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GLOBECOM
2010
IEEE

Learning Interference Strategies in Cognitive ARQ Networks

8 years 7 months ago
Learning Interference Strategies in Cognitive ARQ Networks
Cognitive radios, which enable the coexistence on the same bandwidth of licensed primary and unlicensed secondary users, have the potential for dramatically increasing the efficiency of wireless networks. In this paper, we propose an on line learning algorithm to optimize the transmission strategy of secondary users in interference mitigation scenarios, where the secondary users are allowed to superimpose their transmission onto those of the primary users. Due to practical limitations, the secondary users have access to only a fraction of the current state of the primary users' network. Therefore, the strategy of the secondary users is defined on a reduced state space. Numerical results show that the proposed practical learning algorithm operates close to the performance of the system under full knowledge.
Sina Firouzabadi, Marco Levorato, Daniel O'Neill,
Added 11 Feb 2011
Updated 11 Feb 2011
Type Journal
Year 2010
Where GLOBECOM
Authors Sina Firouzabadi, Marco Levorato, Daniel O'Neill, Andrea J. Goldsmith
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