By utilizing the combination of two powerful tools i.e., stochastic geometry (SG) and copula theory (CT), in this paper, we assess the performance of fluid-based reconfigurable antenna (FA)-enabled user equipments (UEs) in the context of simultaneous wireless information and power transfer (SWIPT) networks. Particularly, by using CT tools, we initially derive a closed-form expression for the cumulative distribution function of the observed signal-to-interference ratio (SIR) under correlated Nakagami-μ fading channels by exploiting a well-investigated Archimedean copula, namely the Frank copula. According to the CT-based approach, a SG-based framework is presented to assess the SWIPT performance of FA-enabled UEs, that are equipped with a power splitting scheme to simultaneously extract information and harvest energy from the port with the strongest SIR. Our results reveal that FA-enabled SWIPT systems experience an improved information decoding performance of around 30% with a slight reduction in energy harvest performance of around 6% compared to conventional fixed-positioned antennas systems.

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