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  • Open Access

    ARTICLE

    Improved IChOA-Based Reinforcement Learning for Secrecy Rate Optimization in Smart Grid Communications

    Mehrdad Shoeibi1, Mohammad Mehdi Sharifi Nevisi2, Sarvenaz Sadat Khatami3, Diego Martín2,*, Sepehr Soltani4, Sina Aghakhani5

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2819-2843, 2024, DOI:10.32604/cmc.2024.056823 - 18 November 2024

    Abstract In the evolving landscape of the smart grid (SG), the integration of non-organic multiple access (NOMA) technology has emerged as a pivotal strategy for enhancing spectral efficiency and energy management. However, the open nature of wireless channels in SG raises significant concerns regarding the confidentiality of critical control messages, especially when broadcasted from a neighborhood gateway (NG) to smart meters (SMs). This paper introduces a novel approach based on reinforcement learning (RL) to fortify the performance of secrecy. Motivated by the need for efficient and effective training of the fully connected layers in the RL… More >

  • Open Access

    ARTICLE

    Performance Analysis of Curved Track G2T-FSO (Ground-to-Train Free Space Optical) Model under Various Weather Conditions

    Mohammed A. Alhartomi1,*, Mohammad F. L. Abdullah2, Wafi A. B. Mabrouk2, Mohammed S. M. Gismalla3, Ahmed Alzahmi1, Saeed Alzahrani1, Mohammad R. Altimania1, Mohammed S. Alsawat4

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2087-2105, 2024, DOI:10.32604/cmes.2024.055679 - 31 October 2024

    Abstract The demand for broadband data services on high-speed trains is rapidly growing as more people commute between their homes and workplaces. However, current radio frequency (RF) technology cannot adequately meet this demand. In order to address the bandwidth constraint, a technique known as free space optics (FSO) has been proposed. This paper presents a mathematical derivation and formulation of curve track G2T-FSO (Ground-to-train Free Space Optical) model, where the track radius characteristics is 2667 m, divergence angle track is 1.5° for train velocity at V = 250 km/h. Multiple transmitter configurations are proposed to maximize More >

  • Open Access

    ARTICLE

    Cyber Security within Smart Cities: A Comprehensive Study and a Novel Intrusion Detection-Based Approach

    Mehdi Houichi1,*, Faouzi Jaidi1,2, Adel Bouhoula3

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 393-441, 2024, DOI:10.32604/cmc.2024.054007 - 15 October 2024

    Abstract The expansion of smart cities, facilitated by digital communications, has resulted in an enhancement of the quality of life and satisfaction among residents. The Internet of Things (IoT) continually generates vast amounts of data, which is subsequently analyzed to offer services to residents. The growth and development of IoT have given rise to a new paradigm. A smart city possesses the ability to consistently monitor and utilize the physical environment, providing intelligent services such as energy, transportation, healthcare, and entertainment for both residents and visitors. Research on the security and privacy of smart cities is… More >

  • Open Access

    ARTICLE

    Physical Layer Security of 6G Vehicular Networks with UAV Systems: First Order Secrecy Metrics, Optimization, and Bounds

    Sagar Kavaiya1, Hiren Mewada2,*, Sagarkumar Patel3, Dharmendra Chauhan3, Faris A. Almalki4, Hana Mohammed Mujlid4

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3685-3711, 2024, DOI:10.32604/cmc.2024.053587 - 12 September 2024

    Abstract The mobility and connective capabilities of unmanned aerial vehicles (UAVs) are becoming more and more important in defense, commercial, and research domains. However, their open communication makes UAVs susceptible to undesirable passive attacks such as eavesdropping or jamming. Recently, the inefficiency of traditional cryptography-based techniques has led to the addition of Physical Layer Security (PLS). This study focuses on the advanced PLS method for passive eavesdropping in UAV-aided vehicular environments, proposing a solution to complement the conventional cryptography approach. Initially, we present a performance analysis of first-order secrecy metrics in 6G-enabled UAV systems, namely hybrid… More >

  • Open Access

    ARTICLE

    Secrecy Outage Probability Minimization in Wireless-Powered Communications Using an Improved Biogeography-Based Optimization-Inspired Recurrent Neural Network

    Mohammad Mehdi Sharifi Nevisi1, Elnaz Bashir2, Diego Martín3,*, Seyedkian Rezvanjou4, Farzaneh Shoushtari5, Ehsan Ghafourian2

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3971-3991, 2024, DOI:10.32604/cmc.2024.047875 - 26 March 2024

    Abstract This paper focuses on wireless-powered communication systems, which are increasingly relevant in the Internet of Things (IoT) due to their ability to extend the operational lifetime of devices with limited energy. The main contribution of the paper is a novel approach to minimize the secrecy outage probability (SOP) in these systems. Minimizing SOP is crucial for maintaining the confidentiality and integrity of data, especially in situations where the transmission of sensitive data is critical. Our proposed method harnesses the power of an improved biogeography-based optimization (IBBO) to effectively train a recurrent neural network (RNN). The… More >

