@inproceedings{e2c7e3c6a26d42f0b6d02316116422c9,
title = "Learning-based framework for policy-aware cognitive radio emergency networking",
abstract = "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.",
keywords = "Cognitive Radio, Licensed Spectrum, Mission Policies, Multi-agent Systems, Reinforcement Learning",
author = "Lee, {Eun Kyung} and Hariharasudhan Viswanathan and Dario Pompili",
year = "2013",
doi = "10.1109/GLOCOM.2013.6831199",
language = "English (US)",
isbn = "9781479913534",
series = "GLOBECOM - IEEE Global Telecommunications Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "968--973",
booktitle = "2013 IEEE Global Communications Conference, GLOBECOM 2013",
address = "United States",
note = "2013 IEEE Global Communications Conference, GLOBECOM 2013 ; Conference date: 09-12-2013 Through 13-12-2013",
}