A Stacked Autoencoder-based Decode-and-Forward Relay Networks with I/Q Imbalance

We propose a stacked autoencoder (AE) that stacks a novel bit-wise denoising AE and a bit-wise AE for decode and forward (DF) relay network impacted by the I/Q imbalance (IQI) at all the nodes. Within the stacked AE framework, we propose block-coded modulation (BCM) and differential-BCM (d-BCM) designs depending on the availability of the channel state information (CSI) knowledge. Moreover, IQI estimation increases feedback overhead, thus, we design the stacked AE without utilizing the IQI parameters information that can generalize well on varying levels of IQI and signal-to-noise ratio, completely removing the IQI estimation overhead. By extensive evaluation, we show that the proposed stacked AE framework can remove the deteriorating impact of IQI performing similar to ideal relay networks without IQI.