Search Results (321)

In widely deployed Internet of Things (IoT) scenarios, physical-layer key generation (PLKG) serves as a useful complement to conventional cryptographic methods, yet it often suffers from a fundamentally low key generation rate, which becomes particularly severe in quasi-static environments. This low rate is mainly attributed to three key issues: (1) slow channel variations, which provide insufficient randomness and thus limit the key generation rate; (2) correlation between the legitimate channel and the eavesdropping channel, which reduces the uniqueness of the extracted key and further degrades the achievable rate; and (3) insufficient degrees of freedom in the key source, which constrain the key space. To address these challenges, this paper introduces the Dynamic Agile Reconfigurable Intelligent Surface Antenna into physical-layer key generation. By deploying metasurface antennas at both ends and independently applying random phase modulation, the scheme injects two-sided randomness, thereby mitigating the adverse effects of quasi-static channels and legitimate eavesdropper channel correlation. Moreover, by leveraging the dynamic, agile, and reconfigurable characteristics of the metasurface antennas in the key generation process, the proposed approach can further enhance the key generation rate while simultaneously resolving all three issues above. The proposed scheme is developed under a general setting where correlation exists between the legitimate and eavesdropping channels. A closed-form expression for the key capacity is rigorously derived, accompanied by detailed theoretical analysis and simulations. The results demonstrate the superiority of the proposed approach when applied to physical-layer key generation. Full article

Reconfigurable intelligent surface (RIS)-aided index modulation (IM) shows great potential for next-generation wireless communications. Nevertheless, obtaining channel state information (CSI) for RIS-based IM incurs high pilot overhead, particularly for multi-domain IM. In this paper, we integrate orthogonal frequency division multiplexing into RIS-aided differential reflecting modulation (DRM) communications, introducing the differential reflecting frequency modulation (DRFM) system. In DRFM, information bits are jointly conveyed through the activation permutations of reflecting patterns, grouped carriers, and constellation symbols. The transmitter combines the differentially coded reflecting-time block and the time–frequency block using the Kronecker product. This allows DRFM to operate without relying on CSI at the transmitter, RIS, or receiver. Moreover, we design a novel high-rate quadrature amplitude modulation (QAM) scheme for DRFM. Compared to PSK-based DRFM, this QAM scheme can boost either the throughput or the performance of DRFM. Simulation results illustrate the superiority of the DRFM system, along with an acceptable SNR penalty, compared to non-differential modulation with coherent detection. At the same spectral efficiency, the proposed QAM-aided DRFM outperforms schemes using traditional PSK, amplitude phase shift keying (APSK), and star-QAM constellation modulations. Full article

The integration of reconfigurable intelligent surfaces (RISs) with flying ad hoc networks (FANETs) offers new opportunities to enhance performance in aerial communications. This paper proposes a novel FANET architecture in which each unmanned aerial vehicle (UAV) or drone is equipped with an RIS comprising M passive elements, enabling dynamic manipulation of the wireless propagation environment. We address the joint power allocation and RIS configuration problem to maximize the sum spectral efficiency, subject to constraints on maximum transmit power and unit-modulus phase shifts. The formulated optimization problem is non-convex due to coupled variables and interference. We develop an alternating optimization-based joint power and phase shift (AO-JPPS) algorithm that decomposes the problem into two subproblems: power allocation via successive convex approximation and phase optimization via Riemannian manifold optimization. A key contribution is addressing the RIS coupling effect, where the configuration of each RIS simultaneously influences multiple communication links. Complexity analysis reveals polynomial-time scalability, while derived performance bounds provide theoretical insights. Numerical simulations demonstrate that our approach achieves significant spectral efficiency gains over conventional FANETs, establishing the effectiveness of RIS-assisted drone networks for future wireless applications. Full article

