Communication Systems Research Articles

An innovative conditional self-attention generative adversarial network with fennec fox optimization approach for resource allocation in cognitive radio wireless communication systems

An innovative conditional self-attention generative adversarial network with fennec fox optimization approach for resource allocation in cognitive radio wireless communication systems

Enhancing millimeter-wave communication: a tropical perspective on raindrop size distribution and signal attenuation

This study tackles rain attenuation in millimeter-wave (mm-wave) communication, a critical concern for the advancement of 5G wireless technology. It examines the variability of raindrop size distribution (DSD) and its impact on specific attenuation, with a focus on tropical environments such as Malaysia. Using the Joss-Waldvogel disdrometer, this study collected and analyzed extensive DSD data over three years, revealing that the highest DSD concentrations do not necessarily result in the greatest specific attenuation. This study adopted a machine learning approach, specifically supervised learning with linear regression, to enhance the accuracy of attenuation prediction models. A new set of coefficients for the power-law model of specific attenuation was derived and benchmarked against the ITU-R P.838-3 standard and similar studies in comparable climates. The findings emphasize the importance of developing region-specific models that consider local meteorological variations, potentially offering significant improvements to the reliability and design of mm-wave communication systems in the future.

Online Sale Trends and Perspectives of Development in Georgia: A Pathway to Sustainable Business Growth

E-commerce is important for companies in order to gain competitive advantage in the market. It is solution for businesses to manage their operations and online sales. It enables merchants to set up an online store, lists services and products, and also accepts payments from consumer. It’s user-friendly interface, where customers can purchase products, track orders and etc. Accordingly, the given paper presents theoretical and practical aspects of online sales and its place in business development; the current situation and perspectives for the development of online sales are analyzed; problems related to online sales in Georgian reality are highlighted; it is noted that, when the competition in the market is increasing day by day, in order to maintain and further strengthen its position in the market, companies should focus more on modern online sales strategies, which together with other general marketing strategies are the basis for further development. Companies must realize that for success they have to implement modern online communications systems in practice, in order to have constant communication with customers. At the end of the paper, appropriate conclusions are given, the consideration of which will contribute to the fact that companies will use modern approaches in the field of online sales which will raise the image of the company, gain trust of customers and obtain competitive advantage. Key words: Internet-technologies; Online Marketing; E-commerce; Online Sales; Online stores; Virtual stores, traditional stores

Controlled Wireless Channel using Multi-Antenna Multi-IRS Assisted Communication System: A Comprehensive Performance Analysis

Controlled Wireless Channel using Multi-Antenna Multi-IRS Assisted Communication System: A Comprehensive Performance Analysis

Gut Microbiome-Host microRNA Interactions in Cancer Development and Immune Regulation: A Case of Colorectal and Breast Cancer

Breast and colorectal cancers represent primary malignancies that researchers worldwide analyze for genetic along with environmental risk elements to build therapeutic methods for better cancer outcomes. The most prevalent cancer in women is breast cancer along with colorectal cancer ranking second and third respectively among females. Adults across the globe most often experience these cancer types yet the present scenario shows rising incidence rates among younger patients. These early-onset tumors often start in the advanced stages of their aggressive type and produce a poor clinical outlook for patients. Past research initially concentrated on identifying genes which might help explain cancer origins but this approach changed in recent years. Scientific research has demonstrated that genetics and epigenetics together with environmental elements strongly affect cancer predisposition. Due to recent paradigm shifts in scientific inquiry researchers performed diverse investigations to analyze host microRNA response patterns and validated microbiota-gut communication systems which significantly influenced disease occurrence and state. These factors directly affect the disease's final results. Immunosuppression stands as a major worrisome consequence among all identified unfavorable effects of this disease because at present such patients remain susceptible to numerous infections. Recent scientific research found microbiome along with microRNA to substantially affect immunosuppression. The review tracked host microRNA activity alongside gut microbiome changes during disease development to determine their influence on immunosuppression in patients. Understanding the microRNA and microbiome interaction mechanisms with disease presentation effects on immune function would enable future therapeutic development opportunities targeting host microRNA and patient gut microbiome functions. The combination of inhibitory-miRNA therapies with miRNA mimic-based therapeutics and immune checkpoint blockade therapies and bacteria-assisted tumor-targeted therapies helps manage cancer. This study simultaneously investigated noninvasive biomarkers that could help with both cancer diagnosis and treatment plans and prognostic assessment.

