This paper proposes a novel communication scheme utilizing Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface (STAR-RIS) and Index Modulation (IM) for Industrial Internet of Things (IIoT) to enhance Spectral Efficiency (SE). In this scheme, information bits are conveyed through the active antennas combination index of the two sensors at receiver, as well as the Pattern Index (PI) of designed subsurfaces on STAR-RIS. To enable reliable detection at the IIoT Control Center (CC), a joint Maximum Likelihood (ML) detector is introduced, and an Efficient ML Approximation (EMAL) detector is developed to lower computational complexity while retaining comparable Bit Error Rate (BER). In the theoretical analysis, closed-form expressions for the Average BER (ABER) under ML detection and computational complexity are provided, and the ABER analysis is validated by Monte Carlo simulations. Theoretical analysis and simulation results confirm that the proposed scheme significantly improves SE and ABER performance. Moreover, through simulation results, the scheme’s flexibility in configuring the number of antennas of the two sensors to meet diverse system requirements is also confirmed.

Recently, state-of-the-art text-to-image generation models, such as FLUX and Ideogram 2.0, have made significant progress in sentence-level visual text rendering. In this paper, we focus on the more challenging scenarios of article-level visual text rendering and address a novel task of generating high-quality business content, including infographics and slides, based on user provided article-level descriptive prompts and ultra-dense layouts. The fundamental challenges are twofold: significantly longer context lengths and the scarcity of high-quality business content data.In contrast to most previous works that focus on a limited number of sub-regions and sentence-level prompts, ensuring precise adherence to ultra-dense layouts with tens or even hundreds of sub-regions in business content is far more challenging. We make two key technical contributions: (i) the construction of scalable, high-quality business content dataset, i.e., Infographics-650K, equipped with ultra-dense layouts and prompts by implementing a layer-wise retrieval-augmented infographic generation scheme; and (ii) a layout-guided cross attention scheme, which injects tens of region-wise prompts into a set of cropped region latent space according to the ultra-dense layouts, and refine each sub-regions flexibly during inference using a layout conditional CFG. We demonstrate the strong results of our system compared to previous SOTA systems such as FLUX and SD3 on our BizEval prompt set. Additionally, we conduct thorough ablation experiments to verify the effectiveness of each component. We hope our constructed Infographics-650K and BizEval can encourage the broader community to advance the progress of business content generation.

The visual world around us constantly evolves, from real-time news and social media trends to global infrastructure changes visible through satellite imagery and augmented reality enhancements. However, Multimodal Large Language Models (MLLMs), which automate many tasks, struggle to stay current, limited by the cutoff dates in their fixed training datasets.To quantify this stagnation, we introduce LiveVQA, the first-of-its-kind dataset featuring 107,143 samples and 12 categories data specifically designed to support research in both seeking and updating with live visual knowledge.Drawing from recent news articles, video platforms, and academic publications in April 2024-May 2025, LiveVQA enables evaluation of how models handle latest visual information beyond their knowledge boundaries and how current methods help to update them. Our comprehensive benchmarking of 17 state-of-the-art MLLMs reveals significant performance gaps on content beyond knowledge cutoff, and tool-use or agentic visual seeking framework drastically gain an average of 327% improvement. Furthermore, we explore parameter-efficient fine-tuning methods to update MLLMs with new visual knowledge.We dive deeply to the critical balance between adapter capacity and model capability when updating MLLMs with new visual knowledge. All the experimental dataset and source code are publicly available at: https://livevqa.github.io.

In recent years, a number of new technologies have emerged in the sixth generation (6G) wireless communication area. Reconfigurable intelligent surface (RIS) technologies have been widely studied because of their strong flexibility for signal adjustment. Combined with transmit spatial modulation (TSM), the RIS-aided TSM (RIS-TSM) system can significantly boost spectral efficiency (SE) while enhancing the received signal quality. In this paper, in order to overcome the effect of correlation among transmit antennas in RIS-TSM systems, we propose an RIS-aided transmit signature constellation based spatial modulation (RIS-TSSM) scheme with a complete system model and expressions. Simulation results depict that RIS-TSSM system can achieve better performance than the RIS-TSM system in the presence of antenna correlation.

