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Generative Artificial Intelligence (GAI) possesses the capabilities of generating realistic data and facilitating advanced decision-making.
N. C. Luong, D. T. Hoang, P. Wang, D. Niyato, D. I. Kim, and Z. Han, “Data collection and wireless communication in Internet of Things (IoT) using economic analysis and pricing models: A survey,” IEEE Communications Surveys & Tutorials , vol. 18, no. 4, pp. 2546–2590, 2016
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J. Kang, Z. Xiong, D. Niyato, D. Ye, D. I. Kim, and J. Zhao, “Toward secure blockchain-enabled Internet of Vehicles: Optimizing consensus management using reputation and contract theory,” IEEE Transactions on Vehicular Technology , vol. 68, no. 3, pp. 2906–2920, 2019
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X. Zhang, D. Guo, K. An, G. Zheng, S. Chatzinotas, and B. Zhang, “Auction-based multichannel cooperative spectrum sharing in hybrid satellite-terrestrial IoT networks,” IEEE Internet of Things Journal , vol. 8, no. 8, pp. 7009–7023, 2020
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D. C. Nguyen, M. Ding, P. N. Pathirana, A. Seneviratne, J. Li, D. Niyato, O. Dobre, and H. V. Poor, “6G Internet of Things: A comprehensive survey,” IEEE Internet of Things Journal , vol. 9, no. 1, pp. 359–383, 2022
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J. Wen, J. Kang, M. Xu, H. Du, Z. Xiong, Y. Zhang, and D. Niyato, “Freshness-aware incentive mechanism for mobile AI-Generated Content (AIGC) networks,” in 2023 IEEE/CIC International Conference on Communications in China (ICCC) . IEEE, 2023, pp. 1–6
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Y. Zhong, J. Wen, J. Zhang, J. Kang, Y. Jiang, Y. Zhang, Y. Cheng, and Y. Tong, “Blockchain-assisted twin migration for vehicular metaverses: A game theory approach,” Transactions on Emerging Telecommunications Technologies , p. e4856, 2023
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