Design of a Reconfigurable Intelligent Surface-Assisted FM-DCSK-SWIPT Scheme with Non-linear Energy Harvesting Model
In this paper, we propose a reconfigurable intelligent surface (RIS)-assisted frequency-modulated (FM) differential chaos shift keying (DCSK) scheme with simultaneous wireless information and power transfer (SWIPT), called RIS-FM-DCSK-SWIPT scheme, for low-power, low-cost, and high-reliability wireless communication networks. In particular, the proposed scheme is developed under a non-linear energy-harvesting (EH) model which can accurately characterize the practical situation. The proposed RIS-FM-DCSK-SWIPT scheme has an appealing feature that it does not require channel state information, thus avoiding the complex channel estimation. We derive the theoretical expressions for the energy shortage probability and bit error rate (BER) of the proposed scheme over the multipath Rayleigh fading channel. We investigate the influence of key parameters on the performance of the proposed scheme in two different scenarios, i.e., RIS-assisted access point (RIS-AP) and dual-hop communication (RISDH). Finally, we carry out various Monte-Carlo experiments to verify the accuracy of the theoretical derivation, and illustrate the performance advantage of the proposed scheme over the existing DCSKSWIPT schemes. Copyright © 2022, The Authors. All rights reserved.
Bit error rate, Channel state information, Energy transfer, Low power electronics, Rayleigh fading, Differential chaos shift keying, Frequency modulated differential chaos shift keying, Information and power transfers, Linear energy, Multipath Rayleigh fading channel, Non linear, Non-linear energy-harvesting, Reconfigurable, Reconfigurable intelligent surface, Simultaneous wireless information and power transfer, Energy harvesting, Information Theory (cs.IT), Information Theory (math.IT), Signal Processing (eess.SP)
Y. Fang, Y. Tao, H. Ma, Y. Li and M. Guizani, "Design of a Reconfigurable Intelligent Surface-Assisted FM-DCSK-SWIPT Scheme with Non-linear Energy Harvesting Model", arXiv, May 2022, doi: 10.48550/arXiv.2205.06971
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