With the development of 6G technology, conventional wireless communication systems are increasingly unable to meet stringent performance requirements in complex and dynamic environments. Therefore, integrated sensing and communication (ISAC), which enables efficient spectrum sharing, has attracted growing attention as a promising solution. This paper provides a comprehensive survey of reconfigurable intelligent surface (RIS)-unmanned aerial vehicle (UAV)-assisted ISAC systems. It first introduces a four-dimensional quantitative evaluation framework grounded in information theory. Then, we provide a structured overview of coordination mechanisms between different types of RIS and UAV platforms within ISAC architectures. Furthermore, we analyze the application characteristics of various multiple access schemes in these systems. Finally, the main technical challenges and potential future research directions are discussed and analyzed. Full article

This paper presents a high-level system architecture that integrates the Software Defined Networking (SDN) paradigm in 5G/6G networks with the aim of supporting the requirements expected for Industrial Internet of Things (IIoT) devices and services. To this purpose, we include multiple Reconfigurable Intelligent Surfaces (RISs) systems and provide for them an abstract representation consistent with the OpenFlow interface and messaging framework. The main contribution of this is firstly focused on designing a comprehensive framework that specifies the modules, components, interfaces, protocols, and message exchanges across the typical three layers SDN architecture. In addition, we characterize the Network Discovery (ND) and Host Discovery (HD) protocols that enable the SDN Controller to achieve a global and updated view of the network. Then, the RIS Placement and Selection Problem (RPSP) is formulated by using two graph-theory approaches, i.e., Set Covering (SC) and Minimum Spanning Tree (MST). Finally, we conduct an extensive simulation campaign that evaluates the performance of the discovery phases and the RIS placement/selection algorithms in realistic industrial environments. The results highlight the advantages achieved in terms of coverage and complexity. Full article

The advent of sixth-generation (6G) imposes stringent demands on wireless networks, while traditional 2D rigid reconfigurable intelligent surfaces (RISs) face bottlenecks in regulatory freedom and scenario adaptability. To address this, stacked intelligent metasurfaces (SIMs) have emerged. This paper presents a systematic review of SIM technology. It first elaborates on the SIM multi-layer stacked architecture and wave-domain signal-processing principles, which overcome the spatial constraints of conventional RISs. Then, it analyzes challenges, including beamforming and channel estimation for SIM, and explores its application prospects in key 6G scenarios such as integrated sensing and communication (ISAC), low earth orbit (LEO) satellite communication, semantic communication, and UAV communication, as well as future trends like integration with machine learning and nonlinear devices. Finally, it summarizes the open challenges in low-complexity design, modeling and optimization, and performance evaluation, aiming to provide insights to promote the large-scale adoption of SIM in next-generation wireless communications. Full article

The rapid growth of wireless devices, the expansion of the Internet of Things, and the aggregate demand for Ultra-Reliable Low-Latency communications (URLLC) are driving the improvement of next-generation wireless systems. One promising emerging technology in this area is cell-free massive Multiple Input Multiple Output (maMIMO) networks. The distributed nature of Access Points presents unique security challenges that must be addressed to unlock their full potential. This paper studies the key security concerns in Cell Free Massive MIMO (CFMM) networks, including eavesdropping, Denial-of-Service attacks, jamming, pilot contamination, and methods for enhancing Physical Layer Security (PLS). We also provide an overview of security solutions specifically designed for CFMM networks and introduce a case study of a Reconfigurable Intelligent Surface (RIS)-aided secure scheme that jointly optimizes the RIS phase shifts with the artificial noise (AN) covariance under power constraints. The non-convex optimization problem is solved via the block coordinate descent (BCD) alternating optimization scheme. The combined RIS, AN, and beamforming configuration achieves a balanced trade-off between security and energy performance, resulting in moderate improvements over the individual schemes. Full article

