arXiv subjects

Qingqing Wu

Publications and source records attributed to Qingqing Wu.

At least 73 records · Page 4Linked to original sources

arXiv2025

Reconfigurable Intelligent Surface-Enhanced Satellite Networks: Deployment Strategies, Key Capabilities, Practical Solutions, and Future Directions

Satellite networks promise wide-area 6G coverage but face two persistent barriers: blockage-induced service discontinuities and increasingly stringent spectrum coexistence across satellite layers and with terrestrial systems. Reconfigurable intelligent surfaces (RISs) act as low-power programmable apertures that redirect energy without the cost and power consumption of fully active arrays. We develop a deployment-first, operations-aware view of RIS-enabled satellite networking that treats RIS as both satellite/terminal antennas and inter-satellite or space-ground relays. We show that system-level gains are governed by two unifying mechanisms: connectivity restoration via virtual line-of-sight links that preserve connectivity under blockage and mobility, and angular selectivity that reshapes interference to enlarge spectrum reuse. We further discuss practical operation under high mobility, highlighting Delay-Doppler channel acquisition, predictive beam tracking, and control designs that budget overhead and latency, and summarize hardware considerations for reliable operation in space. Finally, we outline forward-looking opportunities in the generative artificial intelligence paradigm, multifunctional RIS architectures, ubiquitous satellite integrated sensing and communication, and sustainable satellite Internet-of-Things.

eess.SP↗

arXiv2025

Which Channel in 6G, Low-rank or Full-rank, more needs RIS from a Perspective of DoF?

Reconfigurable intelligent surface (RIS), as an efficient tool to improve receive signal-to-noise ratio, extend coverage and create more spatial diversity, is viewed as a most promising technique for the future wireless networks like 6G. As you know, RIS is very suitable for a special wireless scenario with wireless link between BS and users being completely blocked, i.e., no link. In this paper, we extend its applications to a general scenario, i.e., rank-deficient channel, particularly some extremely low-rank ones such as no link, and line-of-sight (LoS, rank-one). Actually, there are several potential important low-rank applications like low-altitude, satellite, UAV, marine, and deep-space communications. In such a situation, it is found that RIS may make a dramatic degrees of freedom (DoF) enhancement over no RIS. By using a distributed RISs placement, the DoF of channel from BS to user in LoS channel may be even boosted from a low-rank like 0/1 to full-rank. This will achieve an extremely rate improvement via spatial parallel multiple-stream transmission from BS to user. In this paper, we present a complete review of making an in-depth discussion on DoF effect of RIS.

eess.SP↗

arXiv2025

Intelligent Metasurface-Enabled Integrated Sensing and Communication: Unified Framework and Key Technologies

As the demand for ubiquitous connectivity and high-precision environmental awareness grows, integrated sensing and communication (ISAC) has emerged as a key technology for sixth-generation (6G) wireless networks. Intelligent metasurfaces (IMs) have also been widely adopted in ISAC scenarios due to their efficient, programmable control over electromagnetic waves. This provides a versatile solution that meets the dual-function requirements of next-generation networks. Although reconfigurable intelligent surfaces (RISs) have been extensively studied for manipulating the propagation channel between base and mobile stations, the full potential of IMs in ISAC transceiver design remains under-explored. Against this backdrop, this article explores emerging IM-enabled transceiver designs for ISAC systems. It begins with an overview of representative IM architectures, their unique principles, and their inherent advantages in EM wave manipulation. Next, a unified ISAC framework is established to systematically model the design and derivation of diverse IM-enabled transceiver structures. This lays the foundation for performance optimization, trade-offs, and analysis. The paper then discusses several critical technologies for IM-enabled ISAC transceivers, including dedicated channel modeling, effective channel estimation, tailored beamforming strategies, and dual-functional waveform design.

eess.SP↗

arXiv2025

Semi-Passive IRS Enabled Sensing with Group Movable Sensors

The performance of the sensing system is limited by the signal attenuation and the number of receiving components. In this letter, we investigate the sensor position selection in a semi-passive intelligent reflecting surface (IRS) enabled non-line-of-sight (NLoS) sensing system. The IRS consists of passive elements and active sensors, where the sensors can receive and process the echo signal for direction-of-arrival (DoA) estimation. Motivated by the movable antenna array and fluid antenna system, we consider the case where the sensors are integrated into a group for movement and derive the corresponding Cramer-Rao bound (CRB). Then, the optimal solution for the positions of the movable sensors (MSs) to the CRB minimization problem is derived in closed form. Moreover, we characterize the relationship between the CRB and system parameters. Theoretical analysis and numerical results are provided to demonstrate the superiority of the proposed MS scheme over the fixed-position (FP) scheme.

