). The …
approximation in learning prediction and control of Markov decision processes (MDPs). The …
Reinforcement learning-based routing protocols for vehicular ad hoc networks: A comparative survey
Vehicular-ad hoc networks (VANETs) hold great importance because of their potentials in
road safety improvement, traffic monitoring, and in-vehicle infotainment services. Due to high …
road safety improvement, traffic monitoring, and in-vehicle infotainment services. Due to high …
Intelligent wireless communications enabled by cognitive radio and machine learning
The ability to intelligently utilize resources to meet the need of growing diversity in services
and user behavior marks the future of wireless communication systems. Intelligent wireless …
and user behavior marks the future of wireless communication systems. Intelligent wireless …
Learning and reasoning in cognitive radio networks
Cognitive radio networks challenge the traditional wireless networking paradigm by
introducing concepts firmly stemmed into the Artificial Intelligence (AI) field, ie, learning and …
introducing concepts firmly stemmed into the Artificial Intelligence (AI) field, ie, learning and …
Learning transfer-based adaptive energy minimization in embedded systems
Embedded systems execute applications with varying performance requirements. These
applications exercise the hardware differently depending on the computation task …
applications exercise the hardware differently depending on the computation task …
Federated learning for 6G: Paradigms, taxonomy, recent advances and insights
Artificial Intelligence (AI) is expected to play an instrumental role in the next generation of
wireless systems, such as sixth-generation (6G) mobile network. However, massive data …
wireless systems, such as sixth-generation (6G) mobile network. However, massive data …
Distributed heuristically accelerated Q-learning for robust cognitive spectrum management in LTE cellular systems
In this paper, we propose an algorithm for dynamic spectrum access (DSA) in LTE cellular
systems-distributed ICIC accelerated Q-learning (DIAQ). It combines distributed …
systems-distributed ICIC accelerated Q-learning (DIAQ). It combines distributed …
[ספר][B] Cognitive radio communication and networking: Principles and practice
The author presents a unified treatment of this highly interdisciplinary topic to help define the
notion of cognitive radio. The book begins with addressing issues such as the fundamental …
notion of cognitive radio. The book begins with addressing issues such as the fundamental …