A novel wideband 1-bit reconfigurable transmitarray (RTA) is proposed, which is based on a substrate-integrated cavity-backed patch (SCIBP) element. The RTA element consists of a pair of SCIBP antennas, achieving wideband operational capability through the optimization of dielectric substrate thickness. To suppress surface-wave propagation between adjacent RTA elements, a substrate-integrated waveguide (SIW) is designed to function as a metallic isolation wall. A 180° phase shift is realized by dynamically manipulating p-i-n diodes embedded within the SCIBP antenna structure. When the dielectric substrate thickness is increased from 6 mm to 10 mm, the 3 dB transmission bandwidth is expanded from 10% to 33.6%. The simulation results confirm that the proposed element realizes a 3 dB transmission bandwidth of 33.6%. A prototype RTA with 100 elements is designed, fabricated, and measured. The prototype achieves a peak gain of 16.6 dBi at 4.6 GHz, accompanied by an aperture efficiency of 17.2% and a 3 dB gain bandwidth of 18.9%. Furthermore, measured scanned beams illustrate that the proposed RTA possesses good beamscanning performance. Owing to its many advantages, such as wideband operation, lightweight design, low cost, simple structure, and easy fabrication, it is particularly suitable for application in intelligent communication systems and radar systems. Full article

Future internet of things (IoT) services necessitate the integration of sensing and communication functions within the same system, utilizing digital twin (DT) technology. Integrated sensing and communication (ISAC) can address the need for widespread communication and high-precision sensing by leveraging the benefits of spectrum and hardware resource sharing. The DT represents a promising technology for achieving low latency and high energy efficiency, leveraging real-time monitoring, optimization, and predictive maintenance capabilities. Recent advancements in DT and ISAC for IoT systems research necessitate the establishment of effective communication technology methods between the physical entity and its digital representation. Most prior research reviews have not sufficiently explored the critical enabling technologies for DT and ISAC applications in IoT systems that facilitate communication between a physical entity and its digital counterparts. Previous research has primarily focused on the application of DT technology in IoT systems; however, little emphasis has been placed on the integration of ISAC technology with DT in IoT systems, as well as the important integrated sensing and communication technologies between physical entities and their digital counterparts. This paper presents a systematic literature review that focuses on the analysis of key communication technologies that facilitate connections in DT and ISAC for IoT systems. The implications of communication methods derived from the study are presented, focusing on technologies such as unmanned aerial vehicles (UAVs), reconfigurable intelligent surfaces (RISs), millimeter wave (mmWave), and massive MIMO (mMIMO) technologies. The emphasis on these technologies is due to their significance as essential enablers of integrated sensing and communication between physical entities and their digital counterparts. Furthermore, these technologies are critical for integrating DT and ISAC into the IoT systems to efficiently meet the needs of IoT services. Future discussions are finally addressing open research and the challenges that demand attention. Full article

Sparse code multiple access (SCMA) and reconfigurable intelligent surfaces (RISs) are two promising techniques in the forthcoming 6G communication networks to provide massive connectivity and enhance the spectral efficiency. To our best knowledge, the phase optimization for the reflecting elements and multi-user detection for the RIS-assisted downlink MIMO-SCMA system is still an open issue. In this way, we first formulate the RIS-assisted downlink MIMO-SCMA model with respect to the phases of the reflecting elements for the RIS. Next, a closed-form solution to these phases is found by solving the geometric median optimization. The iterative symbol detection steps are also provided for the RIS-assisted downlink MIMO-SCMA system. Simulation results illustrate that the proposed RIS-assisted downlink MIMO-SCMA system can significantly enhance the bit error ratio performance; e.g., the RIS-SCMA system with the proposed Gmedian-optimized phases can achieve a 1.5dB SNR gain as compared to the random phases with 10 reflecting elements. Full article

