Numerical results demonstrate that the proposed SIM-assisted architecture significantly improves spectral efficiency while maintaining low hardware complexity, and highlight the impact of the number of metasurface layers and size of each layer on system performance.
Abstract
In this paper, we investigate an unmanned aerial vehicle (UAV) communication system assisted by stacked intelligent metasurfaces (SIMs), which enable programmable wave-domain signal processing through multiple cascaded metasurface layers. By shifting part of the beamforming functionality from the RF/digital domain to the electromagnetic domain, SIMs allow the realization of energy-efficient hybrid beamforming architectures suitable for aerial platforms. We formulate the joint design of digital precoding, SIM phase configuration, and UAV positioning for multi-user downlink sum-rate maximization. To solve the resulting non-convex problem, we develop an alternating optimization framework that guarantees monotonic improvement of the objective. Numerical results demonstrate that the proposed SIM-assisted architecture significantly improves spectral efficiency while maintaining low hardware complexity, and highlight the impact of the number of metasurface layers and size of each layer on system performance.
This paper studies energy-efficient downlink multi-user transmissions with unmanned aerial vehicle (UAV) communication systems equipped with stacked intelligent metasurfaces (SIM), enabling wave-domain analog beamforming through multiple cascaded metasurface layers, while low-dimensional digital precoding is carried out using a limited number of transmit radio-frequency chains. This architecture enables flexible electromagnetic wave manipulation with reduced hardware complexity, making it particularly suitable for energy-constrained aerial platforms. We formulate a hardware-aware energy-efficiency (EE) maximization problem aiming to jointly optimize the digital precoder, the phase shifts of all SIM layers, and the three-dimensional UAV position under transmit-power, SIM operation, and UAV deployment constraints. The resulting problem is highly non-convex due to the fractional objective, the cascaded SIM structure and the unit-modulus phase constraints of the constituent metasurface layers, as well as the non-linear UAV-dependent channel. To address these challenges, we develop a transform-based alternating optimization framework that combines Dinkelbach's method, dual and quadratic transforms, to enable closed-form digital beamforming, Riemannian manifold optimization for SIM phase shifts, and successive convex approximation (SCA) for UAV positioning. Convergence and complexity analyses are provided to characterize the proposed algorithm. The presented numerical results showcase that the proposed joint design significantly improves EE compared with fully digital and maximum ratio transmission benchmark schemes, while revealing important design trade-offs among transmit power, SIM size, and the number of its constituent stacked layers.
C. K. Sheemar, Giovanni Iacovelli, Sourabh Solanki et al.· 0 citations
This paper investigates a stacked intelligent metasurface (SIM)-assisted multiuser multiple-input single-output (MISO) downlink ultra-reliable and low-latency communication (URLLC) system under the finite blocklength (FBL) regime. By leveraging multiple programmable metasurface layers, SIM enables direct wave-domain beamforming with enhanced electromagnetic wave control, which makes it particularly attractive for reliable and delay-sensitive communications. We propose a joint optimization framework for transmit power allocation, user blocklength, and phase shifts across the stacked metasurface layers, with the objective of maximizing the sum rate under the transmit power constraint while accounting for SIM insertion loss. The resulting problem is non-convex due to the coupled optimization variables and the FBL rate expression. To tackle this problem, an alternating optimization (AO) algorithm is developed, where successive convex approximation is adopted for transmit power and blocklength optimization, while projected gradient ascent is employed for SIM phase shift design. Numerical results show that the proposed design achieves up to an 140% higher sum FBL rate than conventional transmission without SIM. In addition, the optimized blocklength allocation provides approximately an 8% gain over equal blocklength allocation, while the impact of practical insertion loss becomes more pronounced in deeper SIMs, with the degradation reaching about 17% for the six-layer configuration. Moreover, the proposed algorithm exhibits fast convergence, making it suitable for low-latency wireless applications and highlighting the potential of SIM-enabled wave-domain beamforming for next-generation mission-critical wireless networks.
