IEEE Open Journal of the Communications Society最新文献

{"title":"A New Design Criterion of Radio Frequency Front-End Gain for Interference Cancellation Performance in Communication Systems","authors":"Ze Wang;Fangmin He;Yufeng Ma;Bin Li;Yaxing Li","doi":"10.1109/OJCOMS.2026.3660714","DOIUrl":"https://doi.org/10.1109/OJCOMS.2026.3660714","url":null,"abstract":"Adaptive interference cancellation is an effective means to fulfill the anti-interference requirements of communication systems. The radio frequency (RF) front-end gain plays a crucial role since it determines the communication sensitivity and anti-interference performance, especially in the presence of both high-power interference signals and weak communication signals. In this paper, the influence of the RF front-end gain on communication sensitivity as well as Interference cancellation ratio (ICR) are thoroughly analyzed. Thereinafter, we derive the mathematical model of the RF front-end gain constrains taking communication sensitivity, ICR requirement and analog-to-digital converter quantization accuracy into consideration. Based on the upper and lower boundary region of gain, we propose the gain design criterion for adaptive interference cancellation in communication systems. Extensive simulations demonstrate that: 1) the ICR performance improves with the increase of RF front-end gain when lower than the gain obtained from upper boundary region, and is saturated afterward; 2) the gain obtained from lower boundary region analysis can ensure the communication sensitivity. Experimental results verify that the gain design criterion ensures the communication sensitivity and satisfies the requirements of anti-interference performance under high-power interference signals.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"7 ","pages":"1348-1362"},"PeriodicalIF":6.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11370903","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148487346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TUB-IoT: Quantum Trust-Based Big Data UAV Architecture for Security-Centric Internet of Things","authors":"Kamran Ahmad Awan;Mueen Uddin;Maha M. Althobaiti;Hashem Alaidaros;Dheyaaldin Alsalman;Ahmed Farouk","doi":"10.1109/OJCOMS.2026.3658464","DOIUrl":"https://doi.org/10.1109/OJCOMS.2026.3658464","url":null,"abstract":"UAV-assisted sensing in dense smart-city IoT deployments requires trust-aware coordination under post-quantum adversarial models, fluctuating node behavior, and high-rate heterogeneous telemetry. This study introduces a quantum resilience trust architecture that couples probabilistic trust dynamics with hybrid post-quantum cryptography for real-time UAV–IoT coordination. At the edge, UAVs act as mobile trust agents that compute QRNG-driven interaction states and behavior vectors, combining task fidelity, entropy, and interaction history into structured descriptors that parameterize local trust. These descriptors are transformed at the fog layer by a Quantum Probabilistic Trust Model, which encodes trust as density matrices with non-commutative evidence operators, enabling order-sensitive updates and interference between heterogeneous trust cues. A Secure Trust Flow Algorithm then maps trust-state gradients and control signals to tri-level admission decisions (allow, defer, block) and feeds reinforcement updates back into the trust dynamics. A hybrid cryptographic engine integrates Kyber-based key encapsulation and Dilithium signatures with conditionally activated QKD, producing trust-aware session keys, adaptive rekeying, and post-quantum-secure channel authentication. A cloud-level ledger records PQC-protected trust trajectories and synthesizes time-varying trust maps that guide application governance, including flow prioritization, anomaly isolation, and cooperative route reconfiguration. Simulation in the inD traffic dataset under multiple attack classes achieves 95.1% accuracy in trust classification, 2.33% false positive rate, 2.65s mean trust response delay and 451 ops/s throughput with 200 UAV nodes.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"7 ","pages":"1235-1248"},"PeriodicalIF":6.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11366926","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148487426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Cascade Deep Neural Network Approach for Compensation of RF Hardware Impairments in Wireless Transmitters","authors":"Abdullahi Mohammad;Arne Fischer-Bühner;Lauri Anttila;Mikko Valkama;Bo Tan","doi":"10.1109/OJCOMS.2026.3658237","DOIUrl":"https://doi.org/10.1109/OJCOMS.2026.3658237","url":null,"abstract":"Radio frequency (RF) hardware impairments can affect the transmit and receive signals in several ways, including deterioration of signal integrity, loss of power/spectral efficiency, and system performance degradation. While substantial efforts have been invested in modeling and mitigating the nonlinear effect of power amplifiers (PAs), accurate modeling of the entire RF hardware component chain is missing. This paper addresses the various imperfections and impairments in RF transceivers, particularly within analog circuits, such as digital-to-analog-converter (DAC) nonlinear distortion, in-phase/quadrature-phase (IQ) imbalance, and PA nonlinearity. We introduce a Cascade Neural Network Digital Predistortion (Cascade-NNDPD) model to compensate for these impairments. The proposed model employs a two-stage neural network approach: the first stage utilizes a phase normalized time-delay neural network, termed PNTDNN for PA nonlinearities, while the second stage deploys an additional network (MLP, LSTM, BiLSTM, or GRU) to address remaining distortions. Our results demonstrate the potential of Cascade-NNDPD design in mitigating RF hardware impairments, thus enhancing the performance and reliability of wireless communications.