Optimal Beamforming for Covert Communication in MIMO Relay Systems

Transactions on Emerging Telecommunications Technologies, Journal Year: 2025, Volume and Issue: 36(2)

Published: Feb. 1, 2025

ABSTRACT This paper investigates the optimal beamforming design for covert communication in a multiple‐input multiple‐output (MIMO) relay system consisting of source, destination, and warden. For both scenarios when each transmitting node knows perfect or partial warden's channel state information (CSI), we first develop theoretical models to depict inherent relationship between matrices at source/relay end‐to‐end performance regard minimum detection error probability capacity. Based on these models, then formulate capacity maximization under CSI as linear non‐convex (LNC) non‐linear (NLNC) optimization problems, respectively. We apply Lagrangian Hadamard inequality methods solve LNC problem determine closed‐form expressions source/relay, based which stochastic gradient descent algorithm is developed evaluate maximum complicated NLNC problem, propose an efficient search S‐procedure lemma interior point identify reach Finally, provide extensive numerical results illustrate enhancement from adopting MIMO systems.

Language: Английский

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Intelligent multipath congestion control algorithm based on subflow coupling perception

Cluster Computing, Journal Year: 2025, Volume and Issue: 28(4)

Published: Feb. 25, 2025

Language: Английский

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Adversarial Sample Generation Based on Model Simulation Analysis in Intrusion Detection Systems

Electronics, Journal Year: 2025, Volume and Issue: 14(5), P. 870 - 870

Published: Feb. 22, 2025

The explosive development of artificial intelligence technology is profoundly affecting the strategic landscape cyberspace security, demonstrating enormous potential in field intrusion detection. Recent research has found that machine learning models have serious vulnerabilities, and adversarial samples derived from this vulnerability can significantly reduce accuracy model detection by adding slight perturbations to original samples. In our article, we propose a novel method called sample generation based on simulation quickly generates short period time improves model’s generalization robustness after training. Extensive experiments CICIDS-2017 dataset demonstrated consistently outperforms other current methods.

Language: Английский

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Development of a Genetic Algorithm for Optimal Response Time Based on Full Scheduling Model of Electric Vehicle

Transactions on Emerging Telecommunications Technologies, Journal Year: 2025, Volume and Issue: 36(5)

Published: May 1, 2025

ABSTRACT Genetic algorithms (GAs) are frequently used in the design of electric vehicles to optimize various parameters, including battery capacity, motor size, and vehicle weight since they offer a powerful tool for improving their performance. In this paper, we focused our interest on development GA context optimizing response time based full scheduling model applied modern Society Automotive Engineers (SAE) Benchmark. The framework is set many nodes connected through Real‐Time protocol FlexRay middleware Data Distribution Service (DDS). implemented find optimal parameters that minimize required static method SAE Benchmark application. This approach allows one take advantage network high speed profit from DDS Quality‐of‐Service (QoS) management automotive electrical systems. Performance evaluations will be conducted prove efficiency, reliability, robustness proposed framework, comparison with other discussed.

Language: Английский

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Optimal Capacitance Design for IRS Aided Wireless Power Transfer for Sustainable IoT Communication

Transactions on Emerging Telecommunications Technologies, Journal Year: 2024, Volume and Issue: 35(11)

Published: Oct. 30, 2024

ABSTRACT Intelligent reflecting surface (IRS) is a cutting‐edge technique that can significantly improve wireless propagation. It efficiently utilize power transfer to enable sustainable Internet‐of‐Things (IoT) transmission by reconfiguring the incident signal from active transmitter. However, flexibility of capacitance tuning in IRS system, which controls underlying reflections, often overlooked. The effective design system provide new degree freedom IoT communication additional performance gain received power. To achieve this, novel circuital optimization model proposed this work. incorporates various electrical parameters meta‐surface unit cell for improved IoT‐enabled communication. provides an optimal as function phase shift (PS), controlled IRS, frequency, and other parameters. This then used define convexity problem proved, global obtained maximization. Our simulations show outperforms existing constructive interference‐based PS method, first calculated. Finally, analytical results are numerically validated with several insights.

Language: Английский

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An Automated Sparse Channel Estimation Framework for MU‐MIMO‐OFDM System With Adaptive Extreme Learning and Heuristic Mechanism

Transactions on Emerging Telecommunications Technologies, Journal Year: 2024, Volume and Issue: 35(11)

Published: Nov. 1, 2024

ABSTRACT Compressed sensing is used for channel estimation in Multiple Input Output‐Orthogonal Frequency Division Multiplexing (MIMO‐OFDM) systems, but large‐scale networks face challenges regarding the antenna elements and spatial non‐stationarities. To enhance spectral efficiency Multi User‐MIMO (MU‐MIMO) essential signals are collected by Quadrature Phase Shift Keying (QPSK) transformer phase. Further, modulated provided to “Pulse Shaping Algorithm (PSA)” neglecting inter‐symbol interference rate along with inter‐carrier interference. Subsequently, transmitter phase, “Inverse Fast Fourier Transforms (IFFT)” technique performed map symbols then provide signal receiver side. The spare validated using a semi‐blind sparse algorithm, parameters tuned Opposition Mud Ring (OMRA). Then, estimated values generating new data, Adaptive Extreme Learning Model (AELM) trained predict outcome. main objective reduce Minimum Mean Square Error (MMSE) channel. Thus, outcome predicted automatically AELM. diverse evaluations executed suggested approach over different mechanisms observe their effectualness rate.

Language: Английский

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Sensitive data identification for multi‐category and multi‐scenario data

Transactions on Emerging Telecommunications Technologies, Journal Year: 2024, Volume and Issue: 35(5)

Published: April 25, 2024

Abstract Sensitive data identification is the prerequisite for protecting critical user and business data. Traditional methods usually only target a certain type of application scenario or data, thus making it difficult to meet needs enterprise‐level protection. This paper proposes an introduction end‐to‐end sensitive system Beike Inc. The consists & annotation platform, dataset management model, which propose different governance batch streaming respectively. Specifically, we sliding window‐based method long text improve Evaluation results show that this can effect identifying without losing ability on short text, open source test dataset, value be up 94.15, so applicable in diverse scenarios.

Language: Английский

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CA-Live360: Crowd-assisted transcoding and delivery for live 360-degree video streaming

Computer Networks, Journal Year: 2024, Volume and Issue: 251, P. 110618 - 110618

Published: June 28, 2024

Language: Английский

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