Polarization-spatial modulation (PSM) has been recently proposed to improve the system performance and energy efficiency of the conventional polarization modulation (PM) by activating only a single dual-polarized (DP) antenna for signal transmission. However, the spectral efficiency (SE) of PSM is significantly degraded due to the single DP antenna transmission. To tackle this problem, we propose a generalized PSM (GPSM) scheme to enhance the SE of PSM through transmission using multiple DP antennas. In the GPSM scheme, the information bits are mapped to antenna activation patterns (AAPs), polarization matrix activation patterns (PAPs), and modulated symbols. To further enhance the SE of GPSM, we propose a more practical scheme termed multi-mode GPSM (MM-GPSM), which transmits information bits not only through the AAPs, PAPs, and modulated symbols but also via the constellation activation patterns (CAPs). A low-complexity maximum likelihood (ML) detector and a log-likelihood ratio detector for both GPSM and MM-GPSM are proposed to relieve the high computational complexity of the optimal ML detector at the cost of a negligible performance loss. An upper bound on the bit error rate (BER) is derived in closed-form to evaluate the performance of both GPSM and MM-GPSM. Simulation results show that GPSM and MM-GPSM outperform the conventional PM and PSM schemes, particularly in the high signal-to-noise ratio (SNR) region, and verify the accuracy of the theoretical analysis of the upper-bounded BER.

In this paper, we propose a novel polarized reconfigurable intelligent surface (PRIS) -assisted polarized spatial scattering modulation (PSSM) for millimeter wave (mmWave) multiple input multiple output (MIMO) systems. In the PRIS-PSSM system, the PRIS is employed between the transmitter and receiver to provide a supplementary link to enhance spectrum efficiency. A strong line-of-light (LoS) path is considered in the transmitter-PRIS channel to reduce transmission power and non-line-of-light (NLoS) paths are considered in the PRIS-receiver channel to utilize scatters to convey information bits. At the receiver, an optimal maximum likelihood detector (MLD), a sub-optimal MLD, and a low-complexity detector based on minimum mean square error (MMSE) algorithm are proposed and applied to detect the received signals. Furthermore, two union upper bounds (UUBs) based on the optimal MLD and sub-optimal MLD are respectively derived in a closed-form. And the tightness of the proposed two closed-form UUBs are validated via link level simulations. In addition, the complexity of the proposed three detection algorithms is compared. Numerical results demonstrate that the proposed PRIS-PSSM system outperforms the conventional PSSM system in terms of the average bit error probability (ABEP). And the performance of the PRIS-PSSM system can be improved significantly in proportion to the number of PRIS elements.

The application of internet of things (IoT) may suffer from serious security issue, such as the attack and wiretap from jammers and eavesdroppers, which results in the degradation of reception of useful signals at the IoT devices (users), affecting the secrecy performance for the IoT application. In this work, we propose to introduce an active simultaneously transmitting and reflecting reconfigurable intelligent surface (ASTAR-RIS) to resist jamming and eavesdropping caused by multiple jammers and eavesdroppers, respectively. For the security purpose, we formulate a sum rate maximization problem subject to the imperfect channel state information and maximum tolerable leakage rate at the eavesdroppers. By jointly optimizing beamformers at the base station and that at the ASTAR-RIS including phase shifts and amplification factors, simulation results show that the proposed robust scheme is able to provide significant improvement as compared with other baselines.

The integration of the Sixth-Generation (6G) communication technology with the Internet of Things (IoT) is one of the directions in achieving a digitalized world, aiming to provide ultra-high-speed communication services that exhibit higher energy-efficiency, lower latency, and heightened reliability and availability. In this paper, we investigate the use of the Simultaneous Transmitting and Reflecting Reconfigurable Intelligent Surface (STAR-RIS), one of the candidate technologies for 6G communication, along with the Index Modulation (IM) in multi-antennas Ambient Backscatter Communication System (ABCS) to form the STAR-RIS-assisted ABCS with Spatial Modulation (STAR-RIS-ABCS-SM). In particular, through the utilization of STAR-RIS and backscatter communication, we meet the demand for low-power wireless communication devices in the green communication, which is also a crucial characteristic of the IoT. Specifically, we introduce STAR-RIS into ABCS, which not only significantly boost the signal strength but also achieve full communication coverage. Meanwhile, we apply the SM technology in the multi-antennas Backscatter Tags (BTs), located on both sides of the STAR-RIS, and use joint detection at the reader to enhance the system’s Spectral Efficiency (SE) as well as its Bit Error Rate (BER) performance. Furthermore, we divide the STAR-RIS into various subsurfaces to form patterns that further enhance SE, which is termed STAR-RIS-assisted ABCS with Pattern Index and SM (STAR-RIS-ABCS-PISM) scheme. Finally, theoretical BER analytical expressions for both schemes are derived and presented. Simulation and theoretical results demonstrate the enhanced performance of the proposed schemes as well as the validity of the system model.

