以下文章来自于黄大年茶思屋科技网站。
【编者按】面向通信网络的大型生成式AI技术已成为通信领域最活跃的前沿研究方向之一，为了便于相关领域的研究人员快速了解学术研究动态、掌握最新技术进展，黄大年茶思屋科技网站联合IEEE GenAINet ETI组织编辑了《通信中的大型生成式AI研究论文集》（Research Library of Large Generative AI Models in Telecom），并于今年5月在GenAINet ETI官网和微信公众号发布了v1.0版本。由于这一领域的研究发展极为迅速，新的论文不断涌现，为充分体现业界最新进展情况，茶思屋网站组织业界专家对v1.0版本做了大量的更新、补充和完善，现公开发布，供学术界和工业界参考。
联合IEEE GenAINet ETI编辑整理，多位专家学者倾力打造
汇聚通信大模型领域最新学术成果，收录200余篇相关论文
按研究方向分为15个领域，便于针对性阅读学习
持续更新，充分体现前沿性
Research Library of Large Generative AI Models in Telecom
(Edited by Prof. Li Sun)
If you have any publications that would like to be included in this Research Library, please kindly send e-mail to Prof. Li Sun: sunli50@huawei.com
1. Reviews, Surveys, and Tutorials
A. Celik and A. M. Eltawil, At the dawn of generative AI era: A tutorial-cum-survey on new frontiers in 6G wireless intelligence, IEEE Open Journal of the Communications Society, May 2024
Z. Chen, Z. Zhang, and Z. Yang, Big AI models for 6G wireless networks: Opportunities, challenges, and research directions, IEEE Wireless Communications, Jul. 2024
Karapantelakis A, Nikou A, Kattepur A, et al. A Survey on the Integration of Generative AI for Critical Thinking in Mobile Networks. arXiv preprint arXiv:2404.06946, 2024.
Zhou H, Hu C, Yuan Y, et al. Large language model (llm) for telecommunications: A comprehensive survey on principles, key techniques, and opportunities. arXiv preprint arXiv:2405.10825, 2024.
A Chavan, R Magazine, S Kushwaha, M Debbah, D Gupta, Faster and Lighter LLMs: A Survey on Current Challenges and Way Forward, arXiv preprint arXiv:2402.01799, 2024
L Bariah, Q Zhao, H Zou, Y Tian, F Bader, M Debbah, Large generative AI models for telecom: The next big thing? IEEE Communications Magazine, 2024
M Xu, H Du, D Niyato, J Kang, Z Xiong, S Mao, Z Han, A Jamalipour, Unleashing the power of edge-cloud generative AI in mobile networks: A survey of AIGC services, IEEE Communications Surveys & Tutorials, 2024
Y Liu, H Du, D Niyato, J Kang, Z Xiong, DI Kim, A Jamalipour, Deep generative model and its applications in efficient wireless network management: A tutorial and case study, IEEE Wireless Communications, 2024
A Maatouk, N Piovesan, F Ayed, A De Domenico, M Debbah, Large language models for telecom: Forthcoming impact on the industry, arXiv preprint arXiv:2308.06013, 2023
M Xu, D Niyato, J Kang, Z Xiong, A Jamalipour, Y Fang, DI Kim, Integration of Mixture of Experts and Multimodal Generative AI in Internet of Vehicles: A Survey, arXiv preprint arXiv:2404.16356, 2024
R Zhang, K Xiong, H Du, D Niyato, J Kang, X Shen, HV Poor, Generative AI-enabled vehicular networks: Fundamentals, framework, and case study, IEEE Network, 2024
H Du, Z Li, D Niyato, J Kang, Z Xiong, XS Shen, DI Kim, Enabling AI-Generated Content Services in Wireless Edge Networks, IEEE Wireless Communications, 2024
Y Huang, H Du, X Zhang, D Niyato, J Kang, Z Xiong, S Wang, T Huang, Large language models for networking: Applications, enabling techniques, and challenges, arXiv preprint arXiv:2311.17474, 2023
M Xu, D Niyato, H Zhang, J Kang, Z Xiong, S Mao, Z Han, Sparks of generative pretrained transformers in edge intelligence for the metaverse: Caching and inference for mobile artificial intelligence-generated content services, IEEE Vehicular Technology Magazine, 2023
Hongyang Du, Dusit Niyato, Jiawen Kang, Zehui Xiong, Ping Zhang, Shuguang Cui, Xuemin Shen, Shiwen Mao, Zhu Han, Abbas Jamalipour, H Vincent Poor, Dong In Kim, The age of generative AI and AI-generated everything, arXiv preprint arXiv:2311.00947, 2023
H Du, R Zhang, Y Liu, J Wang, Y Lin, Z Li, D Niyato, J Kang, Z Xiong, Beyond deep reinforcement learning: A tutorial on generative diffusion models in network optimization, arXiv preprint arXiv:2308.05384, 2023
W Tong, C Peng, T Yang, F Wang, J Deng, R Li, L Yang, H Zhang, Ten Issues of NetGPT, arXiv preprint arXiv:2311.13106, 2023
Du H, Zhang R, Liu Y, et al. Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization. IEEE Communications Surveys & Tutorials, 2024
Lina Bariah, Merouane Debbah, AI Embodiment Through 6G: Shaping the Future of AGI, IEEE Wireless Communications, vol. 31, no. 5, 2024
Fahime Khoramnejad, Ekram Hossain, Generative AI for the Optimization of Next-Generation Wireless Networks: Basics, State-of-the-Art, and Open Challenges, arXiv:2405.17454, May 2024
2. Fundamentals of Large Generative AI Models in Telecom
Jayashankar T, Lee G C F, Lancho A, et al. Score-based source separation with applications to digital communication signals. Advances in Neural Information Processing Systems, 2024, 36.
Soman S. Observations on LLMs for telecom domain: capabilities and limitations. arXiv preprint arXiv:2305.13102, 2023.
MEA Seddik, SW Chen, S Hayou, P Youssef, M Debbah, How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse, arXiv preprint arXiv:2404.05090, 2024.
Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, Alessandro Cappelli, Ruxandra Cojocaru, Mérouane Debbah, Étienne Goffinet, Daniel Hesslow, Julien Launay, Quentin Malartic, Daniele Mazzotta, Badreddine Noune, Baptiste Pannier, Guilherme Penedo, The falcon series of open language models, arXiv preprint arXiv:2311.16867, 2023
Y Qu, M Ding, N Sun, K Thilakarathna, T Zhu, D Niyato, The Frontier of Data Erasure: Machine Unlearning for Large Language Models, arXiv preprint arXiv:2403.15779, 2024
Abdullah Zayat, Mahmoud A. Hasabelnaby, Mohanad Obeed, Anas Chaaban, Transformer Masked Autoencoders for Next-Generation Wireless Communications: Architecture and Opportunities, IEEE Communications Magazine, 2023
Y Wang, H Sun, J Wang, J Wang, W Tang, Q Qi, S Sun, J Liao, Towards semantic consistency: Dirichlet energy driven robust multi-modal entity alignment, arXiv preprint arXiv:2401.17859, 2024
H Wang, D Cheng, H Sun, J Wang, Q Qi, J Liao, J Wang, C Liu, How Does Diffusion Influence Pretrained Language Models on Out-of-Distribution Data? arXiv preprint arXiv:2307.13949, 2023
T Ahmed, N Piovesan, A De Domenico, S Choudhury, Linguistic Intelligence in Large Language Models for Telecommunications, arXiv preprint arXiv:2402.15818, 2024
N Piovesan, A De Domenico, F Ayed, Telecom Language Models: Must They Be Large?, arXiv preprint arXiv:2403.04666, 2024
AL Bornea, F Ayed, A De Domenico, N Piovesan, A Maatouk, Telco-RAG: Navigating the Challenges of Retrieval-Augmented Language Models for Telecommunications, arXiv preprint arXiv:2404.15939, 2024
3. Large Generative AI for PHY and MAC Design
T. Wu, Z. Chen, D. He, L. Qian, Y. Xu, M. Tao, and W. Zhang, CDDM: Channel denoising diffusion models for wireless semantic communications, arXiv:2309.08895, 2023.
B. Liu, X. Liu, S. Gao, X. Cheng, L. Yang. LLM4CP: Adapting Large Language Models for Channel Prediction. Journal of Communications and Information Networks 9.2 (2024): 113-125.
Fontaine J, Shahid A, De Poorter E. Towards a Wireless Physical-Layer Foundation Model: Challenges and Strategies. arXiv preprint arXiv:2403.12065, 2024.
M. Arvinte and J. I. Tamir, MIMO Channel Estimation Using Score-Based Generative Models, in IEEE Transactions on Wireless Communications, vol. 22, no. 6, pp. 3698-3713, June 2023
Z Wang, J Zhang, H Du, R Zhang, D Niyato, B Ai, KB Letaief, Generative AI Agent for Next-Generation MIMO Design: Fundamentals, Challenges, and Vision, arXiv preprint arXiv:2404.08878, 2024
Nguyen Van Huynh, Jiacheng Wang, Hongyang Du, Dinh Thai Hoang, Dusit Niyato, Diep N Nguyen, Dong In Kim, Khaled B Letaief, Generative AI for physical layer communications: A survey, 2024
M Akrout, A Mezghani, E Hossain, F Bellili, RW Heath, From Multilayer Perceptron to GPT: A Reflection on Deep Learning Research for Wireless Physical Layer, arXiv preprint arXiv:2307.07359, 2023
Lee J H, Lee D H, Lee J, et al. Integrating Pre-Trained Language Model with Physical Layer Communications. arXiv preprint arXiv:2402.11656, 2024
T. Zhang. D. Xu, A. Saas, K. Yu, and V. C. M. Leung, Large Beamforming Models for Robust Wireless Transmission in Generalized Scenes of RIS-aided Intelligent IoV Network, IEEE Transactions on Vehicular Technology, 2024
L. Zhang, H. Sun, Y. Zeng, Q. Hu, Spatial Channel State Information Prediction With Generative AI: Toward Holographic Communication and Digital Radio Twin, IEEE Network, vol. 38, no. 5, 2024
4. Large Generative AI for Radio Resource Allocation/Optimization
H Du, G Liu, Y Lin, D Niyato, J Kang, Z Xiong, DI Kim, Mixture of Experts for Network Optimization: A Large Language Model-enabled Approach, arXiv preprint arXiv:2402.09756, 2024
B Du, H Du, H Liu, D Niyato, P Xin, J Yu, M Qi, Y Tang, YOLO-based semantic communication with generative AI-aided resource allocation for digital twins construction, IEEE Internet of Things Journal, 2023
Liu T, Fang X, He R. Generative Diffusion Model (GDM) for Optimization of Wi-Fi Networks. arXiv preprint arXiv:2404.15684, 2024
Du X, Fang X. An Integrated Communication and Computing Scheme for Wi-Fi Networks based on Generative AI and Reinforcement Learning. arXiv preprint arXiv:2404.13598, 2024
Hongyang Du, Guangyuan Liu, Yijing Lin, Dusit Niyato, Jiawen Kang, Zehui Xiong, Dong In Kim. Mixture of Experts for Intelligent Networks: A Large Language Model-enabled Approach. 2024 International Wireless Communications and Mobile Computing (IWCMC)
Amirhassan Babazadeh Darabi, Sinem Coleri, Diffusion Model Based Resource Allocation Strategy in Ultra-Reliable Wireless Networked Control Systems, arXiv:2407.15784, Jul. 2024
Jie Zhang, Jun Li, Long Shi, Zhe Wang, Shi Jin, Wen Chen, H. Vincent Poor, Decision Transformer for Wireless Communications: A New Paradigm of Resource Management, arXiv:2404.05199, Apr. 2024
5. Large Generative AI for Network Management, Orchestration, Operation, and System-Level Optimization
G Sun, W Xie, D Niyato, H Du, J Kang, J Wu, S Sun, P Zhang, Generative AI for Advanced UAV Networking, arXiv preprint arXiv:2404.10556, 2024
J Wang, H Du, D Niyato, J Kang, Z Xiong, DI Kim, KB Letaief, Toward Scalable Generative AI via Mixture of Experts in Mobile Edge Networks, arXiv preprint arXiv:2402.06942, 2024
