研究人员开发了两种新的基于扩散的方法用于无线通信中的多输入多输出（MIMO）检测。GD4是一种基于图的离散去噪扩散方法，直接在离散符号空间中操作，以实现更快的推理和在欠定系统中的性能提升。软图扩散Transformer（SGDiT）将检测重新构建为一个渐进式去噪过程，使用Transformer架构和交叉熵目标，以更好地与离散符号检测对齐。 AI
影响 引入了用于MIMO检测的新型基于扩散的技术，有可能提高无线通信的效率和准确性。
排序理由 两篇新的arXiv论文介绍了用于MIMO检测的新型基于扩散的方法。
AI 生成摘要 · Google Gemini · 来自 4 个来源。 我们如何撰写摘要 →
arXiv:2605.00423v1 Announce Type: new Abstract: In wireless communications, recovering the optimal solution to the multiple-input multiple-output (MIMO) detection problem is NP-hard. Obtaining high-quality suboptimal solutions with a favorable performance-complexity trade-off is …
arXiv:2605.00449v1 Announce Type: cross Abstract: Learning-based MIMO detection has shown strong empirical performance, yet existing methods typically rely on fixed-depth architectures without explicitly modeling the progressive refinement of symbol estimates. In this paper, we r…
Learning-based MIMO detection has shown strong empirical performance, yet existing methods typically rely on fixed-depth architectures without explicitly modeling the progressive refinement of symbol estimates. In this paper, we revisit MIMO detection from a flow matching perspec…
In wireless communications, recovering the optimal solution to the multiple-input multiple-output (MIMO) detection problem is NP-hard. Obtaining high-quality suboptimal solutions with a favorable performance-complexity trade-off is particularly challenging in under-determined sys…