arXiv subjects

Jiancheng An

Publications and source records attributed to Jiancheng An.

At least 37 records · Page 2Linked to original sources

arXiv2026

Cramér-Rao Bound Minimization for Flexible Intelligent Metasurface-Enabled ISAC Systems

Integrated sensing and communication (ISAC) have been widely recognized as a key enabler for future wireless networks, where the Cramér-Rao bound (CRB) plays a central role in quantifying sensing accuracy.In this paper, we present the first study on CRB minimization in flexible intelligent metasurface (FIM)-enabled ISAC systems.Specifically, we first derive an average CRB expression that explicitly depends on FIM surface shape and demonstrate that array reconfigurability can substantially reduce the CRB, thereby significantly enhancing sensing performance.Moreover, to tackle the challenging CRB minimization problem, we adopt average Fisher information maximization as a surrogate objective and use the Gauss-Hermite quadrature method to obtain an explicit approximation of the objective function.The resulting problem is then decoupled into three subproblem, i.e., beamforming optimization and transmit/receive FIM surface shape optimization.For beamforming optimization, we employ the Schur complement and penalty-based semi-definite relaxation (SDR) technique to solve it.Furthermore, we propose a fixed-point equation method and a projected gradient algorithm to optimize the surface shapes of the receive and transmit FIMs, respectively.Simulation results demonstrate that, compared to rigid arrays, surface shaping of both transmit and receive FIMs can significantly reduce the average sensing CRB while maintaining communication quality, and remains effective even in multi-target scenarios.

cs.IT↗

arXiv2026

Stacked Intelligent Metasurface-Enhanced MIMO OFDM Wideband Communication Systems

Multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems rely on digital or hybrid digital and analog designs for beamforming against frequency-selective fading, which suffer from high hardware complexity and energy consumption. To address this, this work introduces a fully-analog stacked intelligent metasurfaces (SIM) architecture that directly performs wave-domain beamforming, enabling diagonalization of the end-to-end channel matrix and inherently eliminating inter-antenna interference (IAI) for MIMO OFDM transmission. By leveraging cascaded programmable metasurface layers, the proposed system establishes multiple parallel subchannels, significantly improving multi-carrier transmission efficiency while reducing hardware complexity. To optimize the SIM phase shift matrices, a block coordinate descent and penalty convex-concave procedure (BCD-PCCP) algorithm is developed to iteratively minimize the channel fitting error across subcarriers. Simulation results validate the proposed approach, determining the maximum effective bandwidth and demonstrating substantial performance improvements. Moreover, for a MIMO OFDM system operating at 28 GHz with 16 subcarriers, the proposed SIM configuration method achieves over 300% enhancement in channel capacity compared to conventional SIM configuration that only accounts for the center frequency.

eess.SP↗

arXiv2025

Flexible Intelligent Layered Metasurfaces for Downlink Multi-user MISO Communications

Stacked intelligent metasurfaces (SIMs) have recently gained attention as a paradigm for wave-domain signal processing with reduced reliance on costly radio-frequency (RF) chains. However, conventional SIMs rely on uniform inter-layer spacing and require deep stacking to ensure processing capability, resulting in severe power attenuation in practice. To address this issue, we propose a flexible intelligent layered metasurface (FILM) architecture consisting of two shape-controllable flexible metasurface layers. By replacing rigid metasurfaces with flexible ones in both layers, the transmission coefficient matrix can be dynamically adjusted, significantly decreasing the number of required layers while maintaining signal processing performance. Firstly, we develop a two-layer FILM-assisted multi-user multiple-input single-output (MU-MISO) system, wherein we formulate a channel fitting problem aimed at reducing the difference between the FILM-induced and target channels. Then, we solve this non-convex problem by employing an alternating optimization (AO) method, featuring closed-form phase shift updates and a gradient descent-based shape optimization. Furthermore, we analyze the upper bound on sum-rate and the complexity of computation to provide insights into design trade-offs. Finally, simulation results demonstrated that the proposed transmissive FILM architecture achieves over 200\% improvement in sum-rate and more than 7 dB bit-error rate (BER) gain compared to the conventional seven-layer SIMs.

