Learning-based framework for policy-aware cognitive radio emergency networking
Eun Kyung Lee, Hariharasudhan Viswanathan, Dario Pompili · 2013
Uncertainties in the wireless communication medium do not allow for guarantees in network performance for cognitive radio applications envisaged for mobile ad hoc emergency networking. The novel concept of mission policies, which specify the Quality of Service (QoS) requirements of the incumbent network as well as the cognitive radio networks, is introduced. The use of mission policies, which vary over time and space, enables graceful degradation in the QoS of incumbent network (only when necessary) based on mission-policy specifications. A Multi-Agent Reinforcement Learning (MARL)-based cross-layer communication framework, RescueNet, is proposed for self-adaptation of nodes in cognitive radio networks. Also, the novel idea of knowledge sharing among the agents (nodes) is introduced to significantly improve the performance of the proposed solution.