eess.SP↗

arXiv2025

Fair Rate Maximization for Multi-User Multi-Cell MISO Communication Systems via Novel Transmissive RIS Transceiver

This paper explores a multi-cell multiple-input single-output (MISO) downlink communication system enabled by a unique transmissive reconfigurable intelligent surface (TRIS) transceiver configuration. Within this system framework, we formulate an optimization problem for the purpose of maximizing the minimum rate of users for each cell via designing the transmit beamforming of the TRIS transceiver, subject to the power constraints of each TRIS transceiver unit. Since the objective function is non-differentiable, the max-min rate problem is difficult to solve. In order to tackle this challenging optimization problem, an efficient low-complexity optimization algorithm is developed. Specifically, the log-form rate function is transformed into a tractable form by employing the fractional programming (FP) methodology. Next, the max-min objective function can be approximated using a differentiable function derived from smooth approximation theory. Moreover, by applying the majorization-minimization (MM) technique and examining the optimality conditions, a solution is proposed that updates all variables analytically without relying on any numerical solvers. Numerical results are presented to demonstrate the convergence and effectiveness of the proposed low-complexity algorithm. Additionally, the algorithm can significantly reduce the computational complexity without performance loss. Furthermore, the simulation results illustrate the clear superiority of the deployment of the TRIS transceiver over the benchmark schemes.

eess.SP↗

arXiv2025

Movable Intelligent Surface-Enabled Wireless Communications: Static Phase Shifts with Mechanical Reconfigurability

Intelligent surfaces that reshape electromagnetic waves are regarded as disruptive technologies for wireless networks. However, existing designs sit at two costly extremes: dynamic reconfigurable intelligent surfaces (RISs) offer fine beam control but require dense cabling, continuous power consumption, and substantial signaling overhead, whereas low-cost static surfaces require no control lines or electronics but are limited to a single beam pattern. This disparity leaves a practical gap for quasi-static environments, such as industrial Internet-of-things and smart agriculture scenarios, where channels are stable with user demands changing only occasionally or periodically, and neither extreme is sufficiently economical or flexible. To bridge this gap, we propose a novel movable intelligent surface (MIS) architecture, whose beam patterns are switched not by electronic phase tuning but by mechanically sliding a small, pre-phased secondary metasurface layer across a larger, likewise static primary layer. We develop an MIS signal model that characterizes the interaction between static phase elements with dynamic geometry via binary selection matrices. Based on this model, we formulate a new type of optimization problems that jointly design static phase shifts and the overlapping position selection of MS2 (equal to beam pattern scheduling). Efficient algorithms based on the penalty method, block coordinate descent, and Riemannian manifold optimization are proposed to tackle these mixed-integer non-convex problems. Simulation results demonstrate that the proposed MIS architecture substantially narrows the performance gap between single-layer static surfaces and dynamic RISs, providing a practical and flexible solution for quasi-static wireless applications.

eess.SP↗

arXiv2025

Fluid Antenna System-Enabled UAV-to-Ground Communications

Fluid antenna systems (FAS) have emerged as a revolutionary technology offering enhanced spatial diversity within a compact form factor. Concurrently, unmanned aerial vehicles (UAVs) are integral to future networks, necessitating channel models that capture both multipath fading and shadowing. This letter presents a novel performance analysis of a UAV-to-ground link, where the receiver is equipped with an $N$-port FAS operating over the challenging double-shadowing fading channel. By adapting a tractable eigenvalue-based approximation for the correlated FAS ports, we derive new analytical expressions for the end-to-end signal-to-noise ratio statistics, namely the cumulative distribution function and the probability density function. Based on these statistics, we present exact integral expressions for the outage probability, average bit error rate, and average channel capacity. We further derive new, tractable closed-form solutions for the average bit error rate and capacity for the practical dual-rank, independent but non-identically distributed case. Finally, a key asymptotic analysis reveals that the system achieves a multiplicative diversity order of $G_d = M \times d$, which is precisely the product of the FAS spatial rank $M$ and the intrinsic channel diversity order $d$. Simulation results are provided to validate the high accuracy of our entire theoretical framework.

cs.IT↗

arXiv2025

Cramér-Rao Bound Optimization for Fluid Antenna-Empowered Integrated Sensing and Uplink Communication System

