Sample-and-Score：用代理模型优化 IEEE 802.11 协调空间复用
Sample-and-Score: Surrogate-Guided Coordinated Spatial Reuse in IEEE 802.11 Networks
WiFi 网络优化的新论文，不在线调参也能接近多臂老虎机的效果，做无线网络优化的人可以看看思路。
论文针对 IEEE 802.11bn 中协调空间复用（Co-SR）的配置组合爆炸问题，提出 sample-and-score 方法：随机采样 Co-SR 配置，用离线训练的代理模型打分并选最优。该代理模型无需在线微调或顺序探索即可部署，性能接近需要多步交互的多臂老虎机和启发式基线。在含 2-16 个接入点的未见拓扑上，它能恢复完美代理模型吞吐量的 52-77%。当候选配置达 8192 个时，理想的 sample-and-score 方法可达到吞吐量上限的 95%。
Sample-and-Score: Surrogate-Guided Coordinated Spatial Reuse in IEEE 802.11 Networks
Coordinated spatial reuse (Co-SR) in IEEE 802.11bn increases area throughput through simultaneous transmissions, yet the combinatorial configuration space makes real-time optimization challenging. We propose a sample-and-score approach: draw random Co-SR configurations, score each with a surrogate model, and select the best. The surrogate is trained offline and deployed without online fine-tuning or sequential exploration, yet performs close to multi-armed bandit and heuristic baselines that need multiple interaction steps or extensive measurements. On unseen topologies with 2-16 access points, it recovers 52-77% of a perfect surrogate's throughput. A perfect sample-and-score approach reaches 95% of the upper bound throughput with 8192 candidates.