IEEE journal on selected areas in communications : a publication of the IEEE Communications Society最新文献

{"title":"MaLAM4Com: Multi-Agent Cooperative Large AI Models for Wireless Communications","authors":"Ziheng Liu;Jiayi Zhang;Yiyang Zhu;Enyu Shi;Bokai Xu;Dusit Niyato;Shi Jin;Bo Ai","doi":"10.1109/JSAC.2025.3645753","DOIUrl":"10.1109/JSAC.2025.3645753","url":null,"abstract":"Large artificial intelligence (AI) models for wireless communications have demonstrated remarkable success across a range of wireless downstream tasks. However, their high computational overhead, low training efficiency, and limited privacy protection pose significant challenges for deployment on resource-constrained terminal devices. To address this issue, we propose a novel distributed framework that utilizes a three-layer cooperative paradigm to effectively achieve cooperation among agents, namely <underline>M</u>ulti-<underline>a</u>gent cooperative <underline>L</u>arge <underline>A</u>I <underline>M</u>odels <underline>for</u> Wireless <underline>Com</u>munications: MaLAM4Com. However, two key challenges in MaLAM4Com are how to effectively extract knowledge from shared information and how to alleviate the significant complexity arising from high-dimensional information sharing. To address these bottlenecks, we introduce federated distillation and Lyapunov cooperation to achieve robust knowledge transfer and consistent dynamic evolution, enabling the agents to capture the intrinsic structure of wireless channels. Subsequently, we innovatively utilize low-dimensional embeddings to facilitate information sharing among agents, significantly reducing cooperation complexity by up to 94% while enhancing privacy protection. This breaks traditional cooperative paradigms that rely on wireless channels. Moreover, we further introduce dataset distillation to enhance training efficiency by synthesizing elite data instead of directly utilizing raw datasets. Numerical results demonstrate that MaLAM4Com significantly outperforms existing baselines, with gains exceeding 45% under low sampling ratios. Remarkably, low-dimensional embeddings have also shown significant advantages in downstream tasks, reducing inference complexity by over 96%.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"44 ","pages":"2889-2903"},"PeriodicalIF":17.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145777898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FAS-LLM: Large Language Model-Based Channel Prediction for OTFS-Enabled Satellite-FAS Links","authors":"Halvin Yang;Sangarapillai Lambotharan;Mahsa Derakhshani","doi":"10.1109/JSAC.2025.3647013","DOIUrl":"10.1109/JSAC.2025.3647013","url":null,"abstract":"This paper proposes FAS-LLM, a novel large language model (LLM)–based architecture for predicting future channel states in Orthogonal Time Frequency Space (OTFS)-enabled satellite downlinks equipped with fluid antenna systems (FAS). The proposed method introduces a two-stage channel compression strategy combining reference-port selection and separable principal component analysis (PCA) to extract compact, delay–Doppler–aware representations from high-dimensional OTFS channels. These representations are then embedded into a Low Rank Adaptation (LoRA)-adapted LLM, enabling efficient time-series forecasting of channel coefficients. Performance evaluations demonstrate that FAS-LLM outperforms classical baselines including GRU, LSTM, and Transformer models, achieving up to 10 dB normalized mean squared error (NMSE) improvement and up to threefold root mean squared error (RMSE) reduction across prediction horizons. Furthermore, the predicted channels preserve key physical-layer characteristics, enabling near-optimal performance in ergodic capacity, spectral efficiency, and outage probability across a wide range of signal-to-noise ratios (SNRs). These results highlight the potential of LLM-based forecasting for delay-sensitive and energy-efficient link adaptation in future satellite IoT networks.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"44 ","pages":"2952-2963"},"PeriodicalIF":17.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145807454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beamforming-Enabled Covert Communications for Multi-Position Warden","authors":"Mingqian Liu;Zhaoxi Wen;Yunfei Chen;Jie Tang;Kai-Kit Wong;Xiaoniu Yang","doi":"10.1109/JSAC.2025.3647611","DOIUrl":"10.1109/JSAC.2025.3647611","url":null,"abstract":"In covert communications, the position of the warden has a variety of situations, which leads to different scenes that require different covert communication schemes to ensure the security. In response to this situation, in this paper, a beamforming optimization method of covert communications for multi-position warden is proposed. Firstly, we formulate a general optimization problem and optimize it to maximize the covert communication rate of the user based on Dinkelbach’s transform. Subsequently, according to the optimized general optimization problem, we propose three schemes for three scenes corresponding to different fixed warden positions, using appropriate technologies for assistance in each scheme. Specifically, the intelligent reflecting surface (IRS) is used in Scene 1 and the integrated communication and jamming (ICAJ) is used in Scenes 2 and 3, and these technologies can assist the covert communication. Moreover, we propose an alternate optimization (AO) algorithm to solve the optimization problem of Scene 1 for its optimal covert communication performance. Additionally, we also propose an AO algorithm to solve the optimization problems of Scenes 2 and 3 to optimize the active beamforming. Simulation results demonstrate the effectiveness of all three proposed schemes, that outperform their respective benchmark schemes.