Unmanned Aerial Vehicles (UAVs) are integral components of future 6G networks, offering rapid deployment, enhanced line-of-sight communication, and flexible coverage extension. However, UAV communications in low-altitude environments face significant challenges, including rapid link variations due to attitude instability, severe signal blockage by urban obstacles, and critical sensitivity to transmitter–receiver alignment. While traditional planar reconfigurable intelligent surfaces (RIS) show promise for mitigating these issues, they exhibit inherent limitations such as angular sensitivity and beam squint in wideband scenarios, compromising reliability in dynamic UAV scenarios. To address these shortcomings, this paper proposes and evaluates a spherical-cap reflective intelligent surface (ScRIS) specifically designed for dynamic low-altitude communications. The intrinsic curvature of the ScRIS enables omnidirectional reflection capabilities, significantly reducing sensitivity to UAV attitude variations. A rigorous analytical model founded on Generalized Sheet Transition Conditions (GSTCs) is developed to characterize the electromagnetic scattering of the curved metasurface. Three distinct 1-bit RIS unit cell coding arrangements, namely alternate, chessboard, and random, are investigated via numerical simulations utilizing CST Microwave Studio and experimental validation within a mechanically stirred reverberation chamber. Our results demonstrate that all tested ScRIS coding patterns markedly enhance electromagnetic field uniformity within the chamber and reduce the lowest usable frequency (LUF) by approximately 20% compared to a conventional metallic spherical reflector. Notably, the random coding pattern maximizes phase entropy, achieves the most uniform scattering characteristics and substantially reduces spatial field autocorrelation. Furthermore, the combined curvature and coding functionality of the ScRIS facilitates simultaneous directional focusing and diffuse scattering, thereby improving multipath diversity and spatial coverage uniformity. This effectively mitigates communication blind spots commonly encountered in UAV applications, providing a resilient link environment despite UAV orientation changes. To validate these findings in a practical context, we conduct link-level simulations based on a reproducible system model at 3.5 GHz, utilizing electromagnetic scale invariance to bridge the fundamental scattering properties observed in the RC to the application band. The results confirm that the ScRIS architecture can enhance link throughput by nearly five-fold at a 10 km range compared to a baseline scenario without RIS. We also propose a practical deployment strategy for urban blind-spot compensation, discuss hybrid planar-curved architectures, and conduct an in-depth analysis of a DRL-based adaptive control framework with explicit convergence and complexity analysis. Our findings validate the significant potential of ScRIS as a passive, energy-efficient solution for enhancing communication stability and coverage in multi-band 6G networks. Full article

This paper proposes a transmission-path selection algorithm with joint computation and communication resource allocation for sixth-generation (6G) mobile edge computing (MEC) networks enhanced by helper-assisted device-to-device (D2D) communication and reconfigurable intelligent surfaces (RIS). The novelties of this work lie in the joint design of three key components: a helper-assisted D2D uplink scheme, a packet-partitioning cooperative MEC offloading mechanism, and RIS-assisted downlink transmission and deployment design. These components collectively enable diverse transmission paths under strict latency constraints, helping mitigate overload and reduce delay. To demonstrate its performance advantages, the proposed algorithm is compared with a baseline algorithm without helper-assisted D2D or RIS support, under two representative scheduling policies—modified maximum rate and modified proportional fair. Simulation results in single-base station (BS) and dual-BS environments show that the proposed algorithm consistently achieves a higher effective packet-delivery success percentage, defined as the fraction of packets whose total delay (uplink, MEC computation, and downlink) satisfies service-specific latency thresholds, and a lower average total delay, defined as the mean total delay of all successfully delivered packets, regardless of whether individual delays exceed their thresholds. Both metrics are evaluated separately for ultra-reliable low-latency communications, enhanced mobile broadband, and massive machine-type communications services. These results indicate that the proposed algorithm provides solid performance and robustness in supporting diverse 6G services under stringent latency requirements across different scheduling policies and deployment scenarios. Full article