Integrated sensing and communication (ISAC) is a promising solution for the future sixth-generation (6G) system. However, classical fixed-position antenna (FPA) ISAC systems fail to fully utilize spatial degrees of freedom (DoFs), resulting in limited gains for both radar sensing and communication functionalities. This challenge can be addressed by the emerging novel fluid antenna (FA) technology, which can pursue better channel conditions and improve sensing and communication performances. In this paper, we aim to minimize the Cramér-Rao bound (CRB) for estimating the target's angle while guaranteeing communication performance. This involves jointly optimizing active beamforming, power allocation, receiving filters, and FA position configurations, which is a highly non-convex problem. To tackle this difficulty, we propose an efficient iterative solution that analytically optimizes all variables without relying on numerical solvers, i.e., CVX. Specifically, by leveraging cutting-edge majorization-minimization (MM) and penalty-dual-decomposition (PDD) methods, we develop a low-complexity algorithm to solve the beamformer configuration problem containing the fractional and quartic terms. Numerical simulation results demonstrate the effectiveness and efficiency of our proposed algorithm, highlighting significant performance improvements achieved by employing FA in the ISAC system.

eess.SP↗

arXiv2025

Channel Ordering for Fairness in Elastic Optical Networks via a LLM-Guided Bottleneck TSP Solver

In flexible-grid elastic optical networks (EONs), the ordering of frequency channels plays a crucial role in managing inter-channel interference and ensuring signal quality. We address the Channel Ordering Problem (COP) by reformulating it as a Bottleneck Traveling Salesman Problem (BTSP), where interference among channels is represented as edge weights in a graph structure. To tackle this challenge efficiently, we develop a scalable approach that integrates statistical exploration with guidance from large language models (LLMs). Extensive simulations using both the Gaussian Noise (GN) model and the split-step Fourier method demonstrate that our method achieves near-optimal signal-to-noise ratio (SNR) performance and offers robust scalability across diverse network settings, making it well-suited for practical deployment in large-scale optical communication systems.

physics.optics↗

arXiv2025

Joint Optimization for Multi-User Transmissive RIS-MIMO Systems

Transmissive reconfigurable intelligent surfaces (RIS) represent a transformative architecture for future wireless networks, enabling a paradigm shift from traditional costly base stations to low-cost, energy-efficient transmitters. This paper explores a downlink multi-user MIMO system where a transmissive RIS, illuminated by a single feed antenna, forms the core of the transmitter. The joint optimization of the RIS coefficient vector, power allocation, and receive beamforming in such a system is critical for performance but poses significant challenges due to the non-convex objective, coupled variables, and constant modulus constraints. To address these challenges, we propose a novel optimization framework. Our approach involves reformulating the sum-rate maximization problem into a tractable equivalent form and developing an efficient alternating optimization (AO) algorithm. This algorithm decomposes the problem into subproblems for the RIS coefficients, receive beamformers, and power allocation, each solved using advanced techniques including convex approximation and difference-of-convex programming. Simulation results demonstrate that our proposed method converges rapidly and achieves substantial sum-rate gains over conventional schemes, validating the effectiveness of our approach and highlighting the potential of transmissive RIS as a key technology for next-generation wireless systems.

cs.IT↗

arXiv2025

Reconfigurable Airspace: Synergizing Movable Antenna and Intelligent Surface for Low-Altitude ISAC Networks

Low-altitude unmanned aerial vehicle (UAV) networks are integral to future 6G integrated sensing and communication (ISAC) systems. However, their deployment is hindered by challenges stemming from high mobility of UAVs, complex propagation environments, and the inherent trade-offs between coexisting sensing and communication functions. This article proposes a novel framework that leverages movable antennas (MAs) and intelligent reflecting surfaces (IRSs) as dual enablers to overcome these limitations. MAs, through active transceiver reconfiguration, and IRSs, via passive channel reconstruction, can work in synergy to significantly enhance system performance. Our analysis first elaborates on the fundamental gains offered by MAs and IRSs, and provides simulation results that validate the immense potential of the MA-IRS-enabled ISAC architecture. Two core UAV deployment scenarios are then investigated: (i) UAVs as ISAC users, where we focus on achieving high-precision tracking and aerial safety, and (ii) UAVs as aerial network nodes, where we address robust design and complex coupled resource optimization. Finally, key technical challenges and research opportunities are identified and analyzed for each scenario, charting a clear course for the future design of advanced low-altitude ISAC networks.

cs.IT↗

arXiv2025

Joint Space Time Coding on RIS for Simultaneous Direct Modulation and Beamforming

