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Precoding Design for Energy Efficiency Maximization in MIMO Half-Duplex Wireless Sensor Networks with SWIPT
This paper explores the energy efficiency (EE) maximization problem in single-hop multiple-input multiple-output (MIMO) half-duplex wireless sensor networks (WSNs) with simultaneous wireless information and power transfer (SWIPT). Such an energy efficiency maximization problem is considered in two d...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891631/ https://www.ncbi.nlm.nih.gov/pubmed/31726684 http://dx.doi.org/10.3390/s19224923 |
Sumario: | This paper explores the energy efficiency (EE) maximization problem in single-hop multiple-input multiple-output (MIMO) half-duplex wireless sensor networks (WSNs) with simultaneous wireless information and power transfer (SWIPT). Such an energy efficiency maximization problem is considered in two different scenarios, in which the number of energy-harvesting (EH) sensor nodes are different. In the scenario where the single energy-harvesting sensor node is applied, the modeled network consists of two multiple-antenna transceivers, of which the energy-constrained energy-harvesting sensor node harvests energy from the signals transmitted from the source by a power splitting (PS) scheme. In the scenario of multiple EH sensor nodes, K energy-constrained sensor nodes are applied and the same quantity of antennas are equiped on each of them. The optimization problem is formulated to maximize the energy efficiency by jointly designing the transceivers’ precoding matrices and the PS factor of the energy-harvesting sensor node. The considered constraints are the required harvested energy, the transmission power limit and the requirement on the data rate. The joint design of the precoding matrices and the PS factor can be formulated as an optimization problem, which can be transformed into two sub-problems. An alternating algorithm based on Dinkelbach is proposed to solve the two sub-problems. The convergence of the proposed alternating algorithm, the solution optimality and the computational complexity are analyzed in the paper. Simulation results demonstrate the convergence and effectiveness of our proposed algorithm for realizing the maximum energy efficiency. |
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