The integration of movable antenna (MA) and reconfigurable intelligent surfaces (RIS) offers promising potential for enhancing simultaneous wireless information and power transfer (SWIPT) systems. In this paper, we investigate a novel MA-enabled RIS-assisted SWIPT framework, where both RIS and MA are jointly exploited to provide additional spatial degrees of freedom and reconfigurable propagation channels. Then, we formulate an energy harvesting maximization problem under communication reliability constraints by jointly optimizing the base station beamforming, RIS phase shifts, and MA positions. To tackle the proposed non-convexity problem, an efficient alternating optimization (AO) algorithm is developed, which is based on successive convex approximation (SCA) and second-order Taylor expansion. The obtained simulation outcomes reveal that incorporating MA into RIS-assisted SWIPT systems leads to notable performance gains over both conventional RIS schemes and fixed-antenna benchmarks. Full article

Driven by 5G/6G and the Internet of Things (IoT), wireless sensor networks (WSNs) are confronted with core challenges such as limited energy constraints, unbalanced resource allocation, and security vulnerabilities. To address these, WSNs are integrated with cognitive radio networks (CRNs) to alleviate spectrum scarcity, and reconfigurable intelligent surfaces (RIS) are adopted to enhance performance, but traditional passive RIS suffers from “double fading” (signal path loss from transmitter to RIS and RIS to receiver), which undermines WSNs’ energy efficiency and the physical layer security (PLS) (e.g., secrecy rate, SR) of primary users (PUs) in CRNs. This study leverages symmetry to develop an active RIS framework for WSN-integrated CRNs, constructing a tripartite collaborative model where symmetric beamforming and resource allocation improve WSN connectivity, reduce energy consumption, and strengthen PLS. Specifically, three symmetry types—resource allocation symmetry, beamforming structure symmetry, and RIS reflection matrix symmetry—are formalized mathematically. These symmetries reduce the degrees of freedom in optimization (e.g., cutting precoding complexity by ~50%) and enhance the directionality of green interference, while ensuring balanced resource use for WSN nodes. The core objective is to minimize total transmit power while satisfying constraints of PU SR, secondary user (SU) quality-of-service (QoS), and PU interference temperature, achieved by converting non-convex SR constraints into solvable second-order cone (SOC) forms and using an alternating optimization algorithm to iteratively refine CBS/PBS precoding matrices and active RIS reflection matrices, with active RIS generating directional “green interference” to suppress eavesdroppers without artificial noise, avoiding redundant energy use. Simulations validate its adaptability to WSN scenarios: 50% lower transmit power than RIS-free schemes (with four CBS antennas), 37.5–40% power savings as active RIS elements increase to 60, and a 40% lower power growth slope in multi-user WSN scenarios, providing a symmetry-aided, low-power solution for secure and efficient WSN-integrated CRNs to advance intelligent WSNs. Full article

Positioning technology based on 5G networks has been deeply integrated into everyday life. Despite this, severe non-line-of-sight (NLOS) conditions in wireless signal environments can cause signal obstructions, negatively impacting the precision and dependability of positioning services. This paper introduces an innovative algorithm called Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface Non-Line-of-Sight Angle of Arrival (STAR-RIS NLOS AOA) to address these challenges. The algorithm initially develops a system model named 5G STAR-RIS localization (GSL). By integrating STAR-RIS into the system, the model effectively overcomes the challenges of positioning in NLOS scenarios. The inclusion of STAR-RIS not only boosts the system’s adaptability but also meets the positioning requirements for users on both sides of the reflective surface simultaneously. The algorithm then utilizes the Root-MUSIC algorithm for estimating user coordinates. An optimization problem is formulated based on these estimations, with the goal of reducing the gap between estimated and real coordinates. To address this optimization, the Inertia Weight Whale Optimization Algorithm is employed, providing high-precision estimations of users’ three-dimensional positions. Simulations reveal that the proposed Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface Non-Line-of-Sight Angle of Arrival (SRNA) algorithm substantially outperforms conventional algorithms in positioning performance across different signal-to-noise ratio contexts. Specifically, in challenging NLOS situations, the SRNA algorithm can cut positioning errors by 50% to 62%, demonstrating its outstanding capability and efficiency in addressing the difficulties presented by NLOS conditions within 5G-based positioning systems. Full article