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"44 ","pages":"1722-1735"},"PeriodicalIF":17.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145812979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bridging the Modality Gap: Enhancing Channel Prediction With Semantically Aligned LLMs and Knowledge Distillation","authors":"Zhaoyang Li;Qianqian Yang;Zehui Xiong;Zhiguo Shi;Tony Q. S. Quek","doi":"10.1109/JSAC.2025.3647607","DOIUrl":"10.1109/JSAC.2025.3647607","url":null,"abstract":"Accurate channel prediction is essential in massive multiple-input multiple-output (m-MIMO) systems to improve precoding effectiveness and reduce the overhead of channel state information (CSI) feedback. However, existing methods often suffer from accumulated prediction errors and poor generalization to dynamic wireless environments, making it challenging to maintain high prediction accuracy. Large language models (LLMs) have demonstrated remarkable modeling and generalization capabilities in tasks such as time series prediction, making them a promising solution. Nevertheless, a significant modality gap exists between the linguistic knowledge embedded in pretrained LLMs and the intrinsic characteristics of CSI, posing substantial challenges for their direct application to channel prediction. Moreover, the large parameter size of LLMs hinders their practical deployment in real-world communication systems with stringent latency constraints. To address these challenges, we propose a novel channel prediction framework based on semantically aligned large models, referred to as CSI-ALM, which bridges the modality gap between natural language and channel information. Specifically, we design a cross-modal fusion module that aligns CSI representations with the language feature space using a pretrained corpus. Additionally, we maximize the cosine similarity between word embeddings and CSI embeddings to construct semantic cues, effectively leveraging the latent knowledge in LLMs. To reduce complexity and enable practical implementation, we further introduce a lightweight version of the proposed approach, called CSI-ALM-Light. This variant is derived via a knowledge distillation strategy based on attention matrices, which extracts essential features from the teacher model, CSI-ALM, and transfers them to a compact, efficient student model, CSI-ALM-Light. Extensive experimental results demonstrate that CSI-ALM consistently outperforms state-of-the-art deep learning methods across various communication scenarios, achieving substantial performance gains. Moreover, under limited training data conditions—where all models are trained using only 10% of the original training dataset—CSI-ALM-Light, with only 0.34M parameters, attains performance comparable to CSI-ALM and significantly outperforms conventional deep learning approaches. These validate the effectiveness of the proposed approach for accurate and efficient channel prediction in m-MIMO systems.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"44 ","pages":"3382-3396"},"PeriodicalIF":17.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145812977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Covert Communications in MEC-Based Networked ISAC Systems Toward Low-Altitude Economy","authors":"Weihao Mao;Yang Lu;Bo Ai;Tony Q. S. Quek","doi":"10.1109/JSAC.2026.3670076","DOIUrl":"10.1109/JSAC.2026.3670076","url":null,"abstract":"Low-altitude economy (LAE) is an emerging business model, which heavily relies on integrated sensing and communications (ISAC), mobile edge computing (MEC), and covert communications. This paper investigates the covert transmission design in MEC-based networked ISAC systems toward LAE, where an MEC server coordinates multiple access points to simultaneously receive computation tasks from multiple unmanned aerial vehicles (UAVs), locate a target in a sensing area, and maintain the UAVs’ covert transmission against multiple wardens. We first derive closed-form expressions for the detection error probability (DEP) at the wardens. Then, we formulate a total energy consumption minimization problem by optimizing communication, sensing, and computation resources as well as UAV trajectories, subject to the requirements on the quality of MEC services, DEP, and the radar signal-to-interference-and-noise ratio, and the causality constraints of UAV trajectories. An alternating optimization-based algorithm is proposed to handle the considered problem, which decomposes it into two subproblems: joint optimization of communication, sensing, and computation resources, and UAV trajectory optimization. The former is addressed by a successive convex approximation-based algorithm, while the latter is solved via a trust-region-based algorithm. Simulations validate the effectiveness of the proposed algorithm compared with various benchmarks, and reveal the trade-offs among communication, sensing, and computation in LAE systems.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"44 ","pages":"4193-4207"},"PeriodicalIF":17.