Feibo Jiang, Li Dong, Yubo Peng, Kezhi Wang, Kun Yang, Cunhua Pan, Dusit Niyato, Octavia A Dobre, Large Language Model Enhanced Multi-Agent Systems for 6G Communications, arXiv preprint arXiv:2312.07850, 2023
Bo Rong, Humphrey Rutagemwa, Leveraging Large Language Models for Intelligent Control of 6G Integrated TN-NTN with IoT Service, IEEE Network, 2024
D Chen, Q Qi, Q Fu, J Wang, J Liao, Z Han, Transformer-Based Reinforcement Learning for Scalable Multi-UAV Area Coverage, IEEE Transactions on Intelligent Transportation Systems, 2024
J Wang, L Zhang, Y Yang, Z Zhuang, Q Qi, H Sun, L Lu, J Feng, J Liao, Network Meets ChatGPT: Intent Autonomous Management, Control and Operation, Journal of Communications and Information Networks 8 (3), 239-255, 2023
Liexiang Yue and Tianjiao Chen, AI Large Model and 6G Network, IEEE GLOBECOM Workshops, 2023
Dandoush A, Kumarskandpriya V, Uddin M, et al. Large Language Models meet Network Slicing Management and Orchestration. arXiv preprint arXiv:2403.13721, 2024
J. Su, S. Nair, L. Popokh, Leveraging large language models for VNF resource forecasting. 2024 IEEE 10th International Conference on Network Softwarization (NetSoft)
K. B. Kan, H. Mun, G. Cao, Y. Lee, Mobile-LLaMA: Instruction Fine-Tuning Open-Source LLM for Network Analysis in 5G Networks. IEEE Network, vol. 38, no. 5, 2024
Georgios Samaras, Marinela Mertiri, Maria-Evgenia Xezonaki, Vasileios Theodorou, Panteleimon Konstantinos Chartsias, Theodoros Bozios. Unlocking the Path Towards AI-Native Networks with Optimized Lightweight Large Language Models. IEEE MeditCom, 2024
D. M. Manias, Ali Chouman, A. Shami, Towards Intent-Based Network Management: Large Language Models for Intent Extraction in 5G Core Networks. 2024 20th International Conference on the Design of Reliable Communication Networks (DRCN)
Dimitrios Brodimas, Kostis Trantzas, Besiana Agko, Georgios Christos Tziavas, Christos Tranoris, Spyros Denazis, Alexios Birbas, Towards Intent-based Network Management for the 6G System adopting Multimodal Generative AI. 2024 EuCNC/6G Summit
Nguyen Van Tu, Jae-Hyoung Yoo,James Won-Ki Hong, Towards Intent-based Configuration for Network Function Virtualization using In-context Learning in Large Language Models, 2024 IEEE Network Operations and Management Symposium
Hongyang Du, Ruichen Zhang, Dusit Niyato, Jiawen Kang, Zehui Xiong, Dong In Kim, Reinforcement Learning with Large Language Models (LLMs) Interaction for Network Services, IEEE ICNC, 2024
R. Zhang, H. Du, Y. Liu, D. Niyato, J. Kang, S. Sun, X. Shen, and H. V. Poor, Interactive AI with Retrieval-Augmented Generation for Next Generation Networking, IEEE Network, 2024
N. Tu, J-H. Yoo, J. W-K. Hong, Towards Intent-based Configuration for Network Function Virtualization using In-context Learning in Large Language Models, 2024 IEEE Network Operations and Management Symposium
M. Ameur, B. Brik, A. Ksentini, Leveraging LLMs to eXplain DRL Decisions for Transparent 6G Network Slicing, 2024 IEEE 10th International Conference on Network Softwarization (NetSoft)
S. D’urso, M. Fontana, B. Martini, and F. Sciarrone, Enhancing Intent Acquisition and Translation with Large Language Models and Intelligent Chatbots: A DHCP Use Case, 2024 IEEE 10th International Conference on Network Softwarization (NetSoft)
Jingwen Tong, Jiawei Shao, Qiong Wu, Wei Guo, Zijian Li, Zehong Lin, Jun Zhang, WirelessAgent: Large Language Model Agents for Intelligent Wireless Networks, arXiv:2409.07964, Sep. 2024
Chengming Hu, Hao Zhou, Di Wu, Xi Chen, Jun Yan, Xue Liu, Self-Refined Generative Foundation Models for Wireless Traffic Prediction, arXiv:2408.10390, Aug. 2024
Berk Çiloğlu, Görkem Berkay Koç, Afsoon Alidadi Shamsabadi, Metin Ozturk, Halim Yanikomeroglu, Strategic Demand-Planning in Wireless Networks: Can Generative-AI Save Spectrum and Energy? arXiv:2407.02292, Jul. 2024
X. Chen, L. Luo, F. Tang, M. Zhao, and N. Kato, AIGC-based Evolvable Digital Twin Networks: A Road to the Intelligent Metaverse, IEEE Network (Early Access), June 2024
D Wu, X Wang, Y Qiao, Z Wang, J Jiang, S Cui, F Wang, NetLLM: Adapting large language models for networking, in Proceedings of the ACM SIGCOMM 2024 Conference, 2024
Tianyu Cui, Shiyu Ma, Ziang Chen, Tong Xiao, Shimin Tao, et. al., LogEval: A Comprehensive Benchmark Suite for Large Language Models In Log Analysis, arXiv preprint arXiv:2407.01896, 2024
Pengxiang Jin, Shenglin Zhang, Minghua Ma, Haozhe Li, Yu Kang, et. al., Assess and summarize: Improve outage understanding with large language models, in Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023
Yuhe Liu, Changhua Pei, Longlong Xu, Bohan Chen, Mingze Sun, et. al., OpsEval: A Comprehensive Task-Oriented AIOps Benchmark for Large Language Models, arXiv preprint arXiv:2310.07637, 2023
6. Edge Intelligence via Large Generative AI Models
Guanqiao Qu, Qiyuan Chen, Wei Wei, Zheng Lin, Xianhao Chen, Kaibin Huang, Mobile Edge Intelligence for Large Language Models: A Contemporary Survey, arXiv:2407.18921, Jul. 2024
Z. Lin, G. Qu, Q. Chen, X. Chen, Z. Chen, and K. Huang, Pushing large language models to the 6G edge: Vision, challenges, and opportunities
Z. Chen, H. Yang, Y.C. Tay, K. Chong, T. Q. S. Quek, The role of federated learning in a wireless world with foundation models.