Zahra Rostamikafaki, François Chan, C. D’amours· IEEE Open Journal of the Com...· 0 citations
We propose a novel doubly-dispersive (DD) multiple-input multiple-output (MIMO) channel model incorporating flexible intelligent metasurfaces (FIMs), suitable for integrated sensing and communications (ISAC) in high-mobility scenarios. We show how the proposed FIM-parameterized DD (FPDD) channel model extends to multicarrier waveforms known to perform well in DD environments, namely, orthogonal frequency division multiplexing (OFDM), orthogonal time frequency space (OTFS), and affine frequency division multiplexing (AFDM). Leveraging this model, we formulate an achievable rate maxi-mization problem with a sensing constraint for all waveforms and solve it via gradient ascent with closed-form gradients. Numerical results indicate that FIM technology significantly impacts the achievable rate, with careful parametrization essential for strong ISAC performance across all waveforms.
Iván Alexander Morales Sandoval, Thushar Venkataramanaiah, K. R. R. Ranasinghe et al.· 0 citations
This paper investigates an energy-efficient active stacked intelligent metasurfaces (ASIM)-assisted downlink transmission framework, where a multi-antenna base station (BS) serves multiple users through a multi-layer metasurface architecture. Unlike conventional passive intelligent surfaces, the considered ASIM employs active amplification and multiple transmissive layers to enhance electromagnetic wave manipulation. We aim to maximize the system energy efficiency (EE) by jointly optimizing the BS beamforming and ASIM configurations under user quality-of-service and amplification constraints. The resulting problem is highly coupled and non-convex due to the cascaded near-field channel and multi-layer metasurface structure. To address this challenge, we first transform the original problem through Dinkelbach, Lagrangian dual, and quadratic transformations. An alternative optimization framework is then developed, where the BS beamforming subproblem is solved via successive convex approximation (SCA), while the ASIM configuration is optimized using Bayesian optimization based on a Gaussian process surrogate model. Numerical results demonstrate that the proposed scheme significantly improves the achievable EE compared to conventional passive SIM and heuristic benchmark methods. Furthermore, the impacts of amplification capability, number of metasurface layers, and inter-layer spacing on system performance are investigated, providing useful design insights for future active metasurface-assisted wireless networks.
Stacked intelligent metasurfaces (SIM) provide an efficient architecture for integrated sensing and communication (ISAC) with few radio-frequency (RF) chains. However, diagonal SIM provide only element-wise phase control, so balancing multiuser communication and sensing performance may require additional layers. In this letter, we propose a beyond-diagonal SIM (BD-SIM) architecture for ISAC, enabling controllable intra-layer coupling through reconfigurable impedance networks, thereby enhancing wave-domain processing flexibility. We develop a unified alternating optimization framework applicable to fully-connected, group-connected, and diagonal SIM architectures. Within this framework, we derive a closed-form power allocation rule and propose an effective variable separation algorithm for multi-layer phase-shift design. Simulation results show that the proposed BD-SIM achieve a better communication-sensing trade-off and require fewer layers to attain performance comparable to conventional SIM.
Y. Jiao, Qian Zhang, Xuejun Cheng et al.· IEEE Wireless Communications...· 0 citations
In this paper, we investigate the sum rate maximization problem for integrated sensing and communication (ISAC) systems enabled by a flexible intelligent metasurface (FIM) deployed at the base station. By enabling element movement through surface morphing, the FIM introduces additional spatial degrees of freedom that can reshape the wireless propagation environment. To exploit this capability, we jointly optimize the transmit digital beamforming at the base station and the FIM surface configuration, characterized by the positions of its radiating elements, subject to transmit power constraints and minimum sensing beam gain requirements. Since the resulting problem is highly non-convex due to the strong coupling between the beamforming vectors and the element positions, a deep reinforcement learning (DRL)-based algorithm is proposed to efficiently obtain high-quality solutions. Numerical results demonstrate that the proposed framework significantly improves the achievable sum rate while satisfying the sensing performance constraints.
Ho-Ang T. Hung, H. H. Nguyen, Huy T. Nguyen et al.· IEEE International Conferenc...· 0 citations
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