cs.IT↗

arXiv2025

Flexible Intelligent Metasurface for Reconfiguring Radio Environments

Flexible intelligent metasurface (FIM) technology holds immense potential for increasing the spectral efficiency and energy efficiency of wireless networks. In contrast to traditional rigid reconfigurable intelligent surfaces (RIS), an FIM consists of an array of elements, each capable of independently tuning electromagnetic signals, while flexibly adjusting its position along the direction perpendicular to the surface. In contrast to traditional rigid metasurfaces, FIM is capable of morphing its surface shape to attain better channel conditions. In this paper, we investigate the single-input single-output (SISO) and multiple-input single-output (MISO) communication systems aided by a transmissive FIM. In the SISO scenario, we jointly optimize the FIM phase shift matrix and surface shape to maximize the end-to-end channel gain. First, we derive the optimal phase-shift matrix for each tentative FIM surface shape to decompose the high-dimensional non-convex optimization problem into multiple one-dimensional subproblems. Then, we utilize the particle swarm optimization (PSO) algorithm and the multi-interval gradient descent (MIGD) method for updating the FIM's surface shape to maximize the channel gain. In the MISO scenario, we jointly optimize the transmit beamforming, the FIM surface shape, and the phase shift matrix to maximize the channel gain. To tackle this complex problem with multiple highly coupled variables, an efficient alternating optimization algorithm is proposed. Simulation results demonstrate that FIM significantly improves channel gain compared to traditional RIS and exhibits good adaptability to multipath channels.

eess.SP↗

arXiv2025

Introducing Meta-Fiber into Stacked Intelligent Metasurfaces for MIMO Communications: A Low-Complexity Design with only Two Layers

Stacked intelligent metasurfaces (SIMs), which integrate multiple programmable metasurface layers, have recently emerged as a promising technology for advanced wave-domain signal processing. SIMs benefit from flexible spatial degree-of-freedom (DoF) while reducing the requirement for costly radio-frequency (RF) chains. However, current state-of-the-art SIM designs face challenges such as complex phase shift optimization and energy attenuation from multiple layers. To address these aspects, we propose incorporating meta-fibers into SIMs, with the aim of reducing the number of layers and enhancing the energy efficiency. First, we introduce a meta-fiber-connected 2-layer SIM that exhibits the same flexible signal processing capabilities as conventional multi-layer structures, and explains the operating principle. Subsequently, we formulate and solve the optimization problem of minimizing the mean square error (MSE) between the SIM channel and the desired channel matrices. Specifically, by designing the phase shifts of the meta-atoms associated with the transmitting-SIM and receiving-SIM, a non-interference system with parallel subchannels is established. In order to reduce the computational complexity, a closed-form expression for each phase shift at each iteration of an alternating optimization (AO) algorithm is proposed. We show that the proposed algorithm is applicable to conventional multi-layer SIMs. The channel capacity bound and computational complexity are analyzed to provide design insights. Finally, numerical results are illustrated, demonstrating that the proposed two-layer SIM with meta-fiber achieves over a 25% improvement in channel capacity while reducing the total number of meta-atoms by 59% as compared with a conventional seven-layer SIM.

cs.IT↗

arXiv2025

Fundamental Trade-off in Wideband Stacked Intelligent Metasurface Assisted OFDMA Systems

