Channel-Adaptive Wireless Image Transmission With OFDM
Channel-Adaptive Wireless Image Transmission With OFDM
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DOI：
10.1109/lwc.2022.3204837
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发表时间：
2022-05
影响因子：
6.3
通讯作者：
Haotian Wu;Yulin Shao;K. Mikolajczyk;Deniz Gündüz
中科院分区：
文献类型：
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作者：
Haotian Wu;Yulin Shao;K. Mikolajczyk;Deniz Gündüz
针对多径衰落信道下的无线图像传输，提出了一种基于学习的信道自适应联合信源信道编码(CA-JSCC)方案。提出的方法是一种端到端的自动编码器结构，具有双注意机制，使用正交频分多路复用(OFDM)传输。与以前的工作不同，我们的方法通过利用估计的信道状态信息(CSI)来适应信道增益和噪声功率的变化。具体地说，通过提出的双注意机制，我们的模型可以学习映射特征，并基于估计的CSI将发射功率资源明智地分配到可用子信道。大量的数值实验验证了CA-JSCC在现有的JSCC方案中达到了最好的性能。此外，CA-JSCC对变化的信道条件具有较强的鲁棒性，可以通过在更好的子信道上传输关键特征来更好地利用有限的信道资源。
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 to the available subchannels 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.