A human digital twin approach for fatigue-aware task planning in human-robot collaborative assembly

Human-robot collaboration (HRC) has emerged as a pivotal paradigm in manufacturing, integrating the strengths of both human and robot capabilities. Neglecting human physical fatigue may adversely affect worker health and, in extreme cases, may lead to musculoskeletal disorders. However, human fatigue has rarely been considered for decision-making in HRC manufacturing systems. Integrating adaptive decision-making to optimise human fatigue in HRC manufacturing systems is crucial. Nonetheless, real-time perception and estimation of human fatigue and decision-making informed by human fatigue face considerable challenges. To address these challenges, this paper introduces a human digital twin method, a bidirectional communication system for physical fatigue assessment and reduction in human-robot collaborative assembly tasks. The methodology encompasses an IK-BiLSTM-AM-based surrogate model, which consists of inverse kinematics analysis (IK), bidirectional long short-term memory (BiLSTM), and attention mechanism (AM), for real-time muscle force estimation integrated with a muscle force-fatigue model for muscle fatigue assessment. An And-Or graph and optimisation model-based HRC task planner is also developed to alleviate physical fatigue via task allocation. The efficacy of this approach has been validated through proof-of-concept assembly experiments involving multiple subjects. The results show that the IK-BiLSTM-AM model achieves a minimum of 8% greater accuracy in muscle force estimation than the baseline methods. The 12-subject assessment results indicate that the task planner effectively reduces the physical fatigue of workers while performing collaborative assembly tasks.

Frequency domain oversampled OFDM with Index modulation for SFBC-based MIMO system in high-speed wireless communications

Frequency domain oversampled OFDM with Index modulation for SFBC-based MIMO system in high-speed wireless communications

Decentralized Framework for Securing Smart Grids Using Blockchain and Machine Learning

Abstract: The transition to smart grids has revolutionized energy distribution, enabling more efficient and flexible power management through advanced communication and control systems. However, this interconnected structure makes smart grids vulnerable to cyberattacks, such as False Data Injection Attacks (FDIA), Distributed Denial of Service (DDoS) attacks, and data manipulation. These threats undermine the stability and reliability of the grid, and existing centralized security frameworks are often ill-equipped to address them due to their susceptibility to single points of failure and limited scalability. To overcome these challenges, this paper introduces a decentralized security framework that combines blockchain technology with machine learning (ML). The framework leverages blockchain to provide a transparent, immutable, and decentralized ledger, employing consensus mechanisms like Practical Byzantine Fault Tolerance (PBFT) or Proof of Authority (PoA) to ensure secure data validation. Alongside this, ML models, including Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN), are used to detect anomalies in time-series data, such as FDIA, with high precision. Smart contracts embedded in the blockchain enable automated, real-time responses to threats, such as isolating compromised nodes or rerouting energy flows to maintain grid stability. Through simulations replicating real-world cyberattacks, the proposed framework demonstrated over 95% detection accuracy, a 30% reduction in response times, and enhanced computational efficiency with lower energy consumption. These results affirm the effectiveness of the framework as a scalable and resilient solution for modern smart grid security.

