Use este identificador para citar ou linkar para este item: http://repositorio.ufc.br/handle/riufc/60029
Tipo: Artigo de Evento
Título: Resource Allocation for OFDMA Systems and Energy Harvesting Communications in Multi-User Offline Scenarios
Autor(es): Carvalho, Jair Alves de
Saraiva, Juno Vitorino
Lima, Francisco Rafael Marques
Maciel, Tarcísio Ferreira
Cavalcanti, Francisco Rodrigo Porto
Palavras-chave: Resource allocation;Rate maximization;OFDMA;MCS;Energy Harvesting, Heuristic
Data do documento: 2017
Instituição/Editor/Publicador: https://www.sbrt.org.br/sbrt2017
Citação: CARVALHO, Jair Alves de; SARAIVA, Juno Vitorino; LIMA, Francisco Rafael Marques; MACIEL, Tarcísio Ferreira; CAVALCANTI, Francisco Rodrigo Porto. Resource allocation for OFDMA systems and energy harvesting communications in multi-user offline scenarios. In: SIMPÓSIO BRASILEIRO DE TELECOMUNICAÇÕES E PROCESSAMENTO DE SINAIS – SbrT, XXXV., 3 a 6 set. 2017. São Pedro-SP. Anais[…], São Pedro-SP, 2017.p.323-327.
Resumo: We formulate the resource allocation problem of maximizing throughput in an OFDMA (Orthogonal Frequency Division Multiple Access) downlink network where the BS (Base Station) adapts the power allocation according to non-causal (offline) knowledge of the harvested energy and channel state. The offline case is important from a theoretical point of view since it provides a bound on the performance of the online problem (causal). Differently from previous work, that consider a continuous relation between SNR (Signal-to-Noise Ratio) and transmit data rate, we employ a discrete mapping that depends on the required MCSs (Modulation and Code Schemes). Also, we propose a heuristic algorithm that provides near-optimal results and achieves a good complexity/performance trade-off.
Abstract: We formulate the resource allocation problem of maximizing throughput in an OFDMA (Orthogonal Frequency Division Multiple Access) downlink network where the BS (Base Station) adapts the power allocation according to non-causal (offline) knowledge of the harvested energy and channel state. The offline case is important from a theoretical point of view since it provides a bound on the performance of the online problem (causal). Differently from previous work, that consider a continuous relation between SNR (Signal-to-Noise Ratio) and transmit data rate, we employ a discrete mapping that depends on the required MCSs (Modulation and Code Schemes). Also, we propose a heuristic algorithm that provides near-optimal results and achieves a good complexity/performance trade-off.
URI: http://www.repositorio.ufc.br/handle/riufc/60029
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