An overview of medium access control strategies for opportunistic spectrum access in cognitive radio networks
Cognitive radio (CR) is a promising wireless technology that provides efficient spectral
usage. Medium Access Control (MAC) has an important role in several cognitive radio …
usage. Medium Access Control (MAC) has an important role in several cognitive radio …
A survey of dynamic spectrum allocation based on reinforcement learning algorithms in cognitive radio networks
Y Wang, Z Ye, P Wan, J Zhao - Artificial intelligence review, 2019 - Springer
Cognitive radio is an emerging technology that is considered to be an evolution for software
device radio in which cognition and decision-making components are included. The main …
device radio in which cognition and decision-making components are included. The main …
Automatic double-auction mechanism for federated learning service market in Internet of Things
In the past decade, the Artificial Intelligent & Internet of Things (AIoT) has become the
disruptive force resha** our lives and works. Billions of AIoT devices around the world are …
disruptive force resha** our lives and works. Billions of AIoT devices around the world are …
Reinforcement-learning-and belief-learning-based double auction mechanism for edge computing resource allocation
In recent years, we have witnessed the compelling application of the Internet of Things (IoT)
in our daily life, ranging from daily living to industrial production. On account of the …
in our daily life, ranging from daily living to industrial production. On account of the …
Intelligent cognitive spectrum collaboration: Convergence of spectrum sensing, spectrum access, and coding technology
P Cai, Y Zhang - Intelligent and Converged Networks, 2020 - ieeexplore.ieee.org
For a future scenario where everything is connected, cognitive technology can be used for
spectrum sensing and access, and emerging coding technologies can be used to address …
spectrum sensing and access, and emerging coding technologies can be used to address …
The strategy evolution in double auction based on the experience-weighted attraction learning model
The double auction is a widely applicable trading mechanism used to converge to
competitive equilibrium in different markets from which multiple equilibriums and incomplete …
competitive equilibrium in different markets from which multiple equilibriums and incomplete …
Multi-agent reinforcement learning for long-term network resource allocation through auction: A V2X application
We formulate offloading of computational tasks from a dynamic group of mobile agents (eg,
cars) as decentralized decision making among autonomous agents. We design an …
cars) as decentralized decision making among autonomous agents. We design an …
Learning to bid long-term: Multi-agent reinforcement learning with long-term and sparse reward in repeated auction games
We propose a multi-agent distributed reinforcement learning algorithm that balances
between potentially conflicting short-term reward and sparse, delayed long-term reward, and …
between potentially conflicting short-term reward and sparse, delayed long-term reward, and …
Monopolistic models for resource allocation: A probabilistic reinforcement learning approach
Under the environment of cognitive radio networks, users are equipped with intelligent
capabilities so that they can sense the conditions of networks and act optimally to maximize …
capabilities so that they can sense the conditions of networks and act optimally to maximize …
Double auction game-based computing resource allocation in LEO satellite system
In the past few years, satellites have been widely influenced in our daily life, from Global
Positioning System (GPS) to Military investigation. Due to the limitation of computation …
Positioning System (GPS) to Military investigation. Due to the limitation of computation …