Conventional digital beamforming for wideband multiuser orthogonal frequency-division multiplexing (OFDM) demands numerous power-hungry components, increasing hardware costs and complexity. By contrast, the stacked intelligent metasurfaces (SIM) can perform wave-based precoding at near-light speed, drastically reducing baseband overhead. However, realizing SIM-enhanced fully-analog beamforming for wideband multiuser transmissions remains challenging, as the SIM configuration has to handle interference across all subcarriers. To address this, this paper proposes a flexible subcarrier allocation strategy to fully reap the SIM-assisted fully-analog beamforming capability in an orthogonal frequency-division multiple access (OFDMA) system, where each subcarrier selectively serves one or more users to balance interference mitigation and resource utilization of SIM. We propose an iterative algorithm to jointly optimize the subcarrier assignment matrix and SIM transmission coefficients, approximating an interference-free channel for those selected subcarriers. Results show that the proposed system has low fitting errors yet allows each user to exploit more subcarriers. Further comparisons highlight a fundamental trade-off: our system achieves near-zero interference and robust data reliability without incurring the hardware burdens of digital precoding.

eess.SP↗

arXiv2025

Performance Analysis of RIS-Aided High-Mobility Wireless Systems

Reconfigurable intelligent surface (RIS) technology holds immense potential for increasing the performance of wireless networks. Therefore, RIS is also regarded as one of the solutions to address communication challenges in high-mobility scenarios, such as Doppler shift and fast fading. This paper investigates a high-speed train (HST) multiple-input single-output (MISO) communication system aided by a RIS. We propose a block coordinate descent (BCD) algorithm to jointly optimize the RIS phase shifts and the transmit beamforming vectors to maximize the channel gain. Numerical results are provided to demonstrate that the proposed algorithm significantly enhances the system performance, achieving an average channel gain improvement of 15 dB compared to traditional schemes. Additionally, the introduction of RIS eliminates outage probability and improves key performance metrics such as achievable rate, channel capacity, and bit error rate (BER). These findings highlight the critical role of RIS in enhancing HST communication systems.

eess.SP↗

arXiv2025

Joint Association and Phase Shifts Design for UAV-mounted Stacked Intelligent Metasurfaces-assisted Communications

Stacked intelligent metasurfaces (SIMs) have emerged as a promising technology for realizing wave-domain signal processing, while the fixed SIMs will limit the communication performance of the system compared to the mobile SIMs. In this work, we consider a UAV-mounted SIMs (UAV-SIMs) assisted communication system, where UAVs as base stations (BSs) can cache the data processed by SIMs, and also as mobile vehicles flexibly deploy SIMs to enhance the communication performance. To this end, we formulate a UAV-SIM-based joint optimization problem (USBJOP) to comprehensively consider the association between UAV-SIMs and users, the locations of UAV-SIMs, and the phase shifts of UAV-SIMs, aiming to maximize the network capacity. Due to the non-convexity and NP-hardness of USBJOP, we decompose it into three sub-optimization problems, which are the association between UAV-SIMs and users optimization problem (AUUOP), the UAV location optimization problem (ULOP), and the UAV-SIM phase shifts optimization problem (USPSOP). Then, these three sub-optimization problems are solved by an alternating optimization (AO) strategy. Specifically, AUUOP and ULOP are transformed to a convex form and then solved by the CVX tool, while we employ a layer-by-layer iterative optimization method for USPSOP. Simulation results verify the effectiveness of the proposed strategy under different simulation setups.

cs.NI↗

arXiv2025

Flexible Intelligent Metasurfaces in High-Mobility MIMO Integrated Sensing and Communications

We propose a novel doubly-dispersive (DD) multiple-input multiple-output (MIMO) channel model incorporating flexible intelligent metasurfaces (FIMs), which is suitable for integrated sensing and communications (ISAC) in high-mobility scenarios. We then discuss how the proposed FIM-parameterized DD (FPDD) channel model can be applied in a logical manner to ISAC waveforms that are 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 the proposed model, we formulate an achievable rate maximization problem with a strong sensing constraint for all the aforementioned waveforms, which we then solve via a gradient ascent algorithm with closed-form gradients presented as a bonus. Our numerical results indicate that the achievable rate is significantly impacted by the emerging FIM technology with careful parametrization essential in obtaining strong ISAC performance across all waveforms suitable to mitigating the effects of DD channels.

eess.SP↗

arXiv2025

Stacked Intelligent Metasurface Assisted Multiuser Communications: From a Rate Fairness Perspective