Due to the limited bandwidth and severe noise interference in underwater acoustic channels, underwater image transmission typically requires a coding scheme with a high compression ratio and strong robustness. However, existing semantic communication methods are predominantly designed for terrestrial wireless scenarios and do not fully consider the unique characteristics of underwater images and channel features. To address these problems, we propose an efficient semantic communication scheme of underwater images guided by physical priors. Specifically, we design a semantic encoder-decoder with a hybrid architecture of CNN and Swin Transformer for efficient semantic feature extraction and reconstruction. Meanwhile, we design an underwater physical prior fusion module, which leverages physical prior knowledge from underwater imaging to optimize the encoding process, preserving and enhancing essential semantic features. Additionally, a noise-aware training strategy is proposed to guide the network in learning the noise characteristics of measured underwater acoustic channels, improving its robustness in intricate marine conditions. Extensive experiments verify that our method outperforms existing schemes regarding transmission efficiency and image quality.

In this paper, a novel three-dimensional polarized spatial scattering modulation (3-D PSSM), which exploits the available degrees of freedom in the spatial scattering path domain and polarization domain to increase spectral efficiency, is proposed for uplink millimeter-wave (mmWave) multiple-input-multiple-output (MIMO) system. At the receiver, considering the non-orthogonality of the array vectors, a whitening filter based on optimal maximum likelihood detection (MLD) is designed and applied to detect received signals. A tight union upper bound (UUB) on the average bit error probability (ABEP) is derived in a closed-form. Furthermore, a simplified UUB on the ABEP is derived for fast evaluation of the system. And the tightness of the derived UUBs is validated via Monte Carlo simulations. In addition, the 3-D PSSM system under imperfect channel state information (CSI) is investigated. Finally, the ABEP performance of the 3-D PSSM is analyzed in typical indoor propagation environments. Numerical results demonstrate that the proposed 3-D PSSM system outperforms the conventional three-dimensional spatial scattering modulation (3-D SSM) system and the two-dimensional (2-D) PSSM system, which is considerably degraded due to indiscernible scattering paths.

The reconfigurable intelligent surface (RIS)-aided vehicle road cooperation (VRC) scheme is a promising technique. However, the security issue of the RIS-VRC systems is still a crucial problem due to the high connectivity of multiple vehicles under the broadcasting environment. Within this study, based on the potential of the RIS-VRC system, a novel low-complexity consecutive artificial noise (CAN) with legal channel state information (CSI) and a low-cost and spectral-efficient secure index modulation (IM) design physical layer security (PLS) scheme is detailed. Specifically, an information symbol consisting of a modulation symbol and AN devised based on the CSI of the legitimate link across two consecutive time intervals is transmitted. At the receiver, the decoding scheme relies on two consecutive time intervals which can enable the ideal elimination of AN solely at the authorized vehicle is proposed. Nevertheless, given the independence of the CSI for the legitimate links and the illegitimate links, the unauthorized vehicle remains vulnerable to AN interference. Moreover, the antenna selection method based on minimum Euclidean distance (MED-TAS) is proposed to guarantee the requisite number of transmitting antennas for IM. Finally, the expressions of the secrecy rate are deduced by considering the disparity in the attainable mutual information between the authorized vehicle and the eavesdropping vehicle. Compared with traditional PLS schemes, the numerical outcomes affirm the capability of the proposed scheme to attain enhanced security performance with much lower complexity.

