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Low-Complexity Beamforming Designs and Channel Estimation for Passive-Intelligent-Surface-Assisted MISO Energy Transfer

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The usage of passive intelligent surface (PIS) is emerging as a low-cost green alternative to massive antenna systems for realizing high-energy beamforming (EB) gains. Considering the limited computational capability and… Click to show full abstract

The usage of passive intelligent surface (PIS) is emerging as a low-cost green alternative to massive antenna systems for realizing high-energy beamforming (EB) gains. Considering the limited computational capability and constant-envelope precoding for PIS, we propose three novel low-complexity passive EB designs for optimizing the efficacy of PIS-assisted energy transfer (PET) from a multiantenna power beacon (PB) to a single-antenna energy harvesting (EH) user. The first EB design involves solving a univariate equation, and closed forms expressed are presented for the other two. Further, to maximize the practical utility of PET, we introduce a novel channel estimation (CE) protocol for obtaining least-squares estimators for the channels as required for EB designing. Using them, we also derive closed-form expressions for optimal PIS location and optimal time allocation between CE and PET within each coherence block to maximize the user’s net harvested energy. Numerical results verify the CE analysis and validate the novel analytical bound derived for received power during PET and proposed PIS designs’ quality against existing benchmarks. We show that the proposed jointly optimal design for PET can yield a significant improvement of about 15 dB, and a reduced active array size at PB can achieve the desired EB gain with sufficient passive elements at PIS. Finally, we also briefly discuss how the proposed CE and EB designs can be extended to the multiuser settings.

Keywords: passive intelligent; intelligent surface; low complexity; channel estimation; energy; energy transfer

Journal Title: IEEE Internet of Things Journal
Year Published: 2023

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