IET Communications最新文献

Reconfigurable intelligent surface (RIS) is an emerging technology that can enhance service coverage and spectral efficiency in sixth-generation wireless networks. In contrast, relays are a traditional technique for achieving coverage extension. To explore potential benefits, we investigate three probable RIS-relay cascaded scenarios over Nakagami-$�m$ fading channels, where the full-duplex relay is utilized for ensuring spectral efficiency. To evaluate the performance across different scenarios, we first derive their closed-form expressions for the outage probability. Next, we determine the respective diversity order using asymptotic approximations in the high signal-to-noise-ratio regime. Finally, we present the system throughput in delay-limited transmission. Simulation results validate our analysis and demonstrate significant performance differences among various cascaded configurations, with the multi-RIS-assisted relay scenario achieving the best performance. Furthermore, the considered RIS-decode-and-forward relay schemes outperform the corresponding RIS-amplify-and-forward relay schemes in the low-SNR regime.

In this paper, we investigate an unmanned aerial vehicle (UAV) enabled secure multicast communication system, where a UAV serves multiple legitimate ground users in the presence of multiple coordinated eavesdroppers. Taking into account the inherent jittering characteristics of UAVs caused by the airflow, we aim to maximise the worst-case secrecy energy efficiency (SEE) under a constrained UAV transmission power budget. The formulated optimization problem is inherently non-convex and challenging to solve due to the combined effects of jittering uncertainties and the max–min fractional structure of the SEE metric. To address these challenges, we first simplify the original SEE maximization problem by introducing auxiliary variables. Next, considering the impact of jittering on the antenna array response, we develop a novel second-order Taylor series expansion-based approach to approximate beamforming gains as quadratic functions of the angle-of-departure errors, which can be subsequently transformed into deterministic convex constraints by using S-Procedure. Based on these theoretical results, we design an iterative algorithm that combines the penalty function method with the successive convex approximation to efficiently obtain a suboptimal solution. Finally, the simulation results demonstrate the effectiveness and superiority of the proposed scheme compared to several benchmark schemes, highlighting its potential for practical implementation in UAV-enabled secure multicast communication systems.

The multi-mode heterogeneous network combines the advantages of high-speed power line communication (HPLC) and high radio frequency (HRF), ensuring service quality and meeting the requirements for data transmission delay and reliability even when devices are flexibly deployed. Queuing delay and privacy entropy are important metrics for managing multi-mode heterogeneous internet of things (IoT) networks, which require collaborative optimization of the transmission phase (server selection and sub-channel allocation) and the computing phase (computing resource allocation) to ensure low latency and high privacy entropy. However, existing communication-computing collaborative optimization methods face issues such as low privacy security of electricity-carbon service data, high difficulty in solving the joint optimization problem, and resource competition. Therefore, this paper proposes a privacy preservation-driven communication-computing collaboration method for the management of multi-mode heterogeneous IoT networks. Firstly, the architecture for the management of multi-mode heterogeneous IoT networks is constructed and a privacy entropy model for electricity-carbon computing service data is established to measure the privacy security performance of the network management. Secondly, a joint optimization problem of queuing delay and privacy entropy under long-term privacy entropy constraints are constructed and the long-term privacy entropy constraints from short-term decisions is decoupled based on Lyapunov optimization. Finally, a joint optimization algorithm for server selection and multi-mode sub-channel allocation driven by privacy protection is proposed. This algorithm reduces the three-dimensional matching optimization problem among different devices, servers, and channels, and uses auction matching to solve the conflict of resource block selection, further optimizing the computing resource allocation of edge servers based on the Karush–Kuhn–Tucker (KKT) conditions. Simulation results show that the proposed algorithm effectively reduces queuing delay and improves privacy security of data transmission.

To eliminate the error floor of filter bank multicarrier with quadrature amplitude modulation (FBMC/QAM) in multipath fading channels, a novel cyclic prefix–based FBMC/QAM (CP-FBMC/QAM) scheme is proposed in this paper. The proposed CP-FBMC/QAM scheme only requires simple single-tap channel equalization to compensate for the influence of multipath channels. Moreover, we formulate a prototype filter optimization problem by minimising the interference powers subject to the spectrum localization constraints and derive prototype filters with good spectrum confinement for CP-FBMC/QAM. The proposed prototype filters can eliminate the impact of CP insertion on the spectrum confinement. Simulation results confirm the effectiveness of CP-FBMC/QAM in terms of spectrum confinement and bit error rate performance.

Locally caching at base stations (BSs) can increase the network capacity as well as reduce the backhaul burden. However, it iremains an open problem whether it could increase energy efficiency (EE) for the future sixth-generation (6G) network when the offloading link is in a deep fading condition. In order to analyse this problem, we attempt to analyse the energy efficiency of cache-enabled wireless communication system assisted by reconfigurable intelligent surfaces (RIS), which is a new paradigm to increase EE. First, by considering the central limit theorem and Jensen's inequality, we obtain the approximated expression for EE when the number of RIS reflecting elements is very large. Secondly, due to the adoption of the RIS-User/BS random association and a new BS-RIS-User wireless link, we analyse the performance between EE and the number of RIS reflecting elements under some condition. Finally, it is shown by full simulation that it is valid of our analysis, meanwhile, we gain the optimal cache capacity and the optimal transmission power of BS to maximize EE. Moreover, we show that the help of RIS can improve EE when the system is noise-limited due to RIS can improve the signal power and has very low transmit power, but EE decreases in an interference-limited system. Furthermore, we obtain the optimal number of BSs at the minimum EE in interference-limited system, but EE decreases as the number of BS increases when the system is noise-limited.

