Eskandari, Mahdi
(Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran)
,
Doost-Hoseini, Ali Mohamad
(Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran)
,
Jung, Jaehoon
(School of Electrical Engineering, Korea University, 145, Anam-ro, Seongbuk-gu, Seoul, 02841, Korea)
,
Lee, Inkyu
(School of Electrical Engineering, Korea University, 145, Anam-ro, Seongbuk-gu, Seoul, 02841, Korea)
In this paper, we investigate a new solution for the energy efficiency (EE) maximization and power allocation problem in point-to-point multiple-input multiple-output (MIMO) spatial multiplexing schemes. Different from conventional energy-efficient optimization approaches that require iterative nume...
In this paper, we investigate a new solution for the energy efficiency (EE) maximization and power allocation problem in point-to-point multiple-input multiple-output (MIMO) spatial multiplexing schemes. Different from conventional energy-efficient optimization approaches that require iterative numerical algorithms, we derive an optimal solution in a closed form, which provides an insight upon the relation between the optimum EE and system parameters such as circuit power and channel conditions. In addition, using the proposed closed form function, we present an upper bound on the optimum EE in terms of the full active transmit antennas parameters. Based on the derived upper bound, we also propose a new antenna selection algorithm which achieves almost the same performance as the optimum solution with much reduced complexity.
In this paper, we investigate a new solution for the energy efficiency (EE) maximization and power allocation problem in point-to-point multiple-input multiple-output (MIMO) spatial multiplexing schemes. Different from conventional energy-efficient optimization approaches that require iterative numerical algorithms, we derive an optimal solution in a closed form, which provides an insight upon the relation between the optimum EE and system parameters such as circuit power and channel conditions. In addition, using the proposed closed form function, we present an upper bound on the optimum EE in terms of the full active transmit antennas parameters. Based on the derived upper bound, we also propose a new antenna selection algorithm which achieves almost the same performance as the optimum solution with much reduced complexity.
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