Stacked intelligent metasurface (SIM) extends the concept of single-layer reconfigurable holographic surfaces (RHS) by incorporating a multi-layered structure, thereby providing enhanced control over electromagnetic wave propagation and improved signal processing capabilities. This study investigates the potential of SIM in enhancing the rate fairness in multiuser downlink systems by addressing two key optimization problems: maximizing the minimum rate (MR) and maximizing the geometric mean of rates (GMR). {The former strives to enhance the minimum user rate, thereby ensuring fairness among users, while the latter relaxes fairness requirements to strike a better trade-off between user fairness and system sum-rate (SR).} For the MR maximization, we adopt a consensus alternating direction method of multipliers (ADMM)-based approach, which decomposes the approximated problem into sub-problems with closed-form solutions. {For GMR maximization, we develop an alternating optimization (AO)-based algorithm that also yields closed-form solutions and can be seamlessly adapted for SR maximization. Numerical results validate the effectiveness and convergence of the proposed algorithms.} Comparative evaluations show that MR maximization ensures near-perfect fairness, while GMR maximization balances fairness and system SR. Furthermore, the two proposed algorithms respectively outperform existing related works in terms of MR and SR performance. Lastly, SIM with lower power consumption achieves performance comparable to that of multi-antenna digital beamforming.

eess.SP↗

arXiv2025

Flexible Intelligent Metasurface for Enhancing Multi-Target Wireless Sensing

Flexible intelligent metasurface (FIM) has emerged as a transformative technology to enhance wireless sensing by dynamically morphing its three-dimensional (3D) surface shape and electromagnetic response. Unlike conventional rigid arrays, an FIM consists of low-cost radiating elements that can independently adjust their positions and radiation characteristics, thereby allowing for real-time optimization of the sensing environment. This paper investigates the impact of FIM on wireless sensing performance. Specifically, we focus on the maximization of the cumulated power of the probing signals at the target locations under the per-antenna power constraint by jointly optimizing the transmit covariance matrix and the surface shape of the transmitting FIM. We propose a block coordinate descend (BCD) algorithm to find a locally optimal solution, by alternatively updating the FIM surface shape and the transmit covariance matrix, while keeping the other one fixed at each step. Furthermore, we analyze the computational complexity and convergence properties of the proposed algorithm and demonstrate that FIM enhances wireless sensing by providing a new design degree-of-freedom to coordinate the correlation between steering vectors at different angles. Numerical results demonstrate that FIM significantly improves wireless sensing performance under the considered multi-target scenario.

cs.IT↗

arXiv2025

Stacked Intelligent Metasurfaces for Multi-Modal Semantic Communications

Semantic communication (SemCom) powered by generative artificial intelligence enables highly efficient and reliable information transmission. However, it still necessitates the transmission of substantial amounts of data when dealing with complex scene information. In contrast, the stacked intelligent metasurface (SIM), leveraging wave-domain computing, provides a cost-effective solution for directly imaging complex scenes. Building on this concept, we propose an innovative SIM-aided multi-modal SemCom system. Specifically, an SIM is positioned in front of the transmit antenna for transmitting visual semantic information of complex scenes via imaging on the uniform planar array at the receiver. Furthermore, the simple scene description that contains textual semantic information is transmitted via amplitude-phase modulation over electromagnetic waves. To simultaneously transmit multi-modal information, we optimize the amplitude and phase of meta-atoms in the SIM using a customized gradient descent algorithm. The optimization aims to gradually minimize the mean squared error between the normalized energy distribution on the receiver array and the desired pattern corresponding to the visual semantic information. By combining the textual and visual semantic information, a conditional generative adversarial network is used to recover the complex scene accurately. Extensive numerical results verify the effectiveness of the proposed multi-modal SemCom system in reducing bandwidth overhead as well as the capability of the SIM for imaging the complex scene.