Reconfigurable Intelligent Surface (RIS)-based direct modulation communication systems have garnered significant attention due to their low cost, low power consumption, and baseband-less characteristics. However, these systems face challenges such as the random time-varying coding state of the RIS and the difficulty in implementing beamforming in direct modulation. In this paper, we propose a simple and effective joint space-time coding approach for RIS that enables simultaneous realization of both direct modulation communication and beamforming. By modeling the transmitted signals of the RIS using space-time coding, we show that the time coding determines the direct modulation functionality, while the space coding governs the beamforming. Consequently, we introduce a joint time-space coding technique by performing exclusive-or (XOR) operations on the time and space coding sequences, enabling both functionalities to be achieved concurrently. Numerical simulations demonstrate the effectiveness of the proposed method. Furthermore, we design and fabricate a transmissive 1-bit phase reconfigurable RIS operating in the 3.4~3.79 GHz frequency band for the implementation of a direct modulation communication system. Experimental results reveal that the bit error rate (BER) is significantly reduced when joint space-time coding is used, compared to using time coding alone. Additionally, the root-mean-square error vector magnitude (rmsEVM) of the constellation diagram is reduced by 55%. This technique is promising for applications in the Internet of Things (IoT), contributing to the development of intelligent networks for electronic devices.

cs.IT↗

arXiv2025

Joint Discrete Antenna Positioning and Beamforming Optimization in Movable Antenna Enabled Full-Duplex ISAC Networks

In this paper, we propose a full-duplex integrated sensing and communication (ISAC) system enabled by a movable antenna (MA). By leveraging the characteristic of MA that can increase the spatial diversity gain, the performance of the system can be enhanced. We formulate a problem of minimizing the total transmit power consumption via jointly optimizing the discrete position of MA elements, beamforming vectors, sensing signal covariance matrix and user transmit power. Given the significant coupling of optimization variables, the formulated problem presents a non-convex optimization challenge that poses difficulties for direct resolution. To address this challenging issue, the discrete binary particle swarm optimization (BPSO) algorithm framework is employed to solve the formulated problem. Specifically, the discrete positions of MA elements are first obtained by iteratively solving the fitness function. The difference-of-convex (DC) programming and successive convex approximation (SCA) are used to handle non-convex and rank-1 terms in the fitness function. Once the BPSO iteration is complete, the discrete positions of MA elements can be determined, and we can obtain the solutions for beamforming vectors, sensing signal covariance matrix and user transmit power. Numerical results demonstrate the superiority of the proposed system in reducing the total transmit power consumption compared with fixed antenna arrays.

eess.SP↗

arXiv2025

Analysis and Algorithm for Multi IRS Collaborative Localization via Hybrid Time Angle Estimation

This paper proposes a novel multiple intelligent reflecting surfaces (IRSs) collaborative hybrid localization system, which involves deploying multiple IRSs near the target area and achieving target localization through joint time delay and angle estimation. Specifically, echo signals from all reflective elements are received by each sensor and jointly processed to estimate the time delay and angle parameters. Based on the above model, we derive the Fisher Information Matrix (FIM) for cascaded delay, Angle of Arrival (AOA), and Angle of Departure (AOD) estimation in semi passive passive models, along with the corresponding Cramer Rao Bound (CRB). To achieve precise estimation close to the CRB, we design efficient algorithms for angle and location estimation. For angle estimation, reflective signals are categorized into three cases based on their rank, with different signal preprocessing. By constructing an atomic norm set and minimizing the atomic norm, the joint angle estimation problem is transformed into a convex optimization problem, and low-complexity estimation of multiple AOA and AOD pairs is achieved using the Alternating Direction Method of Multipliers (ADMM). For location estimation, we propose a three-stage localization algorithm that combines weighted least squares, total least squares, and quadratic correction to handle errors in the coefficient matrix and observation vector, thus improving accuracy. Numerical simulations validate the superiority of the proposed system, demonstrating that the system's collaboration, hybrid localization, and distributed deployment provide substantial benefits, as well as the accuracy of the proposed estimation algorithms, particularly in low signal to noise ratio (SNR) condition.

eess.SP↗

arXiv2025

Design and Analysis of Phase Conjugation-Based Self-Alignment Beamforming for RIS-Assisted Terahertz SWIPT

Terahertz (THz) simultaneous wireless information and power transfer (SWIPT) is a promising technology for enabling ultra-high-rate and low-latency communications in massive battery-free Internet of Things (IoT) deployments for 6G networks. However, conventional THz systems rely on narrow directional beams that necessitate precise alignment, typically achieved through high-overhead beam scanning procedures, which fundamentally at odds with the energy constraints of battery-free IoT devices. In this paper, we propose a novel self-alignment architecture for THz SWIPT leveraging a reconfigurable intelligent surface (RIS) to eliminate complex beam scanning. By integrating phase conjugate circuits at both the base station and user equipment, the RIS facilitates a resonance-based bidirectional retro-reflection mechanism, enabling the system to autonomously converge to an aligned state without manual intervention. We develop an analytical channel transfer model and a power cycle model to characterize the resonance-assisted beam alignment process and power transfer efficiency. Simulation results demonstrate that the RIS-enabled system achieves effective spatial power concentration with significant sidelobe suppression, leading to a communication capacity of 127.84 Gbit/s and a received power of 13.62 mW over a 2.2-meter link.

