LiTCom：一种用于6G上行链路的轻量级发射机和具备推理能力的接收机框架
LiTCom: A Lightweight Transmitter and Inference-Capable Receiver Framework for 6G Uplink
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中文总结 AI 辅助
研究针对6G上行链路低信噪比条件，提出LiTCom框架，发射机用基本低通滤波和最小信道编码简化设计，接收机用生成式人工智能模型，还开发功率分配策略，仿真验证其有效性，相比基线有信噪比增益且减少发射机端计算量。
中文摘要 AI 辅助
本文介绍了LiTCom，一种轻量级发射机和具备推理能力的接收机框架，旨在实现低信噪比条件下的稳健6G上行链路通信。它考虑了边缘设备与网络基础设施之间的资源不对称性。LiTCom通过应用基本低通滤波进行源编码和最小信道编码简化发射机设计，显著降低处理复杂度。接收机采用大规模生成式人工智能模型从传统解码能力之外的高度失真和降级信号中推断高语义保真度内容。此外，通过利用数据重要性开发高效功率分配策略以提高系统性能，用引入的体验质量指标衡量。仿真结果验证了LiTCom框架和轻量级编码设计的有效性。与类似5G NR的基线（使用JPEG源编码和LDPC信道编码）及Deep-JSCC基线相比，LiTCom分别实现高达8dB和2.5dB的信噪比增益，同时减少超过95%的发射机端计算量。
英文摘要
This paper introduces LiTCom, a lightweight transmitter and inference-capable receiver framework, designed to enable robust 6G uplink communication under low signal-to-noise (SNR) conditions. It embraces the resource asymmetry between edge devices and the network infrastructure. LiTCom simplifies transmitter design by applying basic low-pass filtering for source coding and minimal channel coding, significantly reducing the processing complexity. The receiver employs large-scale generative artificial intelligence (GenAI) models to infer high semantic-fidelity content from highly distorted and degraded signals beyond traditional decoding capabilities. Furthermore, efficient power allocation strategies are developed by exploiting data importance to improve system performance, which is measured by the introduced quality of experience (QoE) metric. Simulation results validate the effectiveness of the proposed LiTCom framework and the lightweight coding design. Compared with the 5G NR-like baseline (using JPEG source coding and LDPC channel coding) and the Deep-JSCC baseline, LiTCom achieves SNR gains up to 8 dB and 2.5 dB, respectively, while reducing over 95% transmitter-side computations.