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"7 ","pages":"1249-1262"},"PeriodicalIF":6.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11364127","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148487429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Walsh-OFDM Breakdown Analysis Breaking the SNR Floor: An Analytical Study of Walsh-Coded OFDM Performance and Breakdown Mechanisms in Low-SNR Rician Fading","authors":"Ahmad Aldelemy;Ali Al-Dulaimi;Shaik Basheeruddin Shah;Nazar T. Ali;Walid A. Al-Hussaibi;Raed A. Abd-Alhameed","doi":"10.1109/OJCOMS.2026.3660202","DOIUrl":"https://doi.org/10.1109/OJCOMS.2026.3660202","url":null,"abstract":"This paper analyses the performance limits and breakdown mechanisms of a Walsh-coded OFDM Integrated Sensing and Communication (ISAC) waveform operating in severe Rician fading. The waveform, previously introduced as a robust low-rate design for wearable links, is here used as a testbed to study how sensing and communication capabilities diverge in ultra-low Signal-to-Noise Ratio (SNR) regimes. We specifically quantify the “breaking points” of the system, demonstrating that while the Walsh-coded communication link becomes unreliable around −18 dB, the direction finding (DF) capability persists with sub-degree accuracy (Root Mean Square Error RMSE <inline-formula> <tex-math>$lt ~1^{circ }$ </tex-math></inline-formula>) down to −33 dB. This reveals a distinct <inline-formula> <tex-math>$approx {mathrm {15~dB}}$ </tex-math></inline-formula> “Sensing-Only” operational gap under quasi-static Rician fading assumptions. Notably, reducing the integration window shifts the sensing threshold upward by <inline-formula> <tex-math>$approx {mathrm {10~dB}}$ </tex-math></inline-formula> per decade reduction in snapshots, while the required hundreds-of-milliseconds observation latency is suitable for quasi-static wearables but may limit real-time tracking applications. Furthermore, we provide analytical approximations for the effective SNR and Angle-of-Arrival (AoA) Cramér-Rao Lower Bound (CRLB) under massive time-frequency averaging, and present a new comparative benchmark against standard estimators (Schmidl-Cox, Moose, MUSIC). Results confirm that the pilot-aided framework extends the synchronisation lock range by <inline-formula> <tex-math>$approx {mathrm {19~dB}}$ </tex-math></inline-formula> compared to classical baselines, establishing it as a reference for analysing breakdown physics in next-generation body-centric networks.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"7 ","pages":"1302-1318"},"PeriodicalIF":6.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11370147","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148487432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structural Multi-Optimality in Edge Server Placement for MEC Networks","authors":"Edson José Pacheco;Carlos Marcelo Pedroso","doi":"10.1109/OJCOMS.2026.3698640","DOIUrl":"https://doi.org/10.1109/OJCOMS.2026.3698640","url":null,"abstract":"Edge server placement in mobile edge computing (MEC) networks is typically treated as an optimization problem with a unique solution. This paper shows that dense base station (BS) deployments produce multiple placements with identical cost, a phenomenon termed structural multi-optimality. A formal coverage-equivalence condition identifies when two BSs are interchangeable, and combinatorial bounds quantify the resulting solution multiplicity. Experiments on eight real BS datasets spanning three continents confirm that multi-optimality persists across four orders of magnitude of network density and is independent of the solver used. A demand-priority extension exploits this multiplicity by steering server selection toward high-demand BSs without increasing the server count. These results reframe MEC placement from a single-solution search into a landscape navigation problem, where planners can select among equivalent configurations to meet site-level and operational constraints.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"7 ","pages":"5889-5902"},"PeriodicalIF":6.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11541200","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148488398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decentralized MARL for SDN Ground Station Cluster Selection in LEO Constellations Under Stochastic Weather","authors":"Wafa Hasanain;Pablo G. Madoery;Halim Yanikomeroglu;Güneş Karabulut Kurt;Sameera Siddiqui;Stéphane Martel","doi":"10.1109/OJCOMS.2026.3710911","DOIUrl":"https://doi.org/10.1109/OJCOMS.2026.3710911","url":null,"abstract":"Low Earth Orbit (LEO) satellite constellations enable global low-latency connectivity but face challenges due to weather-dependent link variability, orbital dynamics, and heterogeneous ground infrastructure. In this paper, we propose a hybrid LEO-terrestrial architecture that integrates Software-Defined Networking (SDN) ground station clusters with repeater-assisted reception and a structured fallback mechanism. We develop a stochastic model that captures weather-driven reliability, correlated repeater behavior, and multi-path reception, and formulate