Optimized High Speed VLSI Implementation of the RSA Algorithm

Abstract: RSA, one of the most widely adopted public-key cryptographic algorithms, ensures secure communication by leveraging the mathematical properties of modular exponentiation and large prime factorization. However, its computational complexity and high resource demands pose significant challenges for real-time and high-speed applications. This paper addresses these challenges by proposing an optimized Very-Large-Scale Integration (VLSI) design for RSA encryption and decryption, focusing on accelerating the modular exponentiation process, which is the core of RSA computations. The design incorporates Montgomery Modular Multiplication to eliminate time-intensive division operations, enabling efficient computation in the modular arithmetic domain. It further integrates techniques such as pipelining, parallel processing, and carry-save adders to reduce critical path delays and enhance throughput. Modular exponentiation is implemented using a scalable iterative approach with the square-and-multiply method, optimized for hardware efficiency. Hardware prototypes were synthesized and tested using FPGA and ASIC platforms, demonstrating superior performance in terms of speed, area, and power consumption. The proposed architecture achieves high-speed operation while maintaining security and scalability, making it suitable for real-time cryptographic applications such as secure communication, digital signatures, and authentication systems. Comparative analysis with existing implementations highlights significant improvements, establishing the proposed design as a viable solution for next-generation secure hardware accelerators.

Channel Prediction Technology Based on Adaptive Reinforced Reservoir Learning Network for Orthogonal Frequency Division Multiplexing Wireless Communication Systems

Channel Prediction Technology Based on Adaptive Reinforced Reservoir Learning Network for Orthogonal Frequency Division Multiplexing Wireless Communication Systems

Massively parallel Hong-Ou-Mandel interference based on independent soliton microcombs.

Hong-Ou-Mandel (HOM) interference is the foundation of quantum optics to test the degree of indistinguishability of two incoming photons, playing a key role in quantum communication, sensing, and photonic quantum computing. Realizing high-visibility HOM interference with massively parallel optical channels is challenging due to the lack of available natural optical references for aligning independent arrayed laser pairs. Here, we demonstrate 50 parallel comb-teeth pairs of continuous-wave weak coherent photons HOM interference using two independently frequency post-aligned soliton microcombs (SMCs), achieving an average fringe visibility over 46%. The frequencies of all comb-teeth pairs are long-term aligned by developing two sets of fully frequency-stabilized SMCs with independent reference and adjusting free spectral range beyond 100 kilohertz through perturbations in soliton state. The verification experiment proves the feasibility of constructing massively quantum information channels by co-opting classical wavelength division multiplexing optical communications, which paves the way for practical large-scale quantum communication systems.

Ultra-narrow size slotted sleeve multi-band antenna for mining wireless repeaters

ABSTRACT The integration of multi-standard and multi-band wireless communication system will be the development trend of mine communication. The mine wireless repeater is an important part of the mine communication system. However, the antenna suitable for wireless repeaters is a vertical whip antenna, which greatly limits the size of the antenna in the horizontal direction. In this paper, an ultra-narrow size slotted sleeve antenna is proposed for the RF front end of wireless repeaters for underground mining. The antenna design process can be divided into three steps. First, a flag shaped slot is cut in the rectangular sleeve to increase the impedance bandwidth of the antenna. Second, the reverse branch is loaded on the top of the sleeve, which ingeniously increases the resonant path of the antenna. Moreover, a T-shaped slot is etched on the transmission line, which further improves the overall performance of the antenna. The electrical size of the antenna with this unique structural design is only 0.41λ × 0.048λ, which is much smaller than the lateral size of similar antennas. The simulation and measurement results of the proposed antenna are in good agreement, and the working bands include 0.79–0.82 GHz, 1.42–1.47 GHz, 2.39–2.59 GHz, 2.63–2.91 GHz, and 5.10–5.75 GHz.

