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, data throughput and network life time. In this paper, we investigate the use of cooperative communications for quality of service (QoS) provisioning in resource-constrained wireless sensor networks, and propose MRL-CC, a Multi-agent Reinforcement Learning based multi-hop mesh Cooperative Communication mechanism for wireless sensor networks. In order to disseminate data reliably in MRL-CC, a multi-hop mesh cooperative structure is first constructed. Then a cooperative mechanism with cooperative partner assignments, and coding and transmission schemes is implemented using a multi-agent reinforcement learning algorithm. We compare the network performance of MRL-CC with MMCC [1], a Multi-hop Mesh structure based Cooperative Communication scheme, and investigate the impacts of network traffic load, interference and sensor node's mobility on the network performance. Simulation results show that MRL-CC performs well in terms of a number of QoS metrics, and fits well in large-scale networks and highly dynamic environments.
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