an optimization problem to minimize the expected communication delay. To address the intractability of this problem in large-scale, partially observable environments, we design a fully decentralized Multi-Agent Reinforcement Learning (MARL) framework based on Proximal Policy Optimization (PPO), where each satellite makes decisions using only local observations. The reward is aligned with the analytical delay objective, ensuring consistency between the model and learned policies. Simulation results across diverse scenarios demonstrate that the proposed approach reduces the mean delay by 40-60% and significantly decreases fallback usage compared to baseline methods. These results highlight the effectiveness of the proposed framework in enabling adaptive and delay-efficient control in next-generation LEO satellite systems.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"7 ","pages":"7770-7789"},"PeriodicalIF":6.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11603814","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148483411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward Generalizable mmWave and Terahertz Deep Learning-Based Channel Prediction in 6G Networks","authors":"Eslam Hasan;Elmahedi Mahalal;Muhammad Ismail;Zi-Yang Wu;Mostafa Fouda;Nei Kato","doi":"10.1109/OJCOMS.2026.3708001","DOIUrl":"https://doi.org/10.1109/OJCOMS.2026.3708001","url":null,"abstract":"The use of millimeter-wave (mmWave) and Terahertz (THz) bands is essential for 6G networks, as they enable ultra-high data rates, increased capacity, and low-latency communication, thereby enabling transformative applications from virtual reality to holographic communications. Channel prediction using deep learning (DL) is essential in both bands to overcome these bands’ challenges, such as sensitivity to blockage. The existing prediction strategies assume static data distributions, where both training and testing datasets are derived from identical or highly similar environmental conditions. However, real-world conditions change over time due to non-stationarity in indoor wireless environments, resulting in data drift from differences between the train and test data distributions. Data drift can impact the generalization of DL channel prediction models by causing model drift. In this paper, the data drift in the mmWave and THz bands is categorized for the first time and represented in three scenarios: user densities, mobility stages, and room configurations. We investigate how data drift affects the generalization of DL models for mmWave and THz channel prediction, and propose a mitigation approach to address model drift and maintain generalization in affected scenarios. Our results show that mmWave models are most affected by mobility-stage changes, with performance degradation ranging from 11% to 68%, whereas THz models are most affected by user-density changes, with degradation ranging from 4% to 62%. To mitigate these effects, we propose a weighted ensemble approach for mmWave, reducing deterioration to <inline-formula> <tex-math>$leq 4%$ </tex-math></inline-formula>, and a two-stage framework for THz, keeping deterioration <inline-formula> <tex-math>$leq 9%$ </tex-math></inline-formula>.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"7 ","pages":"7283-7301"},"PeriodicalIF":6.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11585832","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148484072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"LLM-Driven Multi-Agent Framework for Autonomous Network Slice Management: Architecture and Proof-of-Concept Experiments","authors":"Abdulhalim Dandoush;Viswanath Kumarskandpriya;Mueen Uddin;Ahmed Farouk;Merouane Debbah","doi":"10.1109/OJCOMS.2026.3705651","DOIUrl":"https://doi.org/10.1109/OJCOMS.2026.3705651","url":null,"abstract":"Network slicing (NS) enables service providers to create independent virtual networks, storage, and computing resources (so-called slices) from a shared physical infrastructure across one or more operators. These slices can be tailored to specific services, user needs, and Quality-of-Service (QoS) requirements. However, most production-grade orchestration frameworks deployed today still rely on manually crafted templates and centralized controllers, even though a growing body of research has begun to explore deep reinforcement learning (DRL) and multi-agent DRL (MARL) for autonomous and distributed orchestration. As the number of slices increases, limited visibility across administrative domains and human-driven configuration render provisioning slow and error-prone. We address these limitations by proposing a multi-agent management framework where Large Language Models (LLMs) act as intelligent interfaces between tenants and the Management and Orchestration (MANO) stack. Agents interpret high-level intent provided by users or applications, translate it into standards-compliant descriptors, cooperate with other agents and underlying ML-based optimizers to allocate resources, and supervise the slice lifecycle. To validate this paradigm, we conduct two complementary experiments that together cover the AI-driven stages of the proposed workflow. First, we benchmark four state-of-the-art LLMs in generating Yet Another Markup Language (YAML)-based slice descriptions from natural-language prompts of varying complexity. GPT-4.1 consistently produces valid schemas and adheres to constraints, while other models occasionally violate conditions but still yield usable outputs. Second, we