Fuzzy Logic Based Energy Efficient Simultaneous Wireless Information and Power Transfer for Wireless Sensor Networks

Clustering is one of the most promising approaches to reducing energy usage in Wireless Sensor Networks, where power remains a bottleneck (WSNs). The vast majority of advances in energy efficiency result in exorbitant computing costs. Because of its superiority in simulating human decision making and its capacity to turn several inputs into a single output, the fuzzy-logic based clustering algorithm is preferred over others. This paper proposes a technique to energy-efficient clustering based on fuzzy logic (FLEE). Energy consumption is a significant barrier for geographically dispersed wireless sensor networks (WSNs). Because of the rapid improvement of energy harvesting technology, a novel approach known as simultaneous wireless information and power transmission (SWIPT) has emerged as a hot research topic due to its use in tackling the energy scarcity problem in WSNs. The bulk of existing SWIPT systems rely on time switching (TS) or power splitting due to their high complexity, lack of flexibility, and implementation issues (PS). In this paper, we provide a novel Fuzzy Logic-based Energy Efficient-SWIPT approach for adaptively dividing data packets into energy data packets and information data packets using fountain codes and real-time node decoding status information. The modulation switching thresholds and transmit power allocation at the SWIPT transmitter, as well as the power splitting ratios at the SWIPT receiver, are jointly changed to maximise the spectrum efficiency of wireless information transfer in wireless sensor networks. The numerical demonstration of the FLEE-SWIPT performance of many fixed modulation schemes under different fading situations. The FLEE-SWIPT transceiver with adaptive modulation has been proved to be useful. The results show an increase in Network Lifetime of 12.342 s, an increase in Network Throughput of 1579.41 kbps, a decrease in Energy consumption of 23.789 J, a decrease in Packet Loss Ratio of 38.61%, a decrease in Packet Delivery Ratio of 96.33%, a decrease in Encryption Time of 2.987 s, a decrease in Decryption Time of 3.567 s, and a decrease in Execution.