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.

翻译：语义通信是实现低通信开销与增强用户体验的端到端通信的重要技术路线。将语义概念与无线通信相结合带来了全新挑战。本文提出一种灵活的仿真软件，可自动通过通信信道传输语义分割地图图像。信道模型采用二进制相移键控（BPSK）调制的加性高斯白噪声（AWGN）信道，并选用业界成熟的极化码作为信道编码方案。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。为评估所提软件，我们构建了四个小型数据集，每个包含一千张语义地图样本，并附带每张图像的完整信息（包括极化码参数、图像属性细节、误码率（BER）和误帧率（FER））。该软件能够利用期望的信道编码参数和信噪比生成任意数量的语义地图，同时支持灵活替换其他数据集，使其具备高度适应性与可迁移性，可广泛应用于多种场景。