B. Lai, J. Wen, J. Kang, H. Du, et. al., Resource-Efficient Generative Mobile Edge Networks in 6G Era: Fundamentals, Framework and Case Study, IEEE Wireless Communications, vol. 31, no. 4, pp. 66-74, Aug. 2024.
G Liu, H Du, D Niyato, J Kang, Z Xiong, A Jamalipour, S Mao, DI Kim, Fusion of Mixture of Experts and Generative Artificial Intelligence in Mobile Edge Metaverse, arXiv preprint arXiv:2404.03321, 2024
H Du, R Zhang, D Niyato, J Kang, Z Xiong, S Cui, X Shen, DI Kim, User-Centric Interactive AI for Distributed Diffusion Model-based AI-Generated Content, arXiv preprint arXiv:2311.11094, 2023
H Du, Z Li, D Niyato, J Kang, Z Xiong, H Huang, S Mao, Generative AI-aided optimization for AI-generated content (AIGC) services in edge networks, arXiv preprint arXiv:2303.13052, 2023
Yifei Shen, Jiawei Shao, Xinjie Zhang, Zehong Lin, Hao Pan, Dongsheng Li, Jun Zhang, Khaled B. Letaief, Large Language Models Empowered Autonomous Edge AI for Connected Intelligence, IEEE Communications Magazine, 2024
L Dong, F Jiang, Y Peng, K Wang, K Yang, C Pan, R Schober, Lambo: Large language model empowered edge intelligence, arXiv preprint arXiv:2308.15078, 2023
Y Liu, H Du, D Niyato, J Kang, S Cui, X Shen, P Zhang, Optimizing mobile-edge AI-generated everything (AIGX) services by prompt engineering: Fundamental, framework, and case study, IEEE Network, 2023
M Xu, D Niyato, H Zhang, J Kang, Z Xiong, S Mao, Z Han, Joint foundation model caching and inference of generative AI services for edge intelligence, 2023 IEEE Global Communications Conference, 3548-3553, 2023
T Zhou, J Yu, J Zhang, DHK Tsang, Federated Prompt-based Decision Transformer for Customized VR Services in Mobile Edge Computing System, arXiv preprint arXiv:2402.09729, 2024
L. Zeng, S. Ye, X. Chen, and Y. Yang, Implementation of Big AI Models for Wireless Networks with Collaborative Edge Computing, IEEE Wireless Communications, vol. 31, no. 3, pp. 50-58, 2024
G. Qu, Z. Lin, F. Liu, X. Chen, and K. Huang, TrimCaching: Parameter-Sharing AI Model Caching in Wireless Edge Networks, IEEE 44th International Conference on Distributed Computing Systems (ICDCS), 2024
Guanqiao Qu, Zheng Lin, Qian Chen, Jian Li, Fangming Liu, Xianhao Chen, Kaibin Huang, TrimCaching: Parameter-sharing Edge Caching for AI Model Downloading, arXiv:2404.14204, May 2024
Xinyuan Zhang, Jiang Liu, Zehui Xiong, Yudong Huang, Gaochang Xie, Ran Zhang. Edge Intelligence Optimization for Large Language Model Inference with Batching and Quantization. IEEE WCNC, 2024
D. Du, Z. Li, D. Niyato, J. Kang, Z. Xiong, H. Huang, and S. Mao, Diffusion-Based Reinforcement Learning for Edge-Enabled AI-Generated Content Services, IEEE Transactions on Mobile Computing, vol. 23, no. 9, 2024
S. Zhang, Q. Liu, K. Chen. B. Di. H. Zhang, W. Yang, D. Niyato, Z. Han, and H. V. Poor, Large Models for Aerial Edges: An Edge-Cloud Model Evolution and Communication Paradigm, IEEE Journal on Selected Areas in Communications, 2024
T. Hao, K. Hwang, J. Zhan, Y. Li, and Y. Cao, Scenario-Based AI Benchmark Evaluation of Distributed Cloud/Edge Computing Systems, IEEE Transactions on Computers, vol. 72, no. 3, 2023.
Y. Liu, X. Lin, S. Li, G. Li, Q. Mao, and J. Li, Towards Multi-Task Generative-AI Edge Services with an Attention-based Diffusion DRL Approach, 2024 9th IEEE International Conference on Smart Cloud (SmartCloud)
S. Li, X. Lin, W. Xu, and J. Li, AI-Generated Content-Based Edge Learning for Fast and Efficient Few-Shot Defect Detection in IIoT, IEEE Transactions on Services Computing, 2024
Y. He, J. Fang, F. R. Yu, and V. C. Leung, Large Language Models (LLMs) Inference Offloading and Resource Allocation in Cloud-Edge Computing: An Active Inference Approach, IEEE Transactions on Mobile Computing (Early Access), July 2024
7. Large Generative AI for Green Wireless
J Wen, R Zhang, D Niyato, J Kang, H Du, Y Zhang, Z Han, Generative AI for Low-Carbon Artificial Intelligence of Things, arXiv preprint arXiv:2404.18077, 2024
Y. Mao, X. Yu, K. Huang, Y. Zhang, and J. Zhang, Green Edge AI: A Contemporary Survey, Proceedings of the IEEE, 2024
8. Large Generative AI and Semantics/Effective Communications
K. Zhang, L. Li, W. Lin, Y. Yan, R. Li, W. Cheng, and Z. Han, Semantic successive refinement: A generative AI-aided semantic communication framework.