implement a proof-of-concept multi-agent system that, from a single user request, models a slice, synthesizes a Topology and Orchestration Specification for Cloud Applications (TOSCA) descriptor, and generates a deployment plan. This second experiment validates the multi-agent transformation chain from a slice request to deployable artifacts. The end-to-end workflow completes in about 40 seconds and produces artifacts validated by a domain expert. The final infrastructure instantiation of these already validated artifacts, e.g., through Kubernetes, Docker Compose, or NFV orchestration tools, is intentionally not treated as a separate AI experiment in this paper. Our results show that modern LLMs, when orchestrated in a collaborative agent framework, can significantly reduce the engineering effort and turnaround time required to move from high-level intents to deployable slice descriptors while ensuring alignment with industry standards. The proposed LLM-based framework can be integrated with any resource allocation optimizers or ML-based (e.g., DRL/MARL) infrastructure and network controllers for multi-tenant resource optimization. We emphasize that the present validation targets the orchestration/specification layer of network slice management, namely the translation of natu","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"7 ","pages":"7118-7135"},"PeriodicalIF":6.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11573048","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148487345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantum-Resistant Security for Blockchain-Enabled 6G Networks: A Comprehensive Review","authors":"Pasindu Udugahapattuwa;Chamitha de Alwis;Engin Zeydan;Uditha Wijewardhana;Madhusanka Liyanage","doi":"10.1109/OJCOMS.2026.3673993","DOIUrl":"https://doi.org/10.1109/OJCOMS.2026.3673993","url":null,"abstract":"The exponential advancement of quantum computing poses an unprecedented threat to blockchain technology and emerging Sixth Generation (6G) networks, necessitating an urgent transition to post-quantum cryptographic solutions. This comprehensive review proposed post-quantum Cryptography (PQC) integration within Blockchain Enabled 6G (BE6G) architectures, highlighting vulnerabilities by Shor’s and Grover’s algorithms according to existing cryptographic standards, including Rivest-Shamir-Adleman (RSA), Elliptic Curve Digital Signature Algorithm (ECDSA), and Elliptic-Curve Cryptography (ECC). The paper addresses quantum computing fundamentals and blockchain security implications, exploring quantum-resistant cryptographic schemes including lattice-based, hash-based, code-based, and multivariate approaches. Through systematic examination of post-quantum threats, this review shows vulnerabilities affecting nearly 25% of existing cryptocurrency assets, presenting how quantum computers can break public-key systems in polynomial time. The study proposes solutions for implementing quantum-resistant blockchain architectures throughout 6G components, including Radio Access Network (RAN), edge computing, and core transport networks, while meeting ultra-low latency and scalability requirements. Key findings elaborate that hybrid cryptographic approaches combining classical and quantum-resistant algorithms provide promising directions. Lattice-based algorithms, particularly CRYSTALS-kyber and CRYSTALS-dilithium, are identified as primary deployment candidates. The review concludes that successful Quantum-Resistant Security deployment for BE6G Networks requires unprecedented coordination among telecommunication operators, blockchain developers, equipment manufacturers, and regulatory bodies. The “harvest now, decrypt later” threat model creates sudden implementation, valuable for long-term digital infrastructure security.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"7 ","pages":"3253-3287"},"PeriodicalIF":6.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11434854","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148489416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dual Satellite STBC Combining Under Imperfect Symbol Time Alignment","authors":"Carlos L. Marcos Rojas;Jorge L. Gonzalez Rios;Luis M. Garces Socarras;Vibhum Singh;Raudel Cuiman Marquez;Juan C. Merlano Duncan;Vu Nguyen Ha;Symeon Chatzinotas;Björn Ottersten","doi":"10.1109/OJCOMS.2025.3648041","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3648041","url":null,"abstract":"In distributed satellite communication systems, spatial diversity techniques such as Space-Time Block Coding (STBC) offer an attractive opportunity to enhance the link’s capabilities without additional spectrum consumption. One of the major challenges that still remains is the degradation of the Signal-to-Interference-plus-Noise Ratio (SINR) at the receiver, primarily due to time misalignment between satellites. This paper presents a robust receiver architecture that demonstrates strong resilience against SINR degradation caused by time misalignment between satellites and maintains robust performance even under additional impairments such as power imbalance and Doppler shifts. Moreover, we present an efficient implementation of the receiver, which combines both software and hardware platforms.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"7 ","pages":"301-314"},"PeriodicalIF":6.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11313860","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148490758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}