cs.IT↗

arXiv2025

WirelessMathBench: A Mathematical Modeling Benchmark for LLMs in Wireless Communications

Large Language Models (LLMs) have achieved impressive results across a broad array of tasks, yet their capacity for complex, domain-specific mathematical reasoning-particularly in wireless communications-remains underexplored. In this work, we introduce WirelessMathBench, a novel benchmark specifically designed to evaluate LLMs on mathematical modeling challenges to wireless communications engineering. Our benchmark consists of 587 meticulously curated questions sourced from 40 state-of-the-art research papers, encompassing a diverse spectrum of tasks ranging from basic multiple-choice questions to complex equation completion tasks, including both partial and full completions, all of which rigorously adhere to physical and dimensional constraints. Through extensive experimentation with leading LLMs, we observe that while many models excel in basic recall tasks, their performance degrades significantly when reconstructing partially or fully obscured equations, exposing fundamental limitations in current LLMs. Even DeepSeek-R1, the best performer on our benchmark, achieves an average accuracy of only 38.05%, with a mere 7.83% success rate in full equation completion. By publicly releasing WirelessMathBench along with the evaluation toolkit, we aim to advance the development of more robust, domain-aware LLMs for wireless system analysis and broader engineering applications.

cs.CL↗

arXiv2025

Emerging Technologies in Intelligent Metasurfaces: Shaping the Future of Wireless Communications

Intelligent metasurfaces have demonstrated great promise in revolutionizing wireless communications. One notable example is the two-dimensional (2D) programmable metasurface, which is also known as reconfigurable intelligent surfaces (RIS) to manipulate the wireless propagation environment to enhance network coverage. More recently, three-dimensional (3D) stacked intelligent metasurfaces (SIM) have been developed to substantially improve signal processing efficiency by directly processing analog electromagnetic signals in the wave domain. Another exciting breakthrough is the flexible intelligent metasurface (FIM), which possesses the ability to morph its 3D surface shape in response to dynamic wireless channels and thus achieve diversity gain. In this paper, we provide a comprehensive overview of these emerging intelligent metasurface technologies. We commence by examining recent experiments of RIS and exploring its applications from four perspectives. Furthermore, we delve into the fundamental principles underlying SIM, discussing relevant prototypes as well as their applications. Numerical results are also provided to illustrate the potential of SIM for analog signal processing. Finally, we review the state-of-the-art of FIM technology, discussing its impact on wireless communications and identifying the key challenges of integrating FIMs into wireless networks.

cs.IT↗

arXiv2025

Dynamic Precoding for Near-Field Secure Communications: Implementation and Performance Analysis

The increase in antenna apertures and transmission frequencies in next-generation wireless networks is catalyzing advancements in near-field communications (NFC). In this paper, we investigate secure transmission in near-field multi-user multiple-input single-output (MU-MISO) scenarios. Specifically, with the advent of extremely large-scale antenna arrays (ELAA) applied in the NFC regime, the spatial degrees of freedom in the channel matrix are significantly enhanced. This creates an expanded null space that can be exploited for designing secure communication schemes. Motivated by this observation, we propose a near-field dynamic hybrid beamforming architecture incorporating artificial noise, which effectively disrupts eavesdroppers at any undesired positions, even in the absence of their channel state information (CSI). Furthermore, we comprehensively analyze the dynamic precoder's performance in terms of the average signal-to-interference-plus-noise ratio, achievable rate, secrecy capacity, secrecy outage probability, and the size of the secrecy zone. In contrast to far-field secure transmission techniques that only enhance security in the angular dimension, the proposed algorithm exploits the unique properties of spherical wave characteristics in NFC to achieve secure transmission in both the angular and distance dimensions. Remarkably, the proposed algorithm is applicable to arbitrary modulation types and array configurations. Numerical results demonstrate that the proposed method achieves approximately 20\% higher rate capacity compared to zero-forcing and the weighted minimum mean squared error precoders.

cs.IT↗

arXiv2025

Over-the-Air ODE-Inspired Neural Network for Dual Task-Oriented Semantic Communications