H. Xie, Z. Qin, X. Tao, and Z. Han, Toward intelligent communications: Large model empowered semantic communications, IEEE Communications Magazine, Jul. 2024.
F. Zhao, Y. Sun, L. Feng, L. Zhang, and D. Zhao. Enhancing reasoning ability in semantic communication through generative AI-assisted knowledge construction, IEEE Communications Letters, vol. 28, no. 4, pp. 832-836, Apr. 2024.
A. Raha, Md. S. Munir, A. Adhikary, Y. Qiao, and C. S. Hong, Generative AI-driven semantic communication framework for nextG wireless network
Xu C, Mashhadi M B, Ma Y, et al. Semantic-Aware Power Allocation for Generative Semantic Communications with Foundation Models. arXiv preprint arXiv:2407.03050, 2024.
E. Erdemir, T. Y. Tung, P. L. Dragotti, and D. Gündüz, Generative joint source-channel coding for semantic image transmission, IEEE Journal on Selected Areas in Communications, vol. 41, no. 8, pp. 2645-2657, 2023.
B Li, Y Liu, X Niu, B Bai, L Deng, D Gündüz, Extreme Video Compression with Pre-trained Diffusion Models, arXiv preprint arXiv:2402.08934, 2024.
S. F. Yilmaz, X. Niu, B. Bai, W. Han, L. Deng, and D. Gunduz High perceptual quality wireless image delivery with denoising diffusion models, arXiv:2309.15889v1, Sep. 2023.
J. Chen, D. You, D. Gündüz, and P. L. Dragotti, CommIN: Semantic image communications as an inverse problem with INN-guided diffusion models, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seoul, Republic of Korea, Apr. 2024.
W Yang, Z Xiong, Y Yuan, W Jiang, TQS Quek, M Debbah, Agent-driven Generative Semantic Communication for Remote Surveillance, arXiv preprint arXiv:2404.06997, 2024
Y Liu, H Du, D Niyato, J Kang, Z Xiong, S Mao, P Zhang, X Shen, Cross-Modal Generative Semantic Communications for Mobile AIGC: Joint Semantic Encoding and Prompt Engineering, arXiv preprint arXiv:2404.13898, 2024
G Liu, H Du, D Niyato, J Kang, Z Xiong, DI Kim, X Shen, Semantic communications for artificial intelligence generated content (AIGC) toward effective content creation, IEEE Network, 2024
C Liang, H Du, Y Sun, D Niyato, J Kang, D Zhao, MA Imran, Generative AI-driven semantic communication networks: Architecture, technologies and applications, arXiv preprint arXiv:2401.00124, 2023
R Cheng, Y Sun, D Niyato, L Zhang, L Zhang, MA Imran, A Wireless AI-Generated Content (AIGC) Provisioning Framework Empowered by Semantic Communication, arXiv preprint arXiv:2310.17705, 2023
Y Lin, Z Gao, H Du, D Niyato, J Kang, A Jamalipour, XS Shen, A unified framework for integrating semantic communication and AI-generated content in metaverse, IEEE Network, 2023
L Xia, Y Sun, C Liang, L Zhang, MA Imran, D Niyato, Generative AI for semantic communication: Architecture, challenges, and outlook, arXiv preprint arXiv:2308.15483, 2023
F Ni, B Wang, R Li, Z Zhao, H Zhang, Interplay of Semantic Communication and Knowledge Learning, arXiv preprint arXiv:2402.03339, 2024
F Jiang, Y Peng, L Dong, K Wang, K Yang, C Pan, X You, Large Generative Model Assisted 3D Semantic Communication, arXiv preprint arXiv:2403.05783, 2023
F Jiang, Y Peng, L Dong, K Wang, K Yang, C Pan, X You, Large AI model empowered multimodal semantic communications, arXiv preprint arXiv:2309.01249, 2023
F Jiang, Y Peng, L Dong, K Wang, K Yang, C Pan, X You, Large AI model-based semantic communications, arXiv preprint arXiv:2307.03492, 2023
P Jiang, CK Wen, X Yi, X Li, S Jin, J Zhang, Semantic Communications using Foundation Models: Design Approaches and Open Issues, arXiv preprint arXiv:2309.13315, 2024
L Qiao, MB Mashhadi, Z Gao, CH Foh, P Xiao, M Bennis, Latency-Aware Generative Semantic Communications with Pre-Trained Diffusion Models, arXiv preprint arXiv:2403.17256, 2024
J Choi, J Park, SW Ko, J Choi, M Bennis, SL Kim, Semantics Alignment via Split Learning for Resilient Multi-User Semantic Communication, arXiv preprint arXiv:2310.09394, 2023
S Tang, Q Yang, D Gündüz, Z Zhang, Evolving Semantic Communication with Generative Model, arXiv preprint arXiv:2403.20237, 2024
Lee J H, Lee D H, Sheen E, et al. Seq2Seq-SC: End-to-end semantic communication systems with pre-trained language model, 57th Asilomar Conference on Signals, Systems, and Computers. IEEE, 2023: 260-264
S. Tariq, U. Khalid, B. E. Arfeto, T. Q. Duong, H. Shin, Integrating Sustainable Big AI: Quantum Anonymous Semantic Broadcast, IEEE Wireless Communications, vol. 31, no. 3, pp. 86-99, 2024
Y. Zhao, Y. Yue, S. Hou, B. Cheng, Y. Huang, LaMoSC: Large Language Model-Driven Semantic Communication System for Visual Transmission, IEEE Transactions on Cognitive Communications and Networking, 2024
Zhixiang Yang, Hongyang Du, Dusit Niyato, Xudong Wang, Yu Zhou, Lei Feng, Fanqin Zhou, Wenjing Li, Xuesong Qiu, Revolutionizing Wireless Networks with Self-Supervised Learning: A Pathway to Intelligent Communications, arXiv:2406.06872, Jun. 2024
W. Yang, Z. Xiong, Tony Q. S. Quek, and X. S. Shen, Streamlined Transmission: A Semantic-Aware XR Deployment Framework Enhanced by Generative AI, IEEE Network (Early Access), June 2024
H. Du, J. Wang, D. Niyato, J. Kang, Z. Xiong, and D. I. Kim, AI-Generated Incentive Mechanism and Full-duplex Semantic Communications for Information Sharing, IEEE Journal on Selected Areas in Communications, vol. 41, no. 9, pp. 2981-2997, September 2023
Z. Jiang, X. Liu, G. Yang, W. Li, A. Li, and G. Wang, DIFFSC: Semantic Communication Framework With Enhanced Denoising Through Diffusion Probabilistic Models, in Proc.IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), March 2024
9. Integration of Large Generative AI and Sensing
Guoxuan Chi, Zheng Yang, Chenshu Wu, Jingao Xu, Yuchong Gao, Yunhao Liu, and Tony Xiao Han. RF-Diffusion: Radio Signal Generation via Time-Frequency Diffusion. In Proceedings of the 30th Annual International Conference on Mobile Computing and Networking (ACM MobiCom’24), New York, NY, USA, 77–92.
