SWIPT Optimization Design for Multi-RIS-Aided Cell-Free IoT Networks With Fluid Antenna

Simultaneous wireless information and power transfer (SWIPT) has been regarded as a highly promising technology for delivering reliable energy supply for low-powered Internet-of-Thing devices (IoTDs). In this paper, we originally investigate the performance of SWIPT systems in multi-Reconfigurable Intelligent Surface (RIS) aided cell-free IoT networks with fluid antenna (FA).Our objective is to simultaneously maximize the sum transmission rate and harvested energy by optimizing the selection of FA ports, transmit beamforming vectors at access points (APs), and reflect beamforming at RISs, which is a notorious trade-off and is impossible to simultaneously maximize at the same IoTD under the traditional Power splitting (PS) or Time switching (TS) based SWIPT techniques. By converting the harvested energy into throughput, we formulate a novel equivalent-sum-rate (ESR) maximization problem. To handle this sum-of-logarithmic function and nested multiple-ratio fractional nonconvex optimization problem, we develop a Lagrangian dual transform (LDT) and quadratic transform (QT)-based alternating optimization (AO) framework to tackle it. Simulation results demonstrate that the proposed method outperforms benchmarks, highlighting the enhanced system performance in both information and energy reception facilitated by RISs and FA. Moreover, our research also indicates that the deployment of FA at IoTDs can achieve better performance than the traditional fixed-position antennas in such a network, as long as it can provide an adequate number of ports and FA size.