Channel-Adaptive Wireless Image Transmission With OFDM

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 dual-attention mechanism employing orthogonal frequency division multiplexing (OFDM) transmission. Unlike the previous works, our approach adaptive to channel-gain noise-power variations by exploiting estimated state information (CSI). Specifically, mechanism, model can learn map features allocate transmission-power resources judiciously based on CSI. Extensive numerical experiments verify that CA-JSCC achieves state-of-the-art performance among existing JSCC schemes. In addition, robust varying conditions better exploit limited transmitting critical subchannels.