In this paper, we propose a robust secure communication scheme for a two-Unmanned Aerial Vehicle (UAV) scenario with the assistance of Intelligent Reflecting Surface (IRS), in which one legitimate user and one eavesdropper are considered. In the proposed scheme, the information is transmitted from one UAV named information UAV to the user via the assistance of the IRS, while the jamming information is transmitted by the other UAV named jamming UAV equipped with multi-antenna to interfere with the eavesdropper and safeguard the communication between information UAV and legitimate receiver. For the considered communication system, we assume that the Channel State Information (CSI) of the eavesdropping channels are imperfect. In this imperfect CSI case, we formulate a robust non-convex optimization problem. By jointly optimizing UAV transmit power, trajectory, and IRS phase shifters, the suboptimal average secrecy rate of the proposed scheme can be obtained. Specifically, Lagrangian dual transform and quaduratic transform are introduced to convert the objective function into more tractable form; S-Procedure is used for handling CSI uncertainty; and a two-stage penalty function algorithm is applied to obtain rank-one phase shifters solution. Numerical simulation results validate some interesting insights: (1) The IRS can bring strong robustness to the two-UAV security communication system; (2) Deploying jamming UAV in the IRS-UAV security communication system can greatly improve security performance, especially employing more antennas at the jamming UAV.

Unmanned aerial vehicles (UAVs) could acquire strong line-of-sight (LoS) channels for terrestrial nodes, which means UAV communications are more vulnerable to jammers and eavesdroppers. Thanks to the reconfigurable intelligent surface (RIS), it is capable of reconfiguring the propagation environment and has good prospects for forthcoming secure transmission in combination with UAV wireless network. In this paper, we facilitate RIS to aid the uplink communication between the ground user and the UAV in the existence of a malevolent jammer and an eavesdropper by maximizing the average secrecy rate (ASR) of the proposed scheme. In order to achieve this goal, we jointly optimize the transmission power of the ground user, the RIS phase shift, and the trajectory of the UAV. Nevertheless, the proposed problem cannot be solved directly because of the coupled optimization variables and the non-convexity. Consequently, we tackle it by decomposing the original problem into three achievable sub-problems, in which formulated problem could be handled by using alternative optimization, the successive convex approximation, and semidefinite relaxation. Finally, we continuously optimize three variables and iterate over three sub-problems until the ASR converges to a stationary value. Simulation results show that the proposed scheme effectively boost the ASR compared with other baselines.

It is necessary for rescuers to localize a target trapped in a an unknown area resulting from various natural disasters or human warfare. The global navigation satellite systems and existing wireless and cellular infrastructures may have been partially or totally constrained and not available for localization in the target area. In this article, we propose a simple yet effective single-anchor mobile localization scheme, called TSAL as a potential solution in the case where traditional localization methods fail. By building three Cartesian coordinate systems and carrying out distance and/or steering-angle measurement with the off-the-shelf approaches while the target node is moving, utilizing just one of existing normally-functioning cellular Base Stations (BSs) as the only anchor or redeploying only one BS is enough to localize the target. In addition, TSAL also works with multiple anchor nodes and we propose a corresponding scheme based on TSAL, called TML, which can obtain more accurate localization. Theoretical analyses, extensive simulations and real-world experiments are conducted for evaluating the proposed schemes, with the effects of a set of parameter settings investigated, which shows the high availability and effectiveness of our schemes.

The quality of raw audio waveform generated by a vocoder could affect various audio generative tasks. In recent years, the dominance of source-filter vocoders was greatly challenged by neural vocoders as the latter presents far superior synthesized audio quality. Meanwhile, neural vocoders introduced unprecedented limitations including low runtime efficiency as well as unstable pitch especially in those without explicit periodic excitation input, while these have never been a problem in source-filter vocoders. We present in this paper a novel approach that takes the best from both parties. We start by an in-depth examination of every building block in WORLD – one of the best-performing source-filter vocoders based on plain signal processing algorithms, looking for ones that do not work well, and we replace them with small, lightweight and task-specific neural network models. We also rearranged the vocoding pipeline for a smoother collaboration between building blocks. Our objective and subjective evaluations demonstrate that our methods present competitive synthesized audio quality even when compared against neural vocoders at a much lower computational cost, while keeping spectral envelope acoustic feature, high pitch accuracy as in conventional source-filter vocoders.

