2023
DOI: 10.3390/electronics12020360
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Research on Multi-Agent D2D Communication Resource Allocation Algorithm Based on A2C

Abstract: Device to device (D2D) communication technology is the main component of future communication, which greatly improves the utilization of spectrum resources. However, in the D2D subscriber multiplex communication network, the interference between communication links is serious and the system performance is degraded. Traditional resource allocation schemes need a lot of channel information when dealing with interference problems in the system, and have the problems of weak dynamic resource allocation capability … Show more

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Cited by 15 publications
(2 citation statements)
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“…Recently, researchers have applied reinforcement learning (RL) algorithms to Active SLAM tasks, such as Deep Q-Networks (DQN) [24], Advantage Actor-Critic (A2C) [25], and Dueling Double DQN (D3QN) [26]. Chen et al trained DQN and A2C agents by incorporating the underlying SLAM pose graph through Graph Neural Networks (GNNs) [27].…”
Section: Of 19mentioning
confidence: 99%
“…Recently, researchers have applied reinforcement learning (RL) algorithms to Active SLAM tasks, such as Deep Q-Networks (DQN) [24], Advantage Actor-Critic (A2C) [25], and Dueling Double DQN (D3QN) [26]. Chen et al trained DQN and A2C agents by incorporating the underlying SLAM pose graph through Graph Neural Networks (GNNs) [27].…”
Section: Of 19mentioning
confidence: 99%
“…Non-orthogonal multiple-access (NOMA) device-to-device communication is a promising technology for providing high data rates and secure transmission in short-range communication and improving the performance of fifth-generation (5G) wireless networks [7,8]. D2D communication enables direct connectivity among devices without support from the core network, offloading the cellular network and increasing the network's capacity [9]. Moreover, low latency, energy efficiency, and high data rate requirements can be achieved by combining D2D with cellular networks [10].…”
Section: Introductionmentioning
confidence: 99%