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147350416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fairness-Aware Joint Source-Channel Coding for Robust Task-Oriented Communication","authors":"Jiaxuan Li;Youlong Wu;Songjie Xie;Shuai Ma;Yuanming Shi;Meixia Tao","doi":"10.1109/JSAC.2025.3638730","DOIUrl":"10.1109/JSAC.2025.3638730","url":null,"abstract":"Learning-based joint source-channel coding (JSCC) is widely used in task-oriented communication, which aims to extract and transmit only task-relevant information to improve communication efficiency. However, the learning-empowered algorithms in task-oriented communication may lead to information leakage on sensitive attributes and cause discrimination towards specific groups, resulting in fairness issues in social equity. Meanwhile, directly adopting fair representation learning techniques in the source encoder of communication systems poses significant challenges: First, the favorable fairness-utility tradeoff in the encoded feature representations would be deteriorated by channel noise and dynamic variations. Second, the inherent separation of source and channel design precludes the efficiency offered by JSCC for end-to-end transmission. To address these issues, we propose a task-oriented JSCC communication scheme, namely Fair-RIB, that achieves efficient encoding and inference while preserving group fairness. Our approach leverages an information bottleneck-based framework that maximizes the task utility information while limiting the sensitive information leakage to ensure fairness, and adopts a hypernetwork-parametrization mechanism to adapt to varying channel conditions. We also provide theoretical bounds for fairness guarantees by fully exploiting the characteristics of the channel noise, and introduce a selective noise injection mechanism to better manage the fairness-utility tradeoff. To overcome the intractability of the high-dimensional mutual information terms, we adopt variational approximations to derive a tractable upper bound for objective optimization. Experiments on benchmark tabular and image datasets demonstrate the superiority of our framework in achieving a fairness-utility tradeoff and the adaptability to channel variations.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"44 ","pages":"2086-2101"},"PeriodicalIF":17.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145613487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fractional Domain Waveform Design for Covert Downlink Communication With Signal Overlay in Integrated Satellite-Terrestrial Networks","authors":"Zhaoqi Wang;Peiyuan Zhou;Xiqing Liu;Yafei Zhao;Mugen Peng;Yuanwei Liu","doi":"10.1109/JSAC.2025.3639194","DOIUrl":"10.1109/JSAC.2025.3639194","url":null,"abstract":"Integrated satellite-terrestrial networks (ISTNs) provide crucial support for ubiquitous connectivity, whereas the inherent openness poses significant security threats. Covert communication that achieves intrinsic protection by concealing transmission behavior has become an ideal solution. This work studies a downlink covert satellite communication scenario under signal overlay. Existing research mostly carries out optimizations in the power domain. However, since waveforms serve as the physical carriers of information, their design critically impacts the covert communication performance via different adjustability to channel state information (CSI). Specifically, blindly enhancing demodulation reliability does not necessarily lead to better covert capacity and may even be counterproductive. OFDM is vulnerable to carrier frequency offset, while OTFS lacks the flexibility to accommodate CSI, resulting in difficulties applying existing candidate waveforms. In light of this, we propose a nimble waveform named orthogonal fractional dual index multiplexing (OFDIM) tolerant of fractional delay and Doppler. It enables common modulation schemes through integer indices and creates a fractional domain resilient to CSI. The closed-forms of the maximum covert transmit power, reliability, and spectral efficiency are derived. Fractional indices are optimized to improve the performance based on CSI. Simulations validate the theoretical analysis and demonstrate the benefits of the fractional domain in covert communication. Additionally, OFDIM incorporates a complementary security mechanism where the indices can act as dynamic ciphers and guarantee certain security even if the communication behavior is exposed.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"44 ","pages":"1751-1764"},"PeriodicalIF":17.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145665015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Covert Communication of AF Relaying Networks With Multi-Antenna Probabilistic Jamming","authors":"Qi Jin;Lisheng Fan;Xianfu Lei;Wei Xu;Pingzhi Fan","doi":"10.1109/JSAC.2025.3639023","DOIUrl":"10.1109/JSAC.2025.3639023","url":null,"abstract":"This paper investigates covert communication of multi-antenna relaying system with probabilistic interference, where a multi-antenna Alice transmits its covert message to a single-antenna Bob through a multi-antenna relay. The relay operates under the amplify-and-forward (AF) protocol, and employs antenna selection based on the relay-Bob channel quality. To enhance the covert communication, a multi-antenna jammer probabilistically transmits jamming signals to degrade Willie’s detection performance. For this system, we formulate the covert communication problem as an optimization framework which maximizes the received signal-to-interference-plus-noise ratio (SINR) at Bob while ensuring covertness constraints, by jointly optimizing the beamforming vectors at Alice and the jammer, the jamming probability, and the relay’s amplification factor. To address this non-convex optimization problem, we first derive Willie’s detection error probabilities for both transmission phases. Next, we analytically determine Willie’s optimal detection threshold and minimum detection error probability by examining their monotonicity and extremal properties. Then, we transform the original problem into a tractable convex form based on these analytical results. We further propose an efficient alternating optimization algorithm to iteratively update the system parameters. Simulation results are finally demonstrated to show the effectiveness of the proposed scheme, showing that increasing the jamming power or the number of antennas at the relay significantly improves Bob’s received SINR.