The transmission performance of an reconfigurable intelligent surface (RIS)-aided device-to-device (D2D) communication network is fundamentally limited by the devices' energy. To address this challenge, in this paper, the joint radio resource allocation of D2D users (DUs) with piece-wise linear energy harvesting (EH) models and passive beamforming of the RIS is investigated to maximize the sum rate of DUs for an RIS-aided wireless-powered D2D communication underlaying a cellular network. Specifically, multiple wireless-powered DUs harvest radio-frequency energy from a hybrid access point (HAP) with the help of an RIS during the EH phase and achieve data transmission by using the harvested energy during information transmission phase. The optimization problem is formulated by jointly optimizing the transmit power of DUs, transmission time, the active beamforming vector of the HAP, and the passive beamforming matrix of the RIS. An alternating optimization-based algorithm is designed to solve the non-convex problem by using the variable substitution approach and the Lagrangian dual method. Simulation results have shown that our proposed algorithm provides a significant improvement in data rates over the existing algorithm without the RIS.

Abstract Clustering and layering are widely employed in large‐scale wireless sensor networks (WSNs) to alleviate data implosion, reduce transmission delay and improve energy efficiency. It is vital to conduct performance analysis in clustered WSNs for better defining and designing networks. Here, a general analytical framework based on a randomly spacial model is proposed to conduct inter‐cluster interference analysis and physical‐layer security analysis for clustered WSNs. It is assumed that two adjacent cluster heads exchange confidential massage with a passive eavesdropper and the non‐head nodes in clusters could be selected as cooperative jamming (CJ) nodes to disturb the eavesdropper. All mentioned nodes are randomly located in their specific areas. Under the above settings, three scenarios, namely interference, eavesdropping and CJ are considered, and a stochastic geometry tool based on kinematic measure is employed for analysis. Comparing to existing stochastic geometry methods, the proposed analytical framework can handle arbitrarily shaped, disjoint and tiered networks. The results obtained from extensive simulations have verified the rationality of the framework and demonstrated the impact of different parameters on the performance metrics of interest. The comparison with PPP also shows the advantages of this proposed model.

The secure exchange of messages between different communication devices is a major issue of Internet-of-Things (IoT) applications in future smart cities. Current security mechanisms focus on multiple antennas technology, such as spatial modulation (SM), but in space shift keying (SSK), there is still a space to explore. In this article, we propose a secrecy-enhancing SSK scheme for IoT applications by applying security technologies in the physical layer wherein the number of transmit antennas is arbitrary rather than the value of power of two. In this scheme, the security performance of the communication system is improved by using two technologies, namely, artificial noise (AN) and antenna selection. We assume that the application scenario of the SSK system is under the classic eavesdropping model. First, we design ANs according to the channel state information (CSI) to interrupt the eavesdropper and benefit the legitimate receiver via the appropriate cancellation technology. Second, the antenna selection method is designed based on the signal to leakage noise ratio (SLNR) to further boost the secrecy performance by expanding the mutual information difference between the main channel and the eavesdropping channel. Results from our simulations indicate that by the use of the proposed scheme, significant secrecy enhancing can be achieved in terms of bit error ratio (BER) and secrecy rate (SR) when compared with existing schemes. This achieved secrecy enhancing can benefit the suitable IoT communication applications in the smart city environment to avoid the leakage of data transmission.

Quadrature spatial modulation (QSM) is recently proposed to increase the spectral efficiency (SE) of SM, which extends the transmitted symbols into in-phase and quadrature domains. In this paper, we propose a generalized QSM (GQSM) scheme to further increase the SE of QSM by activating more than one transmit antenna in in-phase or quadrature domain. A low-complexity detection scheme for GQSM is provided to mitigate the detection burden of the optimal maximum-likelihood (ML) detection method. An upper bounded bit error rate is analyzed to discover the system performance of GQSM. Moreover, by collaborating with the non-orthogonal multiple access (NOMA) technique, we investigate the practical application of GQSM to cooperative vehicular networks and propose the cooperative GQSM with OMA (C-OMA-GQSM) and cooperative GQSM with NOMA (C-NOMA-GQSM) schemes. Computer simulation results verify the reliability of the proposed low-complexity detection as well as the theoretical analysis, and show that GQSM outperforms QSM in the entire SNR region. The superior BER performance of the proposed C-NOMA-GQSM scheme make it a promising modulation candidate for next generation vehicular networks.

