Spectrum Auction Policy Design for International Mobile Telecommunications in South Korea: Application of Agent-Based Simulation
Source abstract
Abstract
Spectrum auctions in international mobile telecommunications (IMT) are a representative method for selling the right to transmit signals within a specific band of electromagnetic waves to communication service providers (CSPs); it is important to design a fair spectrum auction that can benefit both government and auction bidders. The government should reduce the burden of maintenance costs by setting a reasonable initial price and selling it to bidders at the highest price they can afford. However, due to the complex auction rules and decision-making process, not many studies has been conducted on how to select an appropriate initial price for the auction. This study aims at introducing a novel simulation modeling approach to develop a spectrum auction policy for international mobile telecommunications (IMT) using agent-based simulation (ABS), which involves three telecommunications service provider types (i.e., the Aggressive bidder, the Moderate bidder, and the Conservative bidder) and the auction environment of IMT in South Korea. In particular, the proposed approach adopts the exponential utility theory to model the behavior of auction bidders and identify the optimal initial bid price. The devised ABS model is calibrated to the IMT spectrum auction conducted in 2018 in South Korea, and the best initial pricing policy identified (i.e., $85.24 million per spectrum block) regarding a sustainable market environment for existing service providers (i.e., 10 blocks for the Aggressive bidder, 10 blocks for the Moderate bidder, and 8 blocks for the Conservative bidder). The proposed approach will be beneficial to both government agencies and auction bidders under fair competition in the IMT market.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Auction Theory and Applications · ICT Impact and Policies · Consumer Market Behavior and Pricing
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Spectrum Network Strategy Research, Korea Information Society Development Institute, Jincheon-gun 27872, Republic of Korea
Department of Industrial and Systems Engineering, Dongguk University-Seoul, Seoul 04620, Republic of Korea
Funding
National Research Foundation of Korea (NRF)
References (38)
Show source-provided references
1. Putting auction theory to work: The simultaneous ascending auction10.1086/262118 ↗
2. Frontiers in spectrum auction design10.1016/j.ijindorg.2016.05.006 ↗
3. The Third Generation (3G) Auction in Asia
4. 3G licensing in Hong Kong: The debate10.1016/j.telpol.2003.12.006 ↗
5. Spectrum auctions in India: Lessons from experience10.1016/S0308-5961(01)00047-7 ↗
6. Why auction the spectrum?10.1016/0308-5961(94)00021-J ↗
7. Chouayakh, A., Bechler, A., Amigo, I., Nuaymi, L., and Maillé, P. (2018, January 9–12). PAM: A fair and truthful mechanism for 5G dynamic spectrum allocation. Proceedings of the 2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Bologna, Italy.10.1109/PIMRC.2018.8580859 ↗
8. Spectrum management policy options10.1109/COMST.1998.5340403 ↗
9. An overview of dynamic spectrum sharing: Ongoing initiatives, challenges, and a roadmap for future research10.1109/TCCN.2016.2592921 ↗
10. Bulow, J., Levin, J., and Milgrom, P. (2009). Winning Play in Spectrum Auctions (No. w14765), National Bureau of Economic Research.10.3386/w14765 ↗
11. On the clock of the combinatorial clock auction10.3982/TE3203 ↗
12. Islam, S., Ghosh, S., Raj, A., Singh, A.K., Swain, S., and Bandyopadhyay, A. (2024, January 6–8). Efficient Spectrum Allocation: A Simultaneous Multi Round Auction Approach. Proceedings of the 2024 3rd International Conference for Advancement in Technology (ICONAT), GOA, India.10.1109/ICONAT61936.2024.10775107 ↗
