6G网络用统一记忆架构打通感知与推理，实现自主演化
Bridging the Cognitive Gap: A Unified Memory Paradigm for 6G Agentic AI-RAN
- 将生物记忆层级映射到异构计算资源，构建跨时序统一内存
- 支持微秒级反应、毫秒级推理与长期演化共享状态
- 适合研究6G自主智能网络的学者与工程师
随着6G发展，无线接入网需超越传统自动化，迈向具备感知、推理与演化能力的智能体。当前解耦架构存在根本性认知鸿沟：物理层接口迫使高维状态压缩为低维指标，导致推理智能体陷入语义瓶颈。本文提出从接口绑定转向内存中心的范式革新，将生物记忆层次结构映射至异构计算硬件。借助新兴相干互连技术，该方法构建了微秒级反射、毫秒级推理与长期演化的认知连续体，实现跨时间尺度的状态共享。通过零拷贝可观测性替代消息传递，赋能AI智能体弥合实时响应与长程上下文间的差距，推动真正自治的6G网络发展。
原文摘要 · Abstract (English)
As 6G evolves, the radio access network must transcend traditional automation to embrace agentic AI capable of perception, reasoning, and evolution. A fundamental cognitive gap persists in current disaggregated architectures, where interfaces force the physical layer to compress high-dimensional states into low-dimensional metrics, trapping reasoning agents behind a semantic bottleneck. This article envisions a shift from interface-bound to memory-centric architectures. We propose a unified memory paradigm that dissolves the boundaries between sensing and reasoning by mapping biological memory hierarchies onto heterogeneous computing fabrics. Enabled by emerging coherent interconnects, this approach creates a cognitive continuum where microsecond-level reflexes, millisecond-level reasoning, and long-term evolution share state across time scales. By replacing message passing with zero-copy observability, we empower AI agents to bridge the gap between real-time responsiveness and long-horizon context for truly autonomous 6G networks.
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