通过监听驱动的非正交多址接入实现低反馈多用户网络中的延迟解耦
Latency Decoupling in Low-Feedback Multi-User Networks via Overhearing-Driven NOMA
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中文总结 AI 辅助
针对低反馈多用户网络问题，提出监听驱动的非正交多址接入（ONOMA）方案，集成随机线性网络编码与符号感知NOMA，利用监听和确认定时，有效解耦用户延迟，性能优于多种传统方案。
中文摘要 AI 辅助
传统无线协议如混合自动重传请求（HARQ）依赖频繁及时反馈，在非地面网络和大规模物联网等低反馈场景中不实用。在异构多用户系统中，单一弱用户可能主导整体完成延迟。我们提出监听驱动的非正交多址接入（ONOMA），一种新颖的跨层传输方案，无需发射机处的瞬时或统计信道状态信息（CSI）即可最小化延迟。ONOMA将随机线性网络编码（RLNC）与符号感知的NOMA集成，利用监听和确认定时。第一阶段用户监听RLNC传输，通过确认相对定时隐式推断信道强度排序；第二阶段符号重建实现强用户的无干扰解码，有效解耦用户延迟。基于确认定时的信道估计得出自适应功率分配策略。分析和仿真结果表明，ONOMA优于时分多址（TDMA）、多播、频分多址（FDMA）、会话间和经典NOMA，在两用户网络中完成时间最多减少34%，在更大的非对称网络中减少50%。
英文摘要
Conventional wireless protocols such as Hybrid Automatic Repeat Request (HARQ) rely on frequent and timely feedback, which becomes impractical in low-feedback regimes including non-terrestrial networks and massive IoT. This limitation is particularly critical in heterogeneous multi-user systems with unknown and asymmetric channels, where a single weak user can dominate the overall completion latency. We propose Overhearing-driven Non-Orthogonal Multiple Access (ONOMA), a novel cross-layer transmission scheme that minimizes latency without requiring instantaneous or statistical CSI at the transmitter. ONOMA integrates Random Linear Network Coding (RLNC) with symbol-aware NOMA and explicitly exploits overhearing and acknowledgment timing. In the first phase, users overhear RLNC transmissions, and the relative timing of acknowledgments is used to implicitly infer channel strength ordering. In the second phase, symbol reconstruction enables interference-free decoding for strong users, effectively decoupling user latencies. An adaptive power allocation policy is derived from acknowledgment timing-based channel estimates. Analytical and simulation results show that ONOMA outperforms TDMA, multicast, FDMA, inter-session, and classical NOMA, reducing completion time by up to 34% in two-user and 50% in larger asymmetric networks.
