Dynamic Resource Management for Cognitive Radios Using Limited-Rate Feedback

Tailored for the emerging class of cognitive radio networks comprising primary and secondary wireless users, the present paper deals with dynamic allocation of sub-carriers, rate and power resources based on channel state information (CSI) for orthogonal frequency-division multiple access (OFDMA). U...

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Detalles Bibliográficos
Autores: García Marqués, Antonio, Wang, Xin, Giannakis, Georgios B.
Tipo de recurso: artículo
Fecha de publicación:2009
País:España
Institución:Universidad Rey Juan Carlos
Repositorio:BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlos
OAI Identifier:oai:burjcdigital.urjc.es:10115/2325
Acceso en línea:http://hdl.handle.net/10115/2325
Access Level:acceso abierto
Palabra clave:Telecomunicaciones
3325 Tecnología de las Telecomunicaciones
Descripción
Sumario:Tailored for the emerging class of cognitive radio networks comprising primary and secondary wireless users, the present paper deals with dynamic allocation of sub-carriers, rate and power resources based on channel state information (CSI) for orthogonal frequency-division multiple access (OFDMA). Users rely on adaptive modulation, coding and power modes that they select in accordance with the limited-rate feedback they receive from the access point. The access point uses CSI to maximize a generic concave utility of the average rates in the network while adhering to rate and power constraints imposed on the primary and secondary users to respect cognitive radio related hierarchies. When the channel distribution is available, optimum dual prices are found to optimally allocate resources across users dynamically per channel realization. In addition, a simple yet optimal on-line algorithm that does not require knowledge of the channel distribution and iteratively computes the dual prices per channel realization is developed using a stochastic dual approach. Analysis of the computational and feedback overhead along with simulations assessing the performance of the novel algorithms are also provided.