  • Open Access

    ARTICLE

    Audio-Text Multimodal Speech Recognition via Dual-Tower Architecture for Mandarin Air Traffic Control Communications

    Shuting Ge1,2, Jin Ren2,3,*, Yihua Shi4, Yujun Zhang1, Shunzhi Yang2, Jinfeng Yang2

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3215-3245, 2024, DOI:10.32604/cmc.2023.046746 - 26 March 2024

    Abstract In air traffic control communications (ATCC), misunderstandings between pilots and controllers could result in fatal aviation accidents. Fortunately, advanced automatic speech recognition technology has emerged as a promising means of preventing miscommunications and enhancing aviation safety. However, most existing speech recognition methods merely incorporate external language models on the decoder side, leading to insufficient semantic alignment between speech and text modalities during the encoding phase. Furthermore, it is challenging to model acoustic context dependencies over long distances due to the longer speech sequences than text, especially for the extended ATCC data. To address these issues,… More >

  • Open Access

    ARTICLE

    A Deep Reinforcement Learning-Based Technique for Optimal Power Allocation in Multiple Access Communications

    Sepehr Soltani1, Ehsan Ghafourian2, Reza Salehi3, Diego Martín3,*, Milad Vahidi4

    Intelligent Automation & Soft Computing, Vol.39, No.1, pp. 93-108, 2024, DOI:10.32604/iasc.2024.042693 - 29 March 2024

    Abstract For many years, researchers have explored power allocation (PA) algorithms driven by models in wireless networks where multiple-user communications with interference are present. Nowadays, data-driven machine learning methods have become quite popular in analyzing wireless communication systems, which among them deep reinforcement learning (DRL) has a significant role in solving optimization issues under certain constraints. To this purpose, in this paper, we investigate the PA problem in a -user multiple access channels (MAC), where transmitters (e.g., mobile users) aim to send an independent message to a common receiver (e.g., base station) through wireless channels. To… More >

  • Open Access

    ARTICLE

    Generative Multi-Modal Mutual Enhancement Video Semantic Communications

    Yuanle Chen1, Haobo Wang1, Chunyu Liu1, Linyi Wang2, Jiaxin Liu1, Wei Wu1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2985-3009, 2024, DOI:10.32604/cmes.2023.046837 - 11 March 2024

    Abstract Recently, there have been significant advancements in the study of semantic communication in single-modal scenarios. However, the ability to process information in multi-modal environments remains limited. Inspired by the research and applications of natural language processing across different modalities, our goal is to accurately extract frame-level semantic information from videos and ultimately transmit high-quality videos. Specifically, we propose a deep learning-based Multi-Modal Mutual Enhancement Video Semantic Communication system, called M3E-VSC. Built upon a Vector Quantized Generative Adversarial Network (VQGAN), our system aims to leverage mutual enhancement among different modalities by using text as the main More >

  • Open Access

    ARTICLE

    New Antenna Array Beamforming Techniques Based on Hybrid Convolution/Genetic Algorithm for 5G and Beyond Communications

    Shimaa M. Amer1, Ashraf A. M. Khalaf2, Amr H. Hussein3,4, Salman A. Alqahtani5, Mostafa H. Dahshan6, Hossam M. Kassem3,4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2749-2767, 2024, DOI:10.32604/cmes.2023.029138 - 15 December 2023

    Abstract Side lobe level reduction (SLL) of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service (QOS) in recent and future wireless communication systems starting from 5G up to 7G. Furthermore, it improves the array gain and directivity, increasing the detection range and angular resolution of radar systems. This study proposes two highly efficient SLL reduction techniques. These techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm (GA) to develop the Conv/GA and DConv/GA, respectively. The convolution process determines the element’s… More >

  • Open Access

    ARTICLE

    Energy Efficiency Maximization in Mobile Edge Computing Networks via IRS assisted UAV Communications

    Ying Zhang1, Weiming Niu2, Supu Xiu1,3, Guangchen Mu3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1865-1884, 2024, DOI:10.32604/cmes.2023.030114 - 17 November 2023

    Abstract In this paper, we investigate the energy efficiency maximization for mobile edge computing (MEC) in intelligent reflecting surface (IRS) assisted unmanned aerial vehicle (UAV) communications. In particular, UAV can collect the computing tasks of the terrestrial users and transmit the results back to them after computing. We jointly optimize the users’ transmitted beamforming and uploading ratios, the phase shift matrix of IRS, and the UAV trajectory to improve the energy efficiency. The formulated optimization problem is highly non-convex and difficult to be solved directly. Therefore, we decompose the original problem into three sub-problems. We first More >

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