多模态并发传输
Multi-Modal Concurrent Transmission
AI总结：
本文提出多模态并发传输（MMCT）物理层方法，通过在同一传输块内联合选择调制编码方案并映射到高信噪比空间频率资源，提升触觉互联网中多数据流传输的可靠性和频谱效率。
摘要：
本文提出了一种名为多模态并发传输（MMCT）的新型物理层方法，用于高效传输具有不同可靠性-延迟性能要求的多个数据流。MMCT将来自多个数据流的数据安排在同一物理层传输块内，其中结合了特定于流的调制和编码方案（MCS）选择，以及将调制码字联合映射到多输入多输出（MIMO）空间层和频率资源上。映射到具有更高信噪比（SNR）的空间频率资源为要求更高的数据流提供了所需的性能提升。在触觉互联网应用中，其中触觉反馈/驱动和音视频流并行流动，与传统的3GPP新空口（NR）传输方法相比，该方法提供了显著的SNR和频谱效率提升。
英文摘要：
This paper introduces a novel physical-layer method labelled as Multi-Modal Concurrent Transmission (MMCT) for efficient transmission of multiple data streams with different reliability-latency performance requirements. The MMCT arranges data from multiple streams within a same physical-layer transport block wherein stream-specific modulation and coding scheme (MCS) selection is combined with joint mapping of modulated codewords to Multiple-Input Multiple-Output spatial layers and frequency resources. Mapping to spatial-frequency resources with higher Signal-to-Noise Ratios (SNRs) provides the required performance boost for the more demanding streams. In tactile internet applications, wherein haptic feedback/actuation and audio-video streams flow in parallel, the method provides significant SNR and spectral efficiency enhancements compared to conventional 3GPP New Radio (NR) transmission methods.
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