J Wang, H Du, D Niyato, Z Xiong, J Kang, B Ai, Z Han, DI Kim, Generative Artificial Intelligence Assisted Wireless Sensing: Human Flow Detection in Practical Communication Environments, arXiv preprint arXiv:2404.14140, 2024
J Wang, H Du, D Niyato, J Kang, S Cui, X Shen, P Zhang, Generative AI for integrated sensing and communication: Insights from the physical layer perspective, arXiv preprint arXiv:2310.01036, 2023
10. Protocol Learning and Design using Large Generative AI
H. Zou, Q. Zhao, Y. Tian, L. Bariah, F. Bader, T. Lestable, and M. Debbah, TelecomGPT: A framework to build telecom-specific large language models.
Jiawei Shao, Jingwen Tong, Qiong Wu, Wei Guo, Zijian Li, Zehong Lin, and Jun Zhang, “WirelessLLM: Empowering large language models towards wireless intelligence,” arxiv preprint arxiv: 2405.17053, 2024.
Roychowdhury S, Jain N, Soman S. Unlocking Telecom Domain Knowledge Using LLMs, 16th International Conference on COMmunication Systems & NETworkS (COMSNETS). IEEE, 2024: 267-269.
L Bariah, H Zou, Q Zhao, B Mouhouche, F Bader, M Debbah, Understanding telecom language through large language models, IEEE Global Communications Conference, 6542-6547, 2023
Y Huang, M Xu, X Zhang, D Niyato, Z Xiong, S Wang, T Huang, AI-Generated Network Design: A Diffusion Model-based Learning Approach, IEEE Network, 2023
Y Huang, M Xu, X Zhang, D Niyato, Z Xiong, S Wang, T Huang, AI-Generated 6G Internet Design: A Diffusion Model-based Learning Approach, arXiv preprint arXiv:2303.13869, 2023
Long He, Geng Sun, Dusit Niyato, Hongyang Du, Fang Mei, Jiawen Kang, Mérouane Debbah, Generative AI for Game Theory-based Mobile Networking, arXiv preprint arXiv:2404.09699, 2024
J Park, SW Ko, J Choi, SL Kim, M Bennis, Towards semantic communication protocols for 6G: From protocol learning to language-oriented approaches, arXiv preprint arXiv:2310.09506, 2023
Athanasios Karapantelakis, Mukesh Thakur, Alexandros Nikou, Farnaz Moradi, Christian Olrog, Fitsum Gaim, Henrik Holm, Doumitrou Daniil Nimara, Vincent Huang. Using Large Language Models to Understand Telecom Standards. 2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN)
11. Deployment, Training, and Inference of Large Models over Networked Environments
J. Tirana, D. Tsigkari, G. Iosifidis, and D. Chatzopoulos, Workflow optimization for parallel split learning.
H Cui, Y Du, Q Yang, Y Shao, SC Liew, LLMind: Orchestrating AI and IoT with LLMs for complex task execution, arXiv preprint arXiv:2312.09007, 2023.
Y. Chen, R. Li, Z. Zhao, C. Peng, J. Wu, E. Hossain, H. Zhang, NetGPT: An AI-Native Network Architecture for Provisioning Beyond Personalized Generative Services, IEEE Network, 2024
W. Zhang, D. Yang, C. Zhang, Q. Ye, H. Zhang, X. Shen, (Com)2Net: A Novel Communication and Computation Integrated Network Architecture, IEEE Network, 2024
F Jiang, L Dong, S Tu, Y Peng, K Wang, K Yang, C Pan, D Niyato, Personalized Wireless Federated Learning for Large Language Models, arXiv preprint arXiv:2404.13238, 2024
H Zou, Q Zhao, L Bariah, Y Tian, M Bennis, S Lasaulce, M Debbah, GenAINet: Enabling Wireless Collective Intelligence via Knowledge Transfer and Reasoning, arXiv preprint arXiv:2402.16631, 2024
H Zou, Q Zhao, L Bariah, M Bennis, M Debbah, Wireless multi-agent generative AI: From connected intelligence to collective intelligence, arXiv preprint arXiv:2307.02757, 2023
J Wang, H Du, D Niyato, J Kang, Z Xiong, D Rajan, S Mao, X Shen, A unified framework for guiding generative AI with wireless perception in resource constrained mobile edge networks, IEEE Transactions on Mobile Computing, 2024
