Resource Allocation for Energy Efficiency and QoS Provisioning

Abstract

In this paper, we formulate and solve two Energy Efficiency (EE) problems, namely the Power Minimization Problem (PMP) and the Maximization of Energy Efficiency Problem (MEEP), for a wireless system using power and frequency resource allocation considering Quality of Service (QoS) requirements and multiple services. Despite those problems are nonlinear, they can be converted into Integer Linear Problems (ILPs). Therefore, the optimal solution for both PMP and MEEP can be obtained by well-known methods. Additionally, we propose two fast suboptimal algorithms as to avoid the high computational complexity of obtaining optimal solution for MEEP. Our results show that the MEEP has a better trade-off between transmitted data rate and power saving than the PMP solution. Moreover, the suboptimal algorithms present good performance compared to the optimal solution for moderated loads but with a much lower computational complexity, thus achieving a remarkable trade-off between performance and computational complexity.

Reinforcement Learning Scheduling for URLLC Service Protection in Industry 4.0 Scenario

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Alocação de Potência em Redes Sem Fio Baseadas em Multiplexção por Divisão de Frequências Ortogonais Utilizando Aprendizagem por Reforço

“…Levando em conta os desafios relatados para a alocac ¸ão de recurso em redes sem fio moderna, tais como as redes da 5ª gerac ¸ão (5G) e 6ª gerac ¸ão (6G) de comunicac ¸ão móvel, na última década, muitos projetos de pesquisas foram desenvolvidos alcanc ¸ando resultados promissores. Em [Mauricio et al 2019], os autores estudam o problema de alocac ¸ão de recurso de rádio envolvendo a otimizac ¸ão de eficiência energética com requisitos específicos de Qualidade de Servic ¸o (QoS -Quality of Service) em cenários multisservic ¸os. Neste trabalho, vai-se além ao utilizar a aprendizagem por reforc ¸o para realizar alocac ¸ão de potência.…”

The Heuristic for Hardware Dimensioning Considering Tidal Effect

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