Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
Cooperative Protocols Design for Wireless Ad-Hoc Networks with Multi-hop Routing
Mobile Networks and Applications
Cooperative wireless communications: a cross-layer approach
IEEE Wireless Communications
Cooperative Communications with Outage-Optimal Opportunistic Relaying
IEEE Transactions on Wireless Communications
Cooperative communications with relay-selection: when to cooperate and whom to cooperate with?
IEEE Transactions on Wireless Communications
IEEE Transactions on Wireless Communications
Distributed energy-efficient cooperative routing in wireless networks
IEEE Transactions on Wireless Communications
Cooperative diversity in wireless networks: Efficient protocols and outage behavior
IEEE Transactions on Information Theory
Cooperative communication in wireless networks
IEEE Communications Magazine
A simple Cooperative diversity method based on network path selection
IEEE Journal on Selected Areas in Communications
Journal of Network and Computer Applications
A game-theoretic approach for relay assignment over distributed wireless networks
Wireless Communications & Mobile Computing
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Cooperative communications have been demonstrated to be effective in combating the multiple fading effects in wireless networks, and improving the network performance in terms of adaptivity, reliability and network throughput. In this paper, we investigate the use of cooperative communications with adaptive relay selection for resource-constrained wireless sensor networks, and propose QoS-RSCC, a QoS-support multi-agent reinforcement learning based relay selection scheme for cooperative communications. In QoS-RSCC, optimal relays, in terms of outage probability and channel efficiency, are selected distributedly from multiple relaying candidates for the intermediate routers along the multi-hop route, without the needs of prior knowledge of the wireless network model and centralized control. We compare the network performance of QoS-RSCC with CRP [1], and investigate the impacts of network traffic load, channel bit error rate, and node's mobility on the network performance. Simulation results show that QoS-RSCC can achieve a near-optimal performance on both diversity gains and channel efficiency, and fits well in dynamic environments.