Cell-free massive multiple-input multiple-output (MIMO) systems can provide uniformly strong service through distributed access points, but performance still depends critically on downlink power control. Existing methods are typically selected offline and then applied uniformly across channel and load regimes, even though no single solver is uniformly best. We therefore propose VISO-PC, a verifier-in-the-loop solver-orchestration framework in which an agent routes among trusted solvers rather than generating power coefficients directly. Given a structured instance descriptor, the router selects an initial solver and fallback order, and an independent verifier accepts only candidates that satisfy the constraints and produce a valid verified common rate. For fairness-oriented downlink cell-free power control under per-AP constraints, verification-aware orchestration improves accepted rate over all fixed single-solver baselines on a reproducible prototype benchmark. Moreover, a lightweight memory-based router matches the accepted rate of a strong rule-based router while reducing average runtime and fallback rate. These results show that solver orchestration is a practical agentic layer for cell-free massive MIMO downlink power control.

翻译：无蜂窝大规模多输入多输出（MIMO）系统可通过分布式接入点提供均匀的强服务，但其性能仍关键取决于下行功率控制。现有方法通常离线选定求解器后，跨信道与负载场景统一应用，尽管没有任何单一求解器在所有场景中均表现最优。为此，我们提出VISO-PC——一种验证器在环的求解器编排框架，其中智能体在可信求解器之间进行路由选择，而非直接生成功率系数。给定结构化实例描述后，路由模块选择初始求解器及回滚顺序，独立验证器仅接受满足约束条件并产生有效已验证共同速率的候选解。针对每接入点约束下的公平性导向无蜂窝下行功率控制问题，在可复现原型基准测试中，验证感知编排策略在所有固定单一求解器基线方法之上提升了被接受速率。此外，轻量级记忆路由模块在保持强规则路由模块同等被接受速率的同时，降低了平均运行时间与回滚率。实验结果表明，求解器编排可作为无蜂窝大规模MIMO下行功率控制的一种实用智能体层。