eess.SP↗

arXiv2025

Low-Altitude UAV-Carried Movable Antenna for Joint Wireless Power Transfer and Covert Communications

The proliferation of Internet of Things (IoT) networks has created an urgent need for sustainable energy solutions, particularly for the battery-constrained spatially distributed IoT nodes. While low-altitude uncrewed aerial vehicles (UAVs) employed with wireless power transfer (WPT) capabilities offer a promising solution, the line-of-sight channels that facilitate efficient energy delivery also expose sensitive operational data to adversaries. This paper proposes a novel low-altitude UAV-carried movable antenna-enhanced transmission system joint WPT and covert communications, which simultaneously performs energy supplements to IoT nodes and establishes transmission links with a covert user by leveraging wireless energy signals as a natural cover. Then, we formulate a multi-objective optimization problem that jointly maximizes the total harvested energy of IoT nodes and sum achievable rate of the covert user, while minimizing the propulsion energy consumption of the low-altitude UAV. To address the non-convex and temporally coupled optimization problem, we propose a mixture-of-experts-augmented soft actor-critic (MoE-SAC) algorithm that employs a sparse Top-K gated mixture-of-shallow-experts architecture to represent multimodal policy distributions arising from the conflicting optimization objectives. We also incorporate an action projection module that explicitly enforces per-time-slot power budget constraints and antenna position constraints. Simulation results demonstrate that the proposed approach significantly outperforms some baseline approaches and other state-of-the-art deep reinforcement learning algorithms.

cs.NI↗

arXiv2025

Six-Dimensional Movable Antenna Enabled Wideband THz Communications

In this paper, we investigate a six-dimensional movable antenna (6DMA)-enabled wideband terahertz (THz) communication system with sub-connected hybrid beamforming architecture at the base station (BS). In particular, the three-dimensional (3D) position and 3D rotation of each 6DMA surface can be flexibly reconfigured to mitigate the beam squint effects instead of introducing costly true-time-delay devices. We first analyze the normalized array gain in the 6DMA-enabled wideband THz systems based on the beam squint effects. Then, we formulate a sum-rate maximization problem via jointly optimizing 3D positions, 3D rotations, and hybrid analog/digital beamforming. To solve the non-convex problem, an alternating optimization algorithm is developed that decomposes the original problem into three subproblems, which are solved alternately. Specifically, given the positions and rotations of 6DMA surfaces, we first reformulate the objective function and design a semidefinite relaxation-based alternating minimization scheme to obtain the hybrid analog/digital beamforming. Then, the positions and rotations of the 6DMA surfaces are further optimized through a feasible gradient descent procedure. The final solutions are obtained by repeating the above procedure until convergence. Numerical results demonstrate the superior performance of the proposed scheme compared with conventional fixed-position antenna architectures.

physics.comp-ph↗

arXiv2025

Joint Beamforming Design and Resource Allocation for IRS-Assisted Full-Duplex Terahertz Systems

Intelligent reflecting surface (IRS)-assisted full-duplex (FD) terahertz (THz) communication systems have emerged as a promising paradigm to satisfy the escalating demand for ultra-high data rates and spectral efficiency in future wireless networks. However, the practical deployment of such systems presents unique technical challenges, stemming from severe propagation loss, frequency-dependent molecular absorption in the THz band, and the presence of strong residual self-interference (SI) inherent to FD communications. To tackle these issues, this paper proposes a joint resource allocation framework that aims to maximize the weighted minimum rate among all users, thereby ensuring fairness in quality of service. Specifically, the proposed design jointly optimizes IRS reflecting phase shifts, uplink/downlink transmit power control, sub-band bandwidth allocation, and sub-band assignment, explicitly capturing the unique propagation characteristics of THz channels and the impact of residual SI. To strike an balance between system performance and computational complexity, two computationally efficient algorithms are developed under distinct spectrum partitioning schemes: one assumes equal sub-band bandwidth allocation to facilliate tractable optimization, while the other introduces adaptive bandwidth allocation to further enhance spectral utilization and system flexibility. Simulation results validate the effectiveness of the proposed designs and demonstrate that the adopted scheme achieves significant spectral efficiency improvements over benchmark schemes.

cs.IT↗