论文标题
使用OFDM的通道自适应无线图像传输
Channel-Adaptive Wireless Image Transmission with OFDM
论文作者
论文摘要
我们提出了一种基于学习的通道自适应关节源和通道编码（CA-JSCC）方案，用于在多路径褪色通道上进行无线图像传输。所提出的方法是一种端到端自动编码器体系结构，其双重意见机制采用正交频施加多路复用（OFDM）传输。与以前的作品不同，我们的方法通过利用估计的通道状态信息（CSI）来适应通道增益和噪声功率变化。具体而言，借助提出的双重注意机制，我们的模型可以学会根据估计的CSI明智地分配传输功率资源来绘制特征。广泛的数值实验验证了CA-JSCC是否在现有的JSCC方案中实现最先进的性能。此外，CA-JSCC对变化的通道条件具有鲁棒性，可以通过将关键功能传输到更好的亚渠道上来更好地利用有限的通道资源。
We present a learning-based channel-adaptive joint source and channel coding (CA-JSCC) scheme for wireless image transmission over multipath fading channels. The proposed method is an end-to-end autoencoder architecture with a dual-attention mechanism employing orthogonal frequency division multiplexing (OFDM) transmission. Unlike the previous works, our approach is adaptive to channel-gain and noise-power variations by exploiting the estimated channel state information (CSI). Specifically, with the proposed dual-attention mechanism, our model can learn to map the features and allocate transmission-power resources judiciously based on the estimated CSI. Extensive numerical experiments verify that CA-JSCC achieves state-of-the-art performance among existing JSCC schemes. In addition, CA-JSCC is robust to varying channel conditions and can better exploit the limited channel resources by transmitting critical features over better subchannels.
