Cross-technology communication (CTC) is a promising technique that enables
direct communications among incompatible wireless technologies without needing
hardware modification. However, it has not been widely adopted in real-world
applications due to its inefficiency and unreliability. To address this issue,
this paper proposes a deep joint source-channel coding (DJSCC) scheme to enable
efficient and reliable CTC. The proposed scheme builds a neural-network-based
encoder and decoder at the sender side and the receiver side, respectively, to
achieve two critical tasks simultaneously: 1) compressing the messages to the
point where only their essential semantic meanings are preserved; 2) ensuring
the robustness of the semantic meanings when they are transmitted across
incompatible technologies. The scheme incorporates existing CTC coding
algorithms as domain knowledge to guide the encoder-decoder pair to learn the
characteristics of CTC links better. Moreover, the scheme constructs shared
semantic knowledge for the encoder and decoder, allowing semantic meanings to
be converted into very few bits for cross-technology transmissions, thus
further improving the efficiency of CTC. Extensive simulations verify that the
proposed scheme can reduce the transmission overhead by up to 97.63\% and
increase the structural similarity index measure by up to 734.78%, compared
with the state-of-the-art CTC scheme.

本论文提出了一种深度联合源 - 信道编码方案，以实现高效可靠的跨技术通信，通过利用现有的 CTC 编码算法作为领域知识来指导编码解码器对 CTC 链路特性进行更好的学习，进一步提高了 CTC 的效率，通过广泛的仿真验证，本方案与现有的 CTC 方案相比，可以将传输开销减少高达 97.63％，结构相似性指数提高了 734.78％。

深度联合源通道编码用于高效可靠的跨技术通信

Deep Joint Source-Channel Coding for Efficient and Reliable  Cross-Technology Communication

We consider distributed image transmission over a noisy multiple access
channel (MAC) using deep joint source-channel coding (DeepJSCC). It is known
that Shannon's separation theorem holds when transmitting independent sources
over a MAC in the asymptotic infinite block length regime. However, we are
interested in the practical finite block length regime, in which case separate
source and channel coding is known to be suboptimal. We introduce a novel joint
image compression and transmission scheme, where the devices send their
compressed image representations in a non-orthogonal manner. While
non-orthogonal multiple access (NOMA) is known to achieve the capacity region,
to the best of our knowledge, non-orthogonal joint source channel coding (JSCC)
scheme for practical systems has not been studied before. Through extensive
experiments, we show significant improvements in terms of the quality of the
reconstructed images compared to orthogonal transmission employing current
DeepJSCC approaches particularly for low bandwidth ratios. We publicly share
source code to facilitate further research and reproducibility.

本研究研究了在噪声的多信道上使用深度联合源频道编码进行分布式图像传输。研究表明，在有限块长度制度下，我们引入了一种新型的联合图像压缩和传输方案，其中设备以非正交方式发送其压缩图像表示。在实验中，相比于使用现有深度联合源频道编码方法的正交传输，特别是在低带宽比下，我们展示了重构图像质量方面的显著改进。