In this study, the authors propose a generalisedswitching protocol (GSP) for increasing the flexibility of energy harvesting (EH) protocol and enhancing the security of amplify‐and‐forward (AF) multi‐antenna relaying system. The proposed GSP‐based relaying [generalised switching relaying (GSR)] system is established with target node assisted interference and EH technologies. In phase I, while the source transmits certain signal to the relay, the destination transmits an artificial noise to interfere the passive eavesdropper. In this phase, the relay harvests energy from the two nodes. In phase II, the relay node processes the two different received signals, which are from the source and destination, then AF them by utilising the harvested energy. The authors also derive a new analytical formula for the proposed protocol on ergodic secrecy capacity. The effect of the number of relay antennas N , the source transmitted power , the destination transmitted power and EH efficiency factors and on ergodic secrecy capacity are investigated. The simulation results show that as N , , , and increase, the ergodic secrecy capacity of GSR system increases accordingly. Moreover, the GSR protocol can provide higher ergodic secrecy capacity than both time switching relaying and powersplitting relaying protocols.

With the widespread use of Internet of Things (IoT), edge computing has recently emerged as a promising technology to tackle low-latency and security issues with personal IoT data. In this regard, many works have been concerned with computing resource allocation of the edge computing server, and some studies have conducted to the pricing schemes for resource allocation additionally. However, few works have attempted to address the comparison among various kinds of pricing schemes. In addition, some schemes have their limitations such as fairness issues on differentiated pricing schemes. To tackle these limitations, this article considered three dynamic pricing mechanisms for resource allocation of edge computing for the IoT environment with a comparative analysis: BID-proportional allocation mechanism (BID-PRAM), uniform pricing mechanism (UNI-PRIM), and fairness-seeking differentiated pricing mechanism (FAID-PRIM). BID-PRAM is newly proposed to overcome the limitation of the auction-based pricing scheme; UNI-PRIM is a basic uniform pricing scheme; FAID-PRIM is newly proposed to tackle the fairness issues of the differentiated pricing scheme. BID-PRAM is formulated as a noncooperative game. UNI-PIM and FAID-PRIM are formulated as a single-leader-multiple-followers Stackelberg game. In each mechanism, the Nash equilibrium (NE) or Stackelberg equilibrium (SE) solution is given with the proof of existence and uniqueness. Numerical results validate the proposed theorems and present a comparative analysis of three mechanisms. Through these analyses, the advantages and disadvantages of each model are identified, to give edge computing service providers guidance on various kinds of pricing schemes.

Recent advances in cooperative multiple-input-multiple-output (CMIMO) techniques have encouraged interest in the development of intelligent transportation systems (ITS). They have the potential for use in the infrastructure to vehicle (I2V) and infrastructure to infrastructure (I2I) communications in ITS networks where the energy consumption of wireless sensor nodes embedded on the road infrastructure is constraint. Therefore, how to reduce the energy consumption becomes a hot research topic . In this paper, applications of cooperative communications in ITS networks are proposed for reducing the total energy consumption . At first, the ITS model is established based on the cooperative multiple-input-multiple-output spatial modulation (CMIMO-SM). A detailed energy consumption analysis of the proposed scheme compared with the traditional single-input-single-output (SISO) based scheme is then presented. The comparison conducted between these communication schemes helps us select the optimal one for energy reduction in energy constrained ITS networks. Additionally, under the guidance of the proposed scheme we consider the multi-hop transmission scenario where the energy efficiency improvement is achieved by finding the optimal hop number with the equal hop-length scheme. As a result, we analyze the energy consumption in different situations, and discuss the requirements on the hop-length and hop number in ITS networks. It shows that the optimal results are dependent on the ITS scenarios and choosing the appropriate transmission scheme will provide a good energy consumption performance in ITS.