A Framework for Stacked Intelligent Metasurfaces With Geometry Design for Near-Field Communications

Abstract

Stacked intelligent metasurfaces (SIMs) enable near-field wavefront shaping via multiple programmable layers. However, widely used wave-domain models often neglect power scaling, mutual coupling, and geometric flexibility, while multiport-network formulations are physically consistent but computationally heavy and typically assume fixed layer spacing. This paper develops a hybrid near-field SIM framework that remains in the wave domain yet is anchored to a physically meaningful power scale and supports geometry-aware optimization. From a Rayleigh-Sommerfeld propagation model, we construct coupling-aware hop matrices and enforce hop-wise power scaling via a Friis-based anchoring rule. Meta-atom responses obey amplitude-phase coupling with a transmission-reflection trade-off, and the inter-layer distances are treated as continuous design variables under total-thickness and minimum-spacing constraints. The resulting transmissive-reflective cascade retains only the dominant single-bounce inter-layer reflections and admits efficient forward evaluation with stable gradients. An alternating optimization (AO) algorithm based geometry-aware architecture was proposed to optimize the metasurface coefficients and the spacings. Simulation results show that, under realistic near-field layer coupling and hardware losses, the achievable sum-rate is non-monotonic in both the number of layers and the total SIM thickness. Geometry-aware spacing significantly improves the conditioning of the effective downlink channel and consistently outperforms uniform spacing, providing a realistic and optimization-ready basis for SIM-assisted near-field communication system design.