Hongyang Du, Ruichen Zhang, Dusit Niyato, Jiawen Kang, Zehui Xiong, Dong In Kim, Xuemin Sherman Shen, H Vincent Poor, Exploring collaborative distributed diffusion-based AI-generated content (AIGC) in wireless networks, IEEE Network, 2023
M Xu, D Niyato, H Zhang, J Kang, Z Xiong, S Mao, Z Han, Sparks of GPTs in edge intelligence for metaverse: caching and inference for mobile AIGC services, arXiv preprint arXiv:2304.08782, 2023
H Du, Z Li, D Niyato, J Kang, Z Xiong, DI Kim, Enabling AI-generated content (AIGC) services in wireless edge networks, arXiv preprint arXiv:2301.03220, 2023
Xumin Huang, Peichun Li, Hongyang Du, Jiawen Kang, Dusit Niyato, Dong In Kim, Yuan Wu, Federated Learning-Empowered AI-Generated Content in Wireless Networks, IEEE Network, 2024
R Ma, J Wang, Q Qi, X Yang, H Sun, Z Zhuang, J Liao, PipeLLM: Pipeline LLM Inference on Heterogeneous Devices with Sequence Slicing, Proceedings of the ACM SIGCOMM 2023 Conference, 1126-1128, 2023
X Yang, D Chen, Q Qi, J Wang, H Sun, J Liao, S Guo, Adaptive DNN Surgery for Selfish Inference Acceleration with On-demand Edge Resource, arXiv preprint arXiv:2306.12185, 2023
M Xu, N Dusit, J Kang, Z Xiong, S Mao, Z Han, DI Kim, KB Letaief, When Large Language Model Agents Meet 6G Networks: Perception, Grounding, and Alignment, arXiv preprint arXiv:2401.07764, 2024
Tarkoma S, Morabito R, Sauvola J. AI-native Interconnect Framework for Integration of Large Language Model Technologies in 6G Systems. arXiv preprint arXiv:2311.05842, 2023
J. Du, T. Lin, C. Jiang, Q. Yang, C. F. Bader, and Z. Han, Distributed Foundation Models for Multi-Modal Learning in 6G Wireless Networks, IEEE Wireless Communications, vol. 31, no. 3, pp. 20-30, 2024
Z. Chen, H. Yang, T.C. Tay, K. Chong, and T. Q. S. Quek, The Role of Federated Learning in a Wireless World with Foundation Models, IEEE Wireless Communications, vol. 31, no. 3, pp. 42-49, 2024
H. Wu, X. Chen, and K. Huang, Device-Edge Cooperative Fine-Tuning of Foundation Models as a 6G Service, IEEE Wireless Communications, vol. 31, no. 3, pp. 60-67, 2024
S. Xu, C. Thomas, O. Hashash, M. Muralidhar, W. Saad, N. Ramakrishnan, Large Multi-Modal Models (LMMs) as Universal Foundation Models for AI-Native Wireless Systems. IEEE Network, vol. 38, no. 5, 2024
Yuqing Tian, Zhaoyang Zhang, Yuzhi Yang, Zirui Chen, Zhaohui Yang, Richeng Jin, Tony Q. S. Quek, Kai-Kit Wong, An Edge-Cloud Collaboration Framework for Generative AI Service Provision With Synergetic Big Cloud Model and Small Edge Models. IEEE Network, vol. 38, no. 5, 2024
C. Han, T. Yang, X. Sun, and Z. Cui, Harnessing Small AI Model Collaboration and Debate Mechanisms in 6G Networks: Distributed Architectures and Layered Privacy Protection. IEEE ICC, 2024
K. Gao, Y. Chai, Y. Li, Z. Zhang, L. Lu, Q. Li, Y. Zhang, Accelerating Distributed Model Training through Intelligent Node Selection and Data Allocation Strategies in 6G network, IEEE ICC Workshops, 2024
W. Wu, M. Li, K. Qu, C. Zhou, X. Shen, W. Zhuang, X. Li, W. Shi, Split Learning Over Wireless Networks: Parallel Design and Resource Management, IEEE Journal on Selected Areas in Communications, vol. 41, no. 4, 2023
S. Tuli, G. Casale, and N. R. Jennings, SplitPlace: AI Augmented Splitting and Placement of Large-Scale Neural Networks in Mobile Edge Environments, IEEE Transactions on Mobile Computing, vol. 22, no. 9, 2023
Haifeng Wen, Hong Xing, Osvaldo Simeone, Pre-Training and Personalized Fine-Tuning via Over-the-Air Federated Meta-Learning:Convergence-Generalization Trade-Offs, arXiv:2406.11569, Sep. 2024
12. Emerging Applications Driven by Large Generative AI
Z. Tao, W. Xu, Y. Huang, X. Wang, and X. You, Wireless network digital twin for 6G: Generative AI as a key enabler, IEEE Wireless Communications, vol. 31, no. 4, pp. 24-31, Aug. 2024.
