IEEE Systems Journal · 2020 · 16 citations · 38 references
EngineeringComputer EngineeringElectrical EngineeringAntennasDigital CommunicationWireless CommunicationsEnergy EfficiencyInterference ManagementWireless NetworksDuplex CommunicationEfficiencyEfficiency EvaluationEnergy Efficiency EvaluationEnergy HarvestingHalf-duplex CommunicationOrthogonal Frequency-division MultiplexingSpectral Efficiency
Energy-efficient wireless system design has gained considerable attraction owing to the widespread proliferation of wireless devices. The next-generation wireless systems should also be spectrally efficient to sustain the tremendous demand for wireless services. Full-duplex (FD) systems have the potential to double the spectral efficiency (SE) of current half-duplex communication systems. The major challenge in FD systems is the suppression of strong self-interference (SI) imposed by the transmit signal on its receiving antennas. However, SI can also be utilized for recycling of energy by exploiting the radio frequency energy harvesting (RFEH) techniques, which is commonly referred to as self-energy recycling (S-ER). S-ER improves the overall energy efficiency (EE) of the system via recycling a portion of transmitted power. In this article, we evaluate the EE for a downlink FD nonlinear multiuser multi-input-multi-output (MU-MIMO) orthogonal frequency division multiplexing (OFDM) system in the presence of S-ER. The proposed analytical formulation consists of closed-form derivation for EE and SE of the aforementioned system. Furthermore, we have also obtained the outage performance and based on this performance proposed a methodology to allocate the antennas for S-ER while satisfying the quality of service. It has been observed that reserving few antennas for S-ER improves the EE albeit with a slight degradation in SE due to reduced array gain. Consequently, with S-ER, the tradeoff between the SE and EE has been studied for a nonlinear MU-MIMO-OFDM system. Analytical derivation for EE, SE, and outage are followed by simulations for corroborating the proposed analysis.
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David Gesbert, Marios Kountouris, Robert W. Heath et al. · IEEE Signal Processing Magazine · 2007 · 1.1K citations