This paper introduces a novel, dual-band, compact 1:4 feed network employing a parallel power divider architecture designed to operate at 0.915 and 2.44 GHz, covering both industrial, scientific, and medical and ultra high frequency bands. The design leverages the non-linear phase characteristics of composite right/left-handed transmission lines to achieve dual-band functionality with high precision. Simulation results confirm the efficacy of the proposed network, which delivers quadrature-phase outputs with a 90° phase shift and uniform power distribution across all output ports, facilitating wideband circular polarisation in array antenna applications. Compared to traditional series power dividers, the parallel power divider offers significant advantages in terms of fabrication simplicity, reduced size, and lower manufacturing costs. The design avoids the use of non-radiating composite right/left-handed transmission lines and addresses impedance-matching challenges through the implementation of only three resistors, effectively isolating the output ports. The proposed architecture is highly scalable and can be easily adapted to various output port configurations, frequencies, and power division ratios, offering broad flexibility for a wide range of microwave applications.

Wireless sensor networks (WSNs) is a wireless system including the set of distributed sensor nodes used for physical or environmental observation. A network energy expenditure is considered as a significant concern because of battery restricted sensors of the WSN. Clustering and multi hop routing are considered as effective approaches to enhance the network lifecycle and communication. Achieving the anticipated objective of reducing the energy expenditure, thereby increasing the network lifecycle, is considered as an optimisation issue. In recent times, a nature inspired meta-heuristic approaches are extensively utilised for solving the different optimisation issues. In this context, this research aims to accomplish the objective by proposing the multiobjective-perturbed learning and mutation strategy based artificial rabbits optimisation namely M-PMARO for an optimum cluster head (CH) selection and route discovery. The proposed M-PMARO incorporates an experience based perturbed learning (EPL) and mutation strategy to identify the capable regions over the search space for enhancing the exploration and avoiding the local optima issue. To formulate the multiobjective, the residual energy, average intracluster distance, average base station (BS) distance, CH balancing factor (CHBF) and node centrality are incorporated for optimum CH discovery while the residual energy and average BS distance are considered for multi hop routing. The M-PMARO is analysed based on alive nodes, dead nodes, energy expenditure, throughput and data received in BS and network lifecycle. The viability of M-PMARO is validated by comparing it with existing approaches such as fitness based glowworm swarm with fruitfly algorithm (FGF), energy balanced particle swarm optimisation (EBPSO), improved bat optimisation algorithm (IBOA), graph neural network (GNN) and fuzzy logic and particle swarm optimisation (PSO) based clustering routing protocol namely PFCRE. The alive node count of M-PMARO is 100 for 1200 rounds, which is higher than the EBPSO.

This study proposed a complex fraud detection framework called CRAFIC (complex relationship analysis for fraud identification and cost management), which combines deep learning and graph neural networks to address complex fraud behaviours such as multi account collaborative fraud. The study used the DataCo Global supply chain dataset and the IEEE-CIS fraud detection dataset to extract order features using convolutional neural networks and long short term memory networks, and analysed the relationships between orders using graph attention networks to reveal complex fraud patterns. The results show that the CRAFIC framework performs well in both single order and collaborative fraud detection tasks. In single order fraud detection, the accuracy of the CRAFIC framework increased from the initial 45.21% to 93.75%, and the loss value decreased from 1.19 to 0.14, significantly better than other models. In collaborative fraud detection, the accuracy of the CRAFIC framework reached 90.3%, once again surpassing other models. These results validate the advantages of the CRAFIC framework in multimodal data fusion and complex relationship modelling. The CRAFIC framework reveals complex fraud patterns, optimizes internal controls and audit processes, enhances data security measures, prevents system vulnerabilities from being exploited, and enhances market reputation and customer trust.

The development of reconfigurable intelligent surface (RIS) makes direction-of-arrival (DOA) estimation possible for single-antenna receivers. However, non-ideal situations such as spectral aliasing occur when facing communication signals using orthogonal frequency division multiplexing modulation. This paper proposes a RIS-based single-channel DOA estimation method for communication signals. Specifically, by extending the time intervals to dynamically reduce the RIS state change rate, a real-time DOA estimation is achieved while mitigating the impact of non-ideal spectral shifts on communication. Then, based on the compressed sensing and mutual incoherence property, the method exploits the sparse property of the signal in space to reduce the estimation time while improving the estimation accuracy. Simulation results show an $��86�\%�$ reduction in computation time for the proposed method compared to the traditional CVX tool. Additionally, the estimation accuracy is as low as $��0.02�deg�$. To verify the practicality and robustness, we develop a prototype system and conduct extensive experiments. The results are consistent with our theoretical analysis, and the method proposed in this paper can realize single-path DOA estimation with an accuracy of less than $��0.1�deg�$ within $��0.4276��s�$. More excitingly, the presented experimental platform achieves DOA estimation for two coherent paths.

Satellite communications have emerged as a promising extension of terrestrial networks in future 6G network research due to their extensive coverage in remote areas and their ability to support the increasing traffic rate and heterogeneous networks. Like other wireless communication technologies, satellite signals are transmitted in a shared medium, making them vulnerable to attacks such as eavesdropping, jamming, and spoofing. A good candidate to overcome these issues is physical layer security (PLS), which utilizes physical layer characteristics to provide security, mainly due to its suitability for resource-limited devices such as satellites and IoT devices. This paper provides a comprehensive and up-to-date review of PLS solutions to secure satellite communication. Main satellite applications are classified into five domains: satellite-terrestrial, satellite-based IoT, satellite navigation systems, FSO-based, and inter-satellite. In each domain, how PLS can improve the overall security of the system, preserve desirable security properties, and resist widespread attacks are discussed and investigated. Finally, some gaps in the related literature are highlight and open research problems, including uplink secrecy techniques, smart threat models, authentication and integrity techniques, PLS for inter-satellite links, and machine learning-based PLS, are discussed.