Mostra el registre d'ítem simple
Cooperation reliability based on reinforcement learning for cognitive radio networks
dc.contributor.author | Vucevic, Nemanja |
dc.contributor.author | Akyildiz, Ian F. |
dc.contributor.author | Pérez Romero, Jordi |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions |
dc.date.accessioned | 2011-05-05T07:45:46Z |
dc.date.available | 2011-05-05T07:45:46Z |
dc.date.created | 2010 |
dc.date.issued | 2010 |
dc.identifier.citation | Vucevic, N.; Akyildiz, I.; Pérez-Romero, J. Cooperation reliability based on reinforcement learning for cognitive radio networks. A: IEEE Workshop on Networking Technologies for Software Defined Radio (SDR) Networks. "5th IEEE Workshop on Networking Technologies for Software Defined Radio (SDR) Networks". Boston: 2010, p. 1-6. |
dc.identifier.isbn | 978-1-4244-7212-3 |
dc.identifier.uri | http://hdl.handle.net/2117/12468 |
dc.description.abstract | The primary objective of cooperation in Cognitive Radio (CR) networks is to increase the efficiency and improve the network performance. However, CR users may act destructively and decrease both their own and others’ performances. This can be due to Byzantine adversaries or unintentional erroneous conduct in cooperation. This work presents an autonomous cooperation solution for each CR user, i.e., each CR user decides with whom to cooperate. The objective of the proposed solution is to increase the spectrum access in cooperative CR networks. To realize this, a Reinforcement Learning (RL) algorithm is utilized to determine the suitability of the available cooperators and select the appropriate set of cooperators. In addition, the proposed solution determines the most appropriate number of cooperators to achieve the highest efficiency for spectrum access. Accordingly, the control communication overhead is reduced. The simulation results demonstrate the learning capabilities of the proposed to achieve reliable behavior under highly unreliable conditions. |
dc.format.extent | 6 p. |
dc.language.iso | eng |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors |
dc.subject.lcsh | Cognitive radio networks |
dc.title | Cooperation reliability based on reinforcement learning for cognitive radio networks |
dc.type | Conference report |
dc.subject.lemac | Xarxes de ràdio cognitiva |
dc.contributor.group | Universitat Politècnica de Catalunya. GRCM - Grup de Recerca en Comunicacions Mòbils |
dc.identifier.doi | 10.1109/SDR.2010.5507921 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://ieeexplore.ieee.org/ |
dc.rights.access | Open Access |
local.identifier.drac | 2641736 |
dc.description.version | Postprint (published version) |
local.citation.author | Vucevic, N.; Akyildiz, I.; Pérez-Romero, J. |
local.citation.contributor | IEEE Workshop on Networking Technologies for Software Defined Radio (SDR) Networks |
local.citation.pubplace | Boston |
local.citation.publicationName | 5th IEEE Workshop on Networking Technologies for Software Defined Radio (SDR) Networks |
local.citation.startingPage | 1 |
local.citation.endingPage | 6 |