Strategic Bidding in 6G Spectrum Auctions with Large Language Models
Efficient and fair spectrum allocation is a central challenge in 6G networks, where massive connectivity and heterogeneous services continuously compete for limited radio resources. We investigate the use of Large Language Models (LLMs) as bidding agents in repeated 6G spectrum auctions with budget constraints in vehicular networks. Each user equipment (UE) acts as a rational player optimizing its long-term utility through repeated interactions. Using the Vickrey-Clarke-Groves (VCG) mechanism as a benchmark for incentive-compatible, dominant-strategy truthfulness, we compare LLM-guided bidding against truthful and heuristic strategies. Unlike heuristics, LLMs leverage historical outcomes ...
| Authors | Ismail Lotfi, Ali Ghrayeb |
|---|---|
| Primary category | cs.GT |
| Published | 27 April 2026 |
| Last updated at source | 27 April 2026 |
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