performance. In a SWIPT-enabled system, a wireless node is powered up by a received Radio Frequency (RF) signal and, simultaneously, information processing is carried out using the same signal [2].SWIPT-based relaying was proposed as a promising technique to provide advantages in two fold. First, the network itself can benefit from the relays in throughput improvement, communication reliability enhancement, and coverage range extension. Second, the harvested energy can be used to charge the relay nodes, and therefore, the overall power consumption of the network may be considerably reduced [3], [4]. From this perspective, the theoretical and implementation aspects of SWIPT relay networks have been areas of active research interest (see [5]-[8] and the references therein).Although there has been a growing literature on SWIPT, particularly in the context of relay networks (see e.g., [5]-[8] and the references therein), all research studies were based upon the classical assumption of additive white Gaussian noise (AWGN). However, many communication channels are additionally impaired by impulsive man-made electromagnetic interference or atmospheric noise encountered in various metropolitan and indoor wireless applications, such as, automotive ignition, electronic devices, household appliances, medical equipment, and industrial equipment.[9]- [11]. A practical foreseen scenario of such a situation is future IoTs, for instance, where nodes can be implanted in environments that are susceptible to impulsive noise such as in industrial locations or in fields close to power lines. Although these nodes are envisioned to be powered by RF energy through SWIPT to achieve advantages, such as, dual use of RF signals for information and power transfer, extended network lifetime, etc., their performance in terms of error rate is not yet studied when impulsive noise is considered. Nonetheless, it is considered as a prevalent source of performance degradation. It has been demonstrated in [12] that communication systems designed under the AWGN assumption typically suffer from severe performance degradations when exposed to impulsive noise. This elevates the need for studying the performance of SWIPT systems, which are not only disturbed by multipath fading, but also by impulsive (non-Gaussian) noise, in order to provide pragmatic information for the system designer.Several statistical models have been proposed to approximate the behaviour of impulsive noise, such as Bernoulli-Gauss [13], the symmetric alpha stable distribution [14], and the Middleton's models [15], [16]. However, Middleton's models have been widely accepted to model the effects of impulse noise in communication systems due to its accuracy