13. Zeroual, J., Akian, M., Bechler, A., Chardy, M., and Gaubert, S. (2024, January 8–10). Optimal Strategy against Straightforward Bidding in Clock Auctions. Proceedings of the International Conference on Network Games, Artificial Intelligence, Control and Optimization, Lille, France.10.1007/978-3-031-78600-6_8 ↗
14. Khadem, M., Zeinali, F., Mokari, N., and Saeedi, H. (2024, January 21–24). AI-enabled priority and auction-based spectrum management for 6G. Proceedings of the 2024 IEEE Wireless Communications and Networking Conference (WCNC), Dubai, United Arab Emirates.10.1109/WCNC57260.2024.10570588 ↗
15. A systematic approach for new service concept generation: Application of agent-based simulation10.1016/j.eswa.2013.10.012 ↗
16. An integrated agent-based simulation modeling framework for sustainable production of an Agrophotovoltaic system10.1016/j.jclepro.2023.138307 ↗
17. Purbasari, A., Zulianto, A., and Hidayanto, A.N. (2018, January 17–18). Revealed-preference activity rule in combinatorial clock spectrum auction: A review and new research opportunities. Proceedings of the 2018 IEEE Third International Conference on Informatics and Computing (ICIC), Palembang, Indonesia.10.1109/IAC.2018.8780558 ↗
18. Liu, S.Z., and Hwang, S.H. (2019, January 16). Survey on co-existence of 5G and satellite earth station in C-band. Proceedings of the Korean Institute of Communications and Information Sciences (KICS) Conference, Seoul, Republic of Korea.
19. New Zealand spectrum policy: A model for the United States?10.1086/467415 ↗
20. Basutli, B. (2016). Distributed Optimisation Techniques for Wireless Networks. [Ph.D. Thesis, Loughborough University].
21. Backus, M., Blake, T., Masterov, D.V., and Tadelis, S. (2015, January 18–22). Is sniping a problem for online auction markets?. Proceedings of the 24th International Conference on World Wide Web, Florence, Italy.10.1145/2736277.2741690 ↗
22. Spectrum auction design10.1007/s11151-013-9376-x ↗
23. Dimpfl, T., and Reining, A. (2021). Price Discovery and Learning during the German 5G Auction. J. Risk Financ. Manag., 14.10.3390/jrfm14060274 ↗
24. Do core-selecting combinatorial clock auctions always lead to high efficiency? An experimental analysis of spectrum auction designs10.1007/s10683-013-9350-3 ↗
25. Combinatorial clock auctions: Price direction and performance10.1016/j.geb.2019.07.001 ↗
26. (2025, January 07). The Ministry of Science and Information and Communications Technology. Announcement of the IMT Spectrum Auction (No. 2018-235), MIST. Available online: https://eiec.kdi.re.kr/policy/callDownload.do?num=176567&filenum=2.
27. Auctioning many divisible goods10.1162/154247604323068168 ↗
28. Strong activity rules for iterative combinatorial auctions10.1016/j.cor.2009.09.003 ↗
29. The German 4G spectrum auction: Design and behavior10.1111/ecoj.12406 ↗
30. Strange bids: Bidding behaviour in the United Kingdom’s third generation spectrum auction10.1111/j.1468-0297.2005.01008.x ↗
31. Properties of the combinatorial clock auction10.1257/aer.20141212 ↗
32. Risk aversion and auction design: Theoretical and empirical evidence10.1016/j.ijindorg.2021.102758 ↗
33. The First Spectrum Auction in Thailand: Lessons Learned and Achievements10.18178/joams.5.2.109-114 ↗
34. Exponential utility functions aid upstream decision making10.1016/j.jngse.2015.10.012 ↗
35. Multi-block ascending auctions for effective 5g licensed shared access10.1109/TMC.2021.3063990 ↗
36. Secondary spectrum allocation framework via concurrent auctions for 5G and beyond networks10.1007/s11276-022-02896-z ↗
37. Competing markets10.1016/S0014-2921(96)00063-3 ↗
38. Blees, J., Kemp, R., Maas, J., Mosselman, M., and May, Z. (2003). Barriers to Entry, The Open University. Zoetermeer, Scientific Analysis of Entrepreneurship and SMEs.