Stacked Intelligent Metasurfaces for Integrated Sensing and Communications

TL;DR

This paper tackles ISAC in a downlink system by employing stacked intelligent metasurfaces (SIM) to perform wave-domain transmit precoding, enabling simultaneous communication to multiple users and radar sensing with a targeted beampattern. The authors formulate a SE-maximization problem over SIM phase shifts and BS power, introducing a penalty-based objective F = ∑_{k=1}^K log(1+γ_k) + β g_c to handle the beampattern constraint, and solve it via a tailored gradient ascent algorithm. The method derives gradients with respect to phase shifts and power allocations, normalizes updates, and uses Armijo step sizes to ensure convergence, demonstrating that additional SIM layers can significantly mitigate inter-user interference and shape beampatterns toward the sensing target. The results show convergence within ~10 iterations, a clear SE gain with more layers (e.g., seven layers giving ~33% improvement over a single layer), and that the beampattern constraint is satisfied, highlighting the practical potential of wave-domain ISAC with SIM for future wireless systems $R= ext{SE}=rac{1}{K} o$ and $P_t$ constraints, with $R_t=G W_1 P P^H W_1^H G^H$ and SINR terms embedded in γ_k.$

Abstract

Stacked intelligent metasurfaces (SIM) have recently emerged as a promising technology, which can realize transmit precoding in the wave domain. In this paper, we investigate a SIM-aided integrated sensing and communications system, in which SIM is capable of generating a desired beam pattern for simultaneously communicating with multiple downlink users and detecting a radar target. Specifically, we formulate an optimization problem of maximizing the spectrum efficiency, while satisfying the power constraint of the desired direction. This requires jointly designing the phase shifts of the SIM and the power allocation at the base station. By incorporating the sensing power constraint into the objective functions as a penalty term, we further simplify the optimization problem and solve it by customizing an efficient gradient ascent algorithm. Finally, extensive numerical results demonstrate the effectiveness of the proposed wave-domain precoder for automatically mitigating the inter-user interference and generating a desired beampattern for the sensing task, as multiple separate data streams transmit through the SIM.

Figures (5)

• Figure 1: A SIM-aided ISAC system.
• Figure 2: The convergence curves of the proposed gradient ascent algorithm ($M=100,\Gamma = 8 ~\text{dBi}$).
• Figure 3: The SE versus the number of metasurface layers ($M=100$).
• Figure 4: Beampattern comparison for $M=100, Q=7, K=4, \Gamma=8~\textrm{dBi}$. (a) ISAC; (b) communication-only system.
• Figure 5: Profiles of Fig. 4. (a) Horizontal beampattern; (b) Vertical beampattern.