使用 Polar Codes 实现端到端基于语义的通信系统中语义地图图像的自动与灵活传输
Automatic and Flexible Transmission of Semantic Map Images using Polar Codes for End-to-End Semantic-based Communication Systems
AI总结：
本文提出一种灵活的仿真软件，利用 polar codes 在 AWGN 信道下自动传输基于 COCO-Stuff 数据集的语义地图图像，并生成含 BER 和 FER 等综合信息的评估数据集，具有高度适应性和可迁移性。
摘要：
语义通信代表了一条实现端到端通信的有前景路线，能降低通信开销并提升用户体验。将语义概念与无线通信结合带来了新挑战。本文提出一种灵活的仿真软件，可在通信信道上自动传输语义分割地图图像。信道设置采用加性高斯白噪声（AWGN）信道及二进制相移键控（BPSK）调制。选用著名的 polar codes 作为信道编码方案。以流行的 COCO-Stuff 数据集为例，生成对应不同信噪比（SNR）的语义地图图像。为评估该软件，我们生成了四个小型数据集，每个包含一千个语义地图样本，并附带每张图像的综合信息，包括 polar codes 规格、详细图像属性、误码率（BER）和帧错误率（FER）。利用所需信道编码参数和首选 SNR 生成无限数量语义地图的能力，结合使用替代数据集的灵活性，使我们的仿真软件具有高度适应性，可广泛迁移至多种用例。
英文摘要：
Semantic communication represents a promising roadmap toward achieving end-to-end communication with reduced communication overhead and an enhanced user experience. The integration of semantic concepts with wireless communications presents novel challenges. This paper proposes a flexible simulation software that automatically transmits semantic segmentation map images over a communication channel. An additive white Gaussian noise (AWGN) channel using binary phase-shift keying (BPSK) modulation is considered as the channel setup. The well-known polar codes are chosen as the channel coding scheme. The popular COCO-Stuff dataset is used as an example to generate semantic map images corresponding to different signal-to-noise ratios (SNRs). To evaluate the proposed software, we have generated four small datasets, each containing a thousand semantic map samples, accompanied by comprehensive information corresponding to each image, including the polar code specifications, detailed image attributes, bit error rate (BER), and frame error rate (FER). The capacity to generate an unlimited number of semantic maps utilizing desired channel coding parameters and preferred SNR, in conjunction with the flexibility of using alternative datasets, renders our simulation software highly adaptable and transferable to a broad range of use cases.
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。
