用大模型辅助调度，让Wi-Fi和5G共存时更省电且公平。
LLM Assisted Alpha Fairness for 6 GHz WiFi and NR_U Coexistence: An Agentic Orchestrator for Throughput, Energy, and SLA
- 大模型分析设备状态，提出可解释的调度参数
- 在保持吞吐量的前提下，能耗降低35.3%，能效提升12.2%
- 适合需要透明、安全、可审计的无线共存系统
未授权6GHz频段正成为高容量接入的主要手段，Wi-Fi与5G NR-U在听前讲（LBT）规则下争夺相同信道。在此场景中，需同时权衡吞吐量、能耗与服务等级目标，且保证安全与可审计性。本文提出一种代理式控制器，将策略与执行分离：每个调度周期初，代理汇总遥测数据（每信道忙闲、基础LBT失败率；每用户信道质量、队列长度、延迟、电池状态、优先级、功耗模式），并调用大语言模型（LLM）生成一组可解释的控制参数：公平性指数α、各信道对Wi-Fi/NR-U的占空比上限及类别权重。随后由确定性优化器确保可行性，并计算内化了LBT损耗与能耗成本的α公平分配；异常或不安全策略被截断并回退至规则基线。在含两个160MHz信道、混合用户类型的6GHz仿真环境中，基于LLM的策略持续提升能效，同时保持吞吐量竞争力。一个LLM使总能耗降低35.3%，另一个实现最佳综合表现，总传输比特数提升3.5%，单位焦耳传输比特数提升12.2%。我们开源代码、每周期日志与绘图工具，可复现全部图表与数据，展示政策级大模型指导如何安全提升无线共存性能。
原文摘要 · Abstract (English)
Unlicensed 6GHz is becoming a primary workhorse for high-capacity access, with Wi-Fi and 5G NR-U competing for the same channels under listen-before-talk (LBT) rules. Operating in this regime requires decisions that jointly trade throughput, energy, and service-level objectives while remaining safe and auditable. We present an agentic controller that separates {policy} from {execution}. At the start of each scheduling epoch the agent summarizes telemetry (per-channel busy and baseline LBT failure; per-user CQI, backlog, latency, battery, priority, and power mode) and invokes a large language model (LLM) to propose a small set of interpretable knobs: a fairness index α, per-channel duty-cycle caps for Wi-Fi/NR-U, and class weights. A deterministic optimizer then enforces feasibility and computes an α-fair allocation that internalizes LBT losses and energy cost; malformed or unsafe policies are clamped and fall back to a rule baseline. In a 6GHz simulator with two 160MHz channels and mixed Wi-Fi/NR-U users, LLM-assisted policies consistently improve energy efficiency while keeping throughput competitive with a strong rule baseline. One LLM lowers total energy by 35.3% at modest throughput loss, and another attains the best overall trade-off, finishing with higher total bits (+3.5%) and higher bits/J (+12.2%) than the baseline. We release code, per-epoch logs, and plotting utilities to reproduce all figures and numbers, illustrating how transparent, policy-level LLM guidance can safely improve wireless coexistence.
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