On the optimal resource allocation for a wireless energy harvesting node considering the circuitry power consumption

In this paper, an energy harvesting transmitter operating in a point-to-point link through a discrete-time fading channel is considered, where symbols can be transmitted through several parallel independent streams. Taking into account the different sources of energy consumption at the transmitter,...

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Detalles Bibliográficos
Autores: Gregori, M, Payaro, M
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2014
País:España
Institución:Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
Repositorio:r-CTTC. Repositorio Institucional Producción Científica del Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
OAI Identifier:oai:cttc.fundanetsuite.com:p1281
Acceso en línea:https://cttc.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=1281
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84910112561&doi=10.1109%2fTWC.2014.2337314&partnerID=40&md5=1e596a32e7b2a7be03755e5983991ab3
Access Level:acceso abierto
Palabra clave:Energy utilization
Fading channels
Resource allocation
Social networking (online)
Transmitters
Asymptotically optimal
Graphical interpretations
Mutual informations
Off-line approaches
On-line algorithms
Optimal resource allocation
Point-to-point link
Power allocations
Energy harvesting
Descripción
Sumario:In this paper, an energy harvesting transmitter operating in a point-to-point link through a discrete-time fading channel is considered, where symbols can be transmitted through several parallel independent streams. Taking into account the different sources of energy consumption at the transmitter, the resource allocation (in terms of power allocation and selection of the active streams and channel accesses) that asymptotically maximizes the mutual information is derived by assuming that the transmitter has non-causal knowledge of the harvested energy and channel state (offline approach). The Boxed Water-Flowing graphical interpretation is presented, which intuitively depicts the asymptotically optimal offline resource allocation. Moreover, an online algorithm is proposed for the case in which the transmitter only has causal (past and present) knowledge of the harvested energy and channel state. Finally, the performance of the proposed offline and online solutions is numerically evaluated and the associated computational complexities are assessed and compared. © 2014 IEEE.