Analog machine-learning hardware platforms promise greater speed and energy efficiency than their digital counterparts. Specifically, over-the-air analog computation allows offloading computation to the wireless propagation through carefully constructed transmitted signals. In addition, reconfigurable intelligent surface (RIS) is emerging as a promising solution for next-generation wireless networks, offering the ability to tailor the communication environment. Leveraging the advantages of RIS, we design and implement the ordinary differential equation (ODE) neural network using over-the-air computation (AirComp) and demonstrate its effectiveness for dual tasks. We engineer the ambient wireless propagation environment through distributed RISs to create an architecture termed the over-the-air ordinary differential equation (Air-ODE) network. Unlike the conventional digital ODE-inspired neural network, the Air-ODE block utilizes the physics of wave reflection and the reconfigurable phase shifts of RISs to implement an ODE block in the analog domain, enhancing spectrum efficiency. Moreover, the advantages of Air-ODE are demonstrated in a deep learning-based semantic communication (DeepSC) system by extracting effective semantic information to reduce the data transmission load, while achieving the dual functions of image reconstruction and semantic tagging simultaneously at the receiver. Simulation results show that the analog Air-ODE network can achieve similar performance to the digital ODE-inspired network. Specifically, for the image reconstruction and semantic tagging task, compared with the analog network without the Air-ODE block, the Air-ODE block can achieve around 2 times gain in both reconstruction quality and tagging accuracy.

eess.SP↗

arXiv2025

Stacked Intelligent Metasurfaces for Wireless Communications: Applications and Challenges

The rapid growth of wireless communications has created a significant demand for high throughput, seamless connectivity, and extremely low latency. To meet these goals, a novel technology -- stacked intelligent metasurfaces (SIMs) -- has been developed to perform signal processing by directly utilizing electromagnetic waves, thus achieving incredibly fast computing speed while reducing hardware requirements. In this article, we provide an overview of SIM technology, including its underlying hardware, benefits, and exciting applications in wireless communications. Specifically, we examine the utilization of SIMs in realizing transmit beamforming and semantic encoding in the wave domain. Additionally, channel estimation in SIM-aided communication systems is discussed. Finally, we highlight potential research opportunities and identify key challenges for deploying SIMs in wireless networks to motivate future research.

cs.IT↗

arXiv2025

Stacked Intelligent Metasurfaces for Multiuser Downlink Beamforming in the Wave Domain

Intelligent metasurface has recently emerged as a promising technology that enables the customization of wireless environments by harnessing large numbers of low-cost reconfigurable scattering elements. However, prior studies have predominantly focused on single-layer metasurfaces, which have limitations in terms of wave-domain processing capabilities due to practical hardware limitations. In contrast, this paper introduces a novel stacked intelligent metasurface (SIM) design. Specifically, we investigate the integration of SIM into the downlink of a multiuser multiple-input single-output (MISO) communication system, where an SIM, consisting of a multilayer metasurface structure, is deployed at the base station (BS) to facilitate transmit beamforming in the electromagnetic wave domain. This eliminates the need for conventional digital beamforming and high-resolution digital-to-analog converters at the BS. To this end, an optimization problem is formulated to maximize the sum rate of all user equipments by jointly optimizing the transmit power allocation at the BS and the wave-based beamforming at the SIM, subject to constraints on the transmit power budget and discrete phase shifts. Furthermore, we propose a computationally efficient algorithm for solving the formulated joint optimization problem and elaborate on the potential benefits of employing SIM in wireless networks. Numerical results are illustrated to corroborate the effectiveness of the proposed SIM-enabled wave-based beamforming design and to evaluate the performance improvement achieved by the proposed algorithm compared to various benchmark schemes. It is demonstrated that considering the same number of transmit antennas, the proposed SIM-based system achieves about 200\% improvement in terms of sum rate compared to conventional MISO systems. The code for this paper is available at \url{https://github.com/JianchengAn}.

cs.IT↗