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"44 ","pages":"1648-1664"},"PeriodicalIF":17.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145664709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physical Layer Security Design and Performance Evaluation for 3D Communication-2D Sensing Enabled Spatial Separation and Interference Decoupling in ISAC-IoV Networks","authors":"Kan Yu;Ruinian Wang;Kaixuan Li;Qixun Zhang;Zhiyong Feng;Dong Li","doi":"10.1109/JSAC.2025.3641091","DOIUrl":"10.1109/JSAC.2025.3641091","url":null,"abstract":"The growing demands for high-precision sensing and ultra-reliable low-latency communications in Internet of Vehicles (IoV) networks, coupled with increasingly congested spectrum resources, have driven integrated sensing and communication (ISAC) technologies toward millimeter-wave (mmWave) frequency bands. However, apart from the inherent openness of wireless channels, this transition exposes critical security gaps that the conventional physical layer security methods featured by communication interference struggle to mitigate: the cross-domain coupling interference between communication and sensing subsystems among vehicles, forming an emergent threat landscape in ISAC-IoV networks. Based on the fact that conventional forward-facing vehicular mmWave radars are typically equipped with horizontally oriented narrow beam, and have limitations in vertical resolution due to the utilization of 1D horizontally arranged antenna arrays, in this paper, we propose a 3D communication-2D sensing (<inline-formula> <tex-math>$rm {textbf {Com}^{3D}textbf {Sen}^{2D}}$ </tex-math></inline-formula>) enabled spatial separation and interference decoupling framework. Furthermore, under the proposed <inline-formula> <tex-math>$rm {textbf {Com}^{3D}textbf {Sen}^{2D}}$ </tex-math></inline-formula> framework, to make a balance between sensing accuracy, communication reliability and security, we formulate a non-convex optimization problem of secrecy rate maximization through jointly optimizing 3D-BF design of communication subsystems and radar sensing power allocation of sensing subsystems, subject to the expected levels of sensing accuracy and communication reliability constraints. Experimental evaluations demonstrate that our joint optimization approach achieves significant performance gains over individual optimization benchmarks, yielding 25.3% and 57.8% improvements in secrecy rate compared to isolated 3D-BF optimization and radar sensing power allocation, respectively. Moreover, experimental results obtained from the hardware platform further validate the effectiveness of our proposed framework. This work establishes a comprehensive solution for coupling interference management and security enhancement in next-generation ISAC-IoV networks.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"44 ","pages":"2102-2115"},"PeriodicalIF":17.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145680466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Piecemaker: A Resource-Efficient Entanglement Distribution Protocol","authors":"Luise Prielinger;Kenneth Goodenough;Guus Avis;Stefan Krastanov;Don Towsley;Gayane Vardoyan","doi":"10.1109/JSAC.2026.3704337","DOIUrl":"10.1109/JSAC.2026.3704337","url":null,"abstract":"We introduce entanglement distribution protocols that use a quantum switch to deliver stabilizer states to remote end users. As in existing schemes, the first step in our protocols involves Bell pair generation between the switch and each end user. However, unlike existing schemes that wait for all Bell pairs to be established before distributing the desired state, our approach stores only a minimal subset of Bell pairs while processing every subsequent Bell pair immediately. In doing so, our protocols reduce the average Bell pair storage time compared to existing schemes, resulting in less cumulative quantum storage noise as a direct consequence. On the theoretical side, our protocol design is grounded in the structure of vertex covers in graph states up to local complementation. Through a comprehensive numerical evaluation, we compare the fidelities of delivered states with those of a baseline scheme, for state sizes up to <inline-formula> <tex-math>$n=50$ </tex-math></inline-formula> qubits. Simulations show that our protocols can achieve the critical fidelity threshold of <inline-formula> <tex-math>$frac {1}{2}$ </tex-math></inline-formula> for multipartite entanglement in a wider range of depolarization rates and success probabilities of Bell-pair generation. Overall, our protocols achieve higher fidelity of the distributed state than the baseline in most considered parameter regimes, and can reduce infidelity by up to 45%.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"44 ","pages":"5341-5355"},"PeriodicalIF":17.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148289304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}