Enhancing Cell-Free SWIPT IoT Networks By Active RIS

In the context of Internet of Things (IoT) networks, this work investigates an active reconfigurable intelligent surface (RIS)-aided cell-free massive multiple-input multiple-output (MIMO) simultaneous wireless information and power transfer (SWIPT) system and establishes an integrated analytical frame-work that rigorously characterizes both the inherent double-fading effect of RIS-assisted propagation and the power-gain coupling introduced by the active RIS. A weighted sum-rate (WSR) maximization problem is then formulated under the constraints of access point (AP) power budgets, the RIS power consumption limitations, and the receiver energy harvesting requirements. To manage the resulting highly non-convex structure, the original problem is equivalently reformulated as a weighted minimum mean squared error (WMMSE) minimization problem, which enables the development of an efficient alternating optimization algorithm. At each iteration, the MMSE decoding vectors are firstly updated in closed form, while the energy signal covariance matrices, the AP information beamformers, and the active RIS reflection coefficients are subsequently optimized via semi-definite programming, successive convex approximation, and augmented Lagrangian method, respectively. Extensive simulation results demonstrate that the adoption of an active RIS effectively mitigates the double-fading effect and achieves performance comparable to that of passive RIS with significantly fewer reflecting elements, while the proposed joint optimization strategy yields substantial WSR gains and further enlarges the performance gap between the optimized active and passive RIS schemes.