J Wang, H Du, D Niyato, Z Xiong, J Kang, S Mao, XS Shen, Guiding AI-generated digital content with wireless perception, IEEE Wireless Communications, 2024
N Sehad, L Bariah, W Hamidouche, H Hellaoui, R Jäntti, M Debbah, Generative AI for Immersive Communication: The Next Frontier in Internet-of-Senses Through 6G, arXiv preprint arXiv:2404.01713, 2024
L Bariah, M Debbah, The interplay of AI and digital twin: Bridging the gap between data-driven and model-driven approaches, IEEE Wireless Communications, 2024
R Zhang, H Du, Y Liu, D Niyato, J Kang, Z Xiong, A Jamalipour, DI Kim, Interactive Generative AI Agents for Satellite Networks through a Mixture of Experts Transmission, arXiv preprint arXiv:2404.09134, 2024
M Xu, D Niyato, H Zhang, J Kang, Z Xiong, S Mao, Z Han, Cached Model-as-a-Resource: Provisioning Large Language Model Agents for Edge Intelligence in Space-air-ground Integrated Networks, arXiv preprint arXiv:2403.05826, 2024
J Chen, C Yi, H Du, D Niyato, J Kang, J Cai, X Shen, A revolution of personalized healthcare: Enabling human digital twin with mobile AIGC, IEEE Network, 2024
J Chen, Y Shi, C Yi, H Du, J Kang, D Niyato, Generative AI-Driven Human Digital Twin in IoT-Healthcare: A Comprehensive Survey, arXiv preprint arXiv:2401.13699, 2024
M Xu, D Niyato, J Kang, Z Xiong, S Guo, Y Fang, DI Kim, Generative AI-enabled Mobile Tactical Multimedia Networks: Distribution, Generation, and Perception, arXiv preprint arXiv:2401.06386, 2024
Y. Du, S. C. Liew, K. Chen, Y. Shao, The power of large language models for wireless communication system development: A case study on FPGA platforms, arXiv:2307.07319, 2023
W. Zhang, N. Tang, D. Yang, R. Guo, H. Zhang, and X. Shen, Det(Com)2: Deterministic Communication and Computation Integration Toward AIGC Services, IEEE Wireless Communications, vol. 31, no. 3, pp. 32-41, 2024
Z. Chen, Q. Sun, N. Li, X. Li, Y. Wang, and C.-L. I. Enabling mobile AI agent in 6G era: Architecture and key technologies, IEEE Network, vol. 38, no. 5, pp. 66-75. 2024
Y. Rong, Y. Mao, H. Cui, X. He, and M. Chen, Edge Computing Enabled Large-Scale Traffic Flow Prediction With GPT in Intelligent Autonomous Transport System for 6G Network, IEEE Transactions on Intelligent Transportation Systems, 2024
R. Zhang, H. Du, Y. Liu, D. Niyato, J. Kang, Z. Xiong, A. Jamalipour, D. I. Kim, Generative AI Agents with Large Language Model for Satellite Networks via a Mixture of Experts Transmission, IEEE JSAC, 2024
S. Havaid, H. Fahim, B. He, N. Saeed, Large Language Models for UAVs: Current State and Pathways to the Future, IEEE Open Journal of Vehicular Technology, 2024
G. Xie, Z. Xiong, X. Zhang, R. Xie, S. Guo, M. Guizani, and H. V. Poor, GAI-IoV: Bridging Generative AI and Vehicular Networks for Ubiquitous Edge Intelligence, IEEE Transactions on Wireless Communications, May 2024
Q. Liu, J. Mu, D. Chen, R. Zhang, Y. Liu, and Tao Hong, LLM Enhanced Reconfigurable Intelligent Surface for Energy-Efficient and Reliable 6G IoV, IEEE Transactions on Vehicular Technology, May 2024
J. Zheng, B. Du, H. Du, J. Kang, D. Niyato, and H. Zhang, Energy-Efficient Resource Allocation in Generative AI-Aided Secure Semantic Mobile Networks, IEEE Transactions on Mobile Computing, May 2024
13. Large AI Models and Blockchain
CT Nguyen, Y Liu, H Du, DT Hoang, D Niyato, DN Nguyen, S Mao, Generative AI-enabled Blockchain Networks: Fundamentals, Applications, and Case Study, arXiv preprint arXiv:2401.15625, 2024
Y. Liu, H. Du, D. Niyato, J. Kang, Z. Xiong, C. Miao, X. S. Shen, and A. Jamalipour, Blockchain-empowered Lifecycle Management for AI-generated Content Products in Edge Networks, IEEE Wireless Communications, vol. 31, no. 3, pp. 286-294, June 2024
S. B. Balija, A. Nanda, and D. Sahoo, Building Communication Efficient Asynchronous Peer-to-Peer Federated LLMs with Blockchain, in Proc. the AAAI Symposium Series, vol. 3, no. 1, pp. 288-292. May 2024
Y. Lin, H. Du, D. Niyato, J. Nie, J. Zhang, Y. Cheng, and Z. Yang, Blockchain-Aided Secure Semantic Communication for AI-Generated Content in Metaverse, IEEE Open Journal of the Computer Society, vol. 4, pp. 72-83, March 2023
B. Chen, G. Li, X. Lin, Z. Wang, and J. Li, BlockAgents: Towards Byzantine-Robust LLM-Based Multi-Agent Coordination via Blockchain, in Proc. the ACM Turing Award Celebration Conference, July 2024
14. Security, Privacy, and Resilience Aspects
Haomiao Yang, Kunlan Xiang, Mengyu Ge, Hongwei Li, Rongxing Lu, Shui Yu, A Comprehensive Overview of Backdoor Attacks in Large Language Models within Communication Networks, IEEE Network, 2024
Mohamed Amine Ferrag, Mthandazo Ndhlovu, Norbert Tihanyi, Lucas C Cordeiro, Merouane Debbah, Thierry Lestable, Narinderjit Singh Thandi, Revolutionizing Cyber Threat Detection with Large Language Models: A privacy-preserving BERT-based Lightweight Model for IoT/IIoT Devices, IEEE Access, 2024
MA Ferrag, A Battah, N Tihanyi, M Debbah, T Lestable, LC Cordeiro, Securefalcon: The next cyber reasoning system for cyber security, arXiv preprint arXiv:2307.06616, 2023
C Zhao, H Du, D Niyato, J Kang, Z Xiong, DI Kim, KB Letaief, Generative AI for Secure Physical Layer Communications: A Survey, arXiv preprint arXiv:2402.13553, 2024
H Du, D Niyato, J Kang, Z Xiong, KY Lam, Y Fang, Y Li, Spear or shield: Leveraging generative AI to tackle security threats of intelligent network services, arXiv preprint arXiv:2306.02384, 2023
J Wang, Y Li, Q Qi, Y Lu, B Wu, Multilayered Fault Detection and Localization With Transformer for Microservice Systems, IEEE Transactions on Reliability, 2024
S. M. Hasan, A. Alotaibi, S. Talukder, and A. R. Shahid, Distributed Threat Intelligence at the Edge Devices: A Large Language Model-Driven Approach. 2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC)
M. Ferrag, M. Ndhlovu, N. Tihany, et. al., Revolutionizing Cyber Threat Detection With Large Language Models: A Privacy-Preserving BERT-Based Lightweight Model for IoT/IIoT Devices, IEEE Access, 2024
15. Dataset, Demos, and Prototypes
A Maatouk, F Ayed, N Piovesan, A De Domenico, M Debbah, ZQ Luo, Teleqna: A benchmark dataset to assess large language models telecommunications knowledge, arXiv preprint arXiv:2310.15051, 2023
