摘要： 针对“经典-量子”异构融合系统中协同通信研究碎片化、模块耦合机理不明、缺乏统一分析框架的问题，本文从体系结构视角综述异构协同通信的技术现状、关键瓶颈与趋势。首先，以反馈闭环的时序耦合深度为本征维度，将协同模式归纳为开环前馈、变分迭代与实时闭环三类，按超导、光量子、离子阱、中性原子四类物理体系对照分析协同架构差异。其次，构建“经典-量子”双向数据流交互模型，将承载时序同步与门触发脉冲的控制流与承载测量结果的反馈流严格解耦，以量子纠错微秒级实时闭环为标尺量化交互约束。然后，按通信距离与部署形态将技术体系归纳为近端高频测控、分布式协同与量子云通信三类，比较FPGA室温测控、低温CMOS与单磁通量子三类近端测控架构的性能边界，揭示分布式协同由离线优化向动态协同演进，梳理“近量子计算”运行时优化与异构硬件抽象两条云通信路线。最后，从物理层时序、系统层带宽、算力层耦合与生态层标准四维度剖析瓶颈，以性能约束模型阐明带宽与解码算力耦合，给出优化路径与梯次。研究表明，量子门操作与经典通信存在3至6个数量级的时间尺度差，解码延迟约为纠错周期的57倍；万比特超导系统面临穿温区线缆超3万根、热负载超出4 K温区冷却能力一个数量级等互连难题；频分复用读取N个比特时，信噪比按√N比例退化；随着码距增大，带宽与解码算力出现耦合失衡，百万比特系统综合征上行带宽将达Tbps级。同时，私有协议加剧标准碎片化，测控成本呈超线性增长。研究认为，协同通信的本质在于反馈闭环的时序耦合深度，相关瓶颈需通过时序优化、跨层调度、技术协同和协议统一共同突破。为此，提出近期频分复用、中期片上路由、远期光互连的分阶段策略，端到端跨层优化将成为迈向百万比特级容错计算的关键。

Abstract: To address the fragmentation of cooperative-communication research in "classical-quantum" heterogeneous fusion systems—where the module-coupling mechanism remains unclear and a unified analytical framework is lacking—this paper reviews the technical status, key bottlenecks, and trends of heterogeneous cooperative communication from an architectural perspective. First, taking the timing-coupling depth of feedback loops as the essential dimension, we classify cooperative modes into three types: open-loop feedforward, variational iteration, and real-time closed-loop. Moreover, cooperative-architecture differences are comparatively analyzed across four physical systems, namely superconducting, photonic, trapped-ion, and neutral-atom. Second, a "classical-quantum" bidirectional data-flow interaction model is constructed. In this model, the control flow carrying timing synchronization and gate-trigger pulses is strictly decoupled from the feedback flow carrying measurement results, and the microsecond-level real-time closed-loop demand of quantum error correction serves as a benchmark to quantify the interaction constraints. Then, according to communication distance and deployment form, the technical system is organized into three categories: near-field high-frequency measurement and control, distributed cooperation, and quantum cloud communication. Specifically, the performance boundaries of three near-field control architectures—FPGA room-temperature control, cryogenic CMOS, and single-flux-quantum—are compared. In addition, the evolution of distributed cooperation from offline optimization toward dynamic cooperation is revealed, and two cloud-communication routes are outlined: "near-quantum computing" runtime optimization and heterogeneous hardware abstraction. Finally, the bottlenecks are dissected from four layers—physical-layer timing, system-layer bandwidth, computing-layer coupling, and ecosystem-layer standards. Here, a performance-constraint model is used to clarify the coupling between bandwidth and decoding computing power, thereby yielding optimization paths and evolution tiers. The study shows that a 3-to-6-order-of-magnitude time-scale gap exists between quantum gate operations and classical communication, and that the decoding latency is about 57 times the error-correction cycle period. For ten-thousand-qubit superconducting systems, moreover, interconnect challenges emerge: more than 30,000 cables cross the temperature zones, and the heat load exceeds the 4 K cooling capacity by an order of magnitude. In addition, when frequency-division multiplexing reads out N qubits, the signal-to-noise ratio degrades as the square root of N. Furthermore, as the code distance grows, bandwidth and decoding computing power fall into a coupled imbalance; consequently, the syndrome uplink bandwidth of a million-qubit system will reach the Tbps level. Meanwhile, proprietary protocols aggravate standard fragmentation, and measurement-and-control costs grow superlinearly. We therefore conclude that the essence of cooperative communication lies in the timing-coupling depth of feedback loops, and that the relevant bottlenecks must be broken through jointly via timing optimization, cross-layer scheduling, technology integration, and protocol unification. Accordingly, a phased strategy is proposed: frequency-division multiplexing for the near term, on-chip routing for the mid term, and optical interconnection for the long term. Ultimately, end-to-end cross-layer optimization will become the key to advancing toward million-qubit fault-tolerant computation.