arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2401.02178eess.SP
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基于OFDM且具有重要性感知的数字语义通信

OFDM-Based Digital Semantic Communication with Importance Awareness

Chuanhong Liu, Caili Guo, Yang Yang, Wanli Ni, Tony Q. S. Quek

AI总结:

针对现有语义通信局限于模拟与简单信道的问题,提出基于OFDM的数字语义通信系统,通过语义重要性度量联合优化子载波与比特分配,显著提升了通信性能。

摘要:

语义通信因其能在保持任务性能的同时减少数据传输量而备受关注。然而,现有工作主要集中于采用简单信道模型的模拟语义通信,这可能限制其实际应用。为缩小这一差距,我们提出一种基于正交频分复用(OFDM)的语义通信系统,该系统与现有数字通信基础设施兼容。在所考虑的系统中,提取的语义由标量量化器量化,转换为OFDM信号,随后在频率选择性信道上传输。此外,我们提出一种语义重要性度量方法,以建立目标任务与语义特征之间的关系。基于语义重要性,我们构建子载波和比特分配问题以最大化通信性能。然而,由于基于神经网络的语义编解码器,优化目标函数无法用数学表达式准确刻画。鉴于该问题的复杂性,我们首先提出一种低复杂度子载波分配方法,将信道条件更好的子载波分配给更关键的语义。然后,我们提出一种基于深度强化学习的动态动作空间比特分配算法。仿真结果表明,与模拟语义通信和传统基于比特的通信系统相比,所提系统分别实现了9.7%和28.7%的性能提升。

英文摘要:

Semantic communication (SemCom) has received considerable attention for its ability to reduce data transmission size while maintaining task performance. However, existing works mainly focus on analog SemCom with simple channel models, which may limit its practical application. To reduce this gap, we propose an orthogonal frequency division multiplexing (OFDM)-based SemCom system that is compatible with existing digital communication infrastructures. In the considered system, the extracted semantics is quantized by scalar quantizers, transformed into OFDM signal, and then transmitted over the frequency-selective channel. Moreover, we propose a semantic importance measurement method to build the relationship between target task and semantic features. Based on semantic importance, we formulate a sub-carrier and bit allocation problem to maximize communication performance. However, the optimization objective function cannot be accurately characterized using a mathematical expression due to the neural network-based semantic codec. Given the complex nature of the problem, we first propose a low-complexity sub-carrier allocation method that assigns sub-carriers with better channel conditions to more critical semantics. Then, we propose a deep reinforcement learning-based bit allocation algorithm with dynamic action space. Simulation results demonstrate that the proposed system achieves 9.7% and 28.7% performance gains compared to analog SemCom and conventional bit-based communication systems, respectively.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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