| 研究生: |
吳恩綺 WU, EN-CHI |
|---|---|
| 論文名稱: |
AI 動態頻譜共享情境下之頻譜釋出、拍賣與監管機制 Spectrum Allocation, Auction, and Regulatory Mechanisms under AI-Enabled Dynamic Spectrum Sharing |
| 指導教授: |
陳文字
CHEN, WEN-TZU |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 電信管理研究所 Institute of Telecommunications Management |
| 論文出版年: | 2026 |
| 畢業學年度: | 114 |
| 語文別: | 中文 |
| 論文頁數: | 98 |
| 中文關鍵詞: | 人工智慧 、動態頻譜共享 、頻譜管理 、頻譜發照制度 、頻譜治理 |
| 外文關鍵詞: | Artificial Intelligence, Dynamic Spectrum Sharing, Spectrum Management, Spectrum Licensing, Spectrum Governance |
| 相關次數: | 點閱:3 下載:0 |
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因應無線通訊技術快速演進,頻譜資源需求持續攀升,傳統以固定專屬方式分配頻譜之制度已難以因應未來6G及萬物聯網情境下高密度與即時調度需求。為提升頻譜使用效率與政策彈性,動態頻譜共享(Dynamic Spectrum Sharing, DSS)逐漸成為重要發展方向,結合人工智慧(Artificial Intelligence, AI)技術進行即時配置與干擾管理,更被視為關鍵解方。
本研究在AI動態頻譜共享成功應用之情境下,探討未來頻譜釋出方式、拍賣制度設計及監管機制之調整方向。透過主題分析與專家訪談,建構制度分析框架,並評估不同政策工具在共享情境下之適用性與互動關係。
研究結果顯示,在6G頻譜共享架構下,整體制度呈現技術可行、制度可建、但市場受限之特徵。技術上,AI與動態頻譜共享已具備支撐即時管理之能力;制度上,現行法規具備調整空間;然而在市場面,業者因競爭與投資誘因不足,對共享機制之採用仍具高度不確定性。
基於上述發現,本研究提出「審議為主、投標為輔」之混合發照制度,透過制度化評分機制進行資源配置,並於高度競爭情境下輔以市場機制作為補充,以兼顧效率與公平。同時建議採取漸進式政策推動路徑,由低干擾場域試辦,逐步建立共享資料庫與AI監管機制,並透過誘因設計促進制度落地。
As sixth-generation (6G) mobile communication technologies advance, traditional exclusive and static spectrum allocation mechanisms are increasingly challenged by spectrum scarcity, inefficient utilization, and real-time service demands. Dynamic Spectrum Sharing (DSS), supported by Artificial Intelligence (AI), has emerged as a potential approach to improve spectrum efficiency, enable dynamic coordination, and enhance interference management. This study examines spectrum release methods, auction mechanism design, and regulatory frameworks under an AI-enabled dynamic spectrum sharing environment.
This research adopts thematic analysis and expert interviews to construct an institutional analysis framework for future spectrum governance. The findings indicate that AI-enabled DSS is technically feasible and institutionally constructible, but remains constrained by market incentives. While AI can support near-real-time monitoring, interference prediction, and dynamic resource allocation, incumbent operators may lack sufficient incentives to participate in sharing due to high spectrum acquisition costs, investment recovery concerns, and competitive considerations.
Based on these findings, this study proposes a hybrid licensing framework characterized by “deliberation as the primary mechanism and bidding as a supplementary mechanism.” It also recommends a gradual implementation pathway, beginning with low-interference pilot areas, followed by the development of shared spectrum databases, AI-based regulatory platforms, and market incentive mechanisms. These measures aim to support a more flexible, accountable, and efficient spectrum governance model for the 6G era..
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