240 Gbps SI-FMF/FSO communication system based on LP modes and PV code with the impact of foggy weather in Alexandria and Setif

This paper presents a novel, to the best of our knowledge, high-speed optical communication system achieving a 240 Gbps transmission capacity by integrating step-index few-mode fiber (SI-MMF) and free space optics (FSO). Knowing that Hermite-Gaussian modes (HGMs) are eigenmodes of a free space medium and the linearly polarized modes (LPMs) are eigenmodes of step-index few-mode fiber (SI-FMF), and by considering the similarity between HGM ( and ) and LPM ( and ), respectively, the system employs dual-polarization (DP) and linearly polarized (LP) modes (, , and ), combined with optical code division multiple access (OCDMA) using permutation vector (PV) codes. Each polarization state carries data from three LP modes, with each mode supporting four OCDMA channels, each assigned a unique PV code. The system’s performance is evaluated under varying fog conditions using key metrics such as quality-factor (Q-factor), bit error rate (BER), and eye diagrams, which provide a comprehensive assessment of signal strength and quality. Real-world applicability is assessed using meteorological data from two African cities, Alexandria, Egypt, and Setif, Algeria. System performance is characterized using the Q-factor, bit error rate (BER), and eye diagrams. The results show that, in Alexandria, successful transmission is achieved over 1.41 km. In Setif, the transmission distance is reduced to 1.31 km due to slightly higher atmospheric attenuation. These ranges are observed at a BER below HG00 and a Q-factor exceeding 3.10. Consequently, these findings confirm the viability of the proposed system for high-capacity optical communication in challenging weather conditions, making it suitable for future 6G networks.

Real Time Anomaly Detection and Intrusion Detection for Safeguarding Intra-Vehicle Communication Powered by AI

This study addresses cyber-attacks in Electric Vehicles (EVs) and proposes an intelligent, secure framework to protect both in-vehicle and vehicle-to-vehicle communication systems. The proposed model uses an improved support vector machine (SVM) for anomaly and intrusion detection based on the Controller Area Network (CAN) protocol a critical component in vehicle communication. To further enhance detection speed and accuracy a new optimization algorithm the Social Spider Optimization (SSO) is introduced for reinforcing the offline training process. Simulation results on real-world datasets demonstrate the model's high performance, reliability and ability to defend against denial-of-service (DoS) attacks in EVs.

High‐Performance and Ultrafast Single Germanium Nanowire Photodetectors

AbstractSemiconductor nanowire‐based photodetectors with high sensitivity and fast photoresponse in the near‐infrared wavelength range are crucial for applications in light‐wave communication switches, as well as environmental and atmospheric sensing. However, to advance this field, it is essential to develop innovative fabrication techniques that improve device performance. Here, the fabrication of an axial p–n junction along single germanium nanowires (Ge NWs) and their photoresponse characterization at near‐infrared wavelengths are reported. The resulting devices exhibit rectifying current–voltage characteristics with a high rectification ratio in dark conditions and operate with high sensitivity at zero bias under illumination. A high responsivity of 1.72 AW−1, a low noise‐equivalent power of 5.68 × 10−11 , and a high‐frequency response with a 3dB cut‐off frequency of 2.85 GHz are determined under 850 nm laser illumination at reverse bias. The high sensitivity of the Ge NW‐based photodetectors is ascribed to the radial built‐in electric field, which increases the carrier lifetime. In addition, the small size of the Ge NWs results in very small capacitance, leading to very fast response. These results have significant potential for advancing high‐speed and low‐power photodetectors in next‐generation optical communication systems and integrated optoelectronic devices.

Performance analysis of the photonic crystal–based X-OR gate for the terahertz applications

Abstract A key component of high-speed switching networks is an optical logic gate. This study presents the design and analysis of an all-optical XOR gate based on a two-dimensional photonic crystal (2D PC) structure, aiming to enhance high-speed switching in optical networks. The XOR gate, with two input and one output waveguide, is constructed on a hexagonal lattice, optimized for operation at a wavelength of 1,550 nm. The design is evaluated using the Finite Difference Time Domain (FDTD) approach, which simulates the optical performance of the structure. Key performance metrics, including the bit rate, contrast ratio, and delay time, are computed, showing that the proposed logic gate achieves a high contrast ratio of 30.35 dB and a minimal delay time of 0.4 ps. The results confirm the potential of this all-optical XOR gate for integration into high-speed optical circuits, offering low power consumption and high efficiency. This work demonstrates the feasibility of utilizing photonic crystal structures for high-performance optical logic gates in future communication systems. The simplicity of fabrication in a two-dimensional photonic crystal (2D-PC)-based all-optical logic gate can often be attributed to its simple design.

