We propose the use of adversarial wireless jamming to regularise the latent space of an autoencoder to match a diagonal Gaussian distribution. We consider the minimisation of a mean squared error distortion, where a jammer attempts to disrupt the recovery of a Gaussian source encoded and transmitted over the adversarial channel. A straightforward consequence of existing theoretical results is the fact that the saddle point of a minimax game - involving such an encoder, its corresponding decoder, and an adversarial jammer - consists of diagonal Gaussian noise output by the jammer. We use this result as inspiration for a novel approach to distribution matching in the latent space, utilising jamming as an auxiliary objective to encourage the aggregated latent posterior to match a diagonal Gaussian distribution. Using this new technique, we achieve distribution matching comparable to standard variational autoencoders and to Wasserstein autoencoders. This approach can also be generalised to other latent distributions.

翻译：我们提出利用对抗性无线干扰来正则化自编码器的潜在空间，以匹配对角高斯分布。我们考虑最小化均方误差失真，其中干扰器试图破坏在对抗性信道中编码和传输的高斯源信号的恢复。现有理论结果的一个直接推论是：涉及此类编码器、其对应解码器以及对抗性干扰器的极小极大博弈的鞍点，由干扰器输出的对角高斯噪声构成。我们利用这一结果作为灵感，提出了一种在潜在空间中进行分布匹配的新方法，通过将干扰作为辅助目标，促使聚合的潜在后验匹配对角高斯分布。采用这