High-precision 1.5 µm band tunable single-frequency fluoro-sulfo-phosphate fiber laser based on a self-injection locking scheme

In this paper, a high-precision 1.5 µm band tunable single-frequency Er3+/Yb3+ co-doped fluoro-sulfo-phosphate (EYFSP) fiber laser based on a self-injection locking scheme is experimentally demonstrated. A self-developed 4 cm long EYFSP fiber with a high gain coefficient (3.2–4.7 dB/cm) at the C-band serves as the gain medium for laser output. The single longitudinal mode (SLM) operation is realized via a 15 cm long commercial unpumped gain fiber and a self-injection locking scheme, while flexible wavelength tuning is controlled by a fiber Fabry–Perot tunable filter (FFP-TF). The laser wavelength is tuned from 1528.08 to 1555.55 nm, with a tuning precision of up to 10–18 pm and a tuning speed of 30 nm/s. Throughout the entire tuning range of 27.47 nm, the measured laser linewidth is less than 1.3 kHz, the relative intensity noise remains below −140dB/Hz at frequencies above 3 MHz, and the power fluctuation is as low as 1% over a measurement period of 2 h. These results demonstrate that the high-precision 1.5 µm band tunable single-frequency EYFSP fiber laser is a promising candidate for future coherent optical communication systems and optical fiber sensing.

A Hybrid Heuristic‐Aided Algorithm of Serial Cascaded Autoencoder and ALSTM for Channel Estimation in Millimeter‐Wave Massive MIMO Communication System

A Hybrid Heuristic‐Aided Algorithm of Serial Cascaded Autoencoder and ALSTM for Channel Estimation in Millimeter‐Wave Massive MIMO Communication System

A Comprehensive Review of Quality of Aquaculture Services in Integrated Multi-Trophic Systems

The concept of Quality of Aquaculture Services (QoAS) is inspired by the Quality of Service (QoS) principle, originally developed in the field of networks and telecommunications, where it refers to the ability to guarantee the quality, availability, and priority of service in a communications system. Adapted to the aquaculture context, QoAS is fundamental to maximising the benefits of Integrated Multi-Trophic Aquaculture (IMTA). IMTA has emerged as a sustainable approach to meet the growing global demand for aquatic food products by combining species from different trophic levels in a single system, optimising resource use, improving environmental performance, and diversifying production. However, ensuring QoAS in these complex systems requires the implementation of advanced technologies to monitor, manage, and optimise every aspect of the aquaculture process. This article presents a comprehensive review of technologies applied at IMTA, focusing on IoT-based monitoring systems, resource management algorithms, water recirculation technologies, intelligent automation, biosecurity, and data management platforms. Our review finds that IoT and automation-based solutions significantly enhance real-time monitoring, increasing operational efficiency and environmental sustainability. Key challenges identified include integration complexity, high costs, and technical expertise requirements, but the ongoing development of modular, user-friendly solutions indicates a promising trajectory. This review highlights the transformative role of technological innovation in IMTA, providing a foundation for future research and advancements in QoAS management in aquaculture.

Barabási–Albert-Based Network Growth Model to Sustainable Urban Planning

Urban planning and development require methodologies to address the challenges of managing urban growth. This study uses Vladivostok as a case study to explore urban evolution and apply predictive models for socio-economic development. By analyzing the life cycle of the city and breaking down its growth processes into key components, specific patterns and strategies tailored to Vladivostok’s development are identified. The Barabási–Albert (BA) network growth model is used to study the temporal dynamics of the city’s urban network, enabling forecasts and optimization of its infrastructure, communication systems, and social environment. The approach shown in this study can be adapted to other cities, providing a framework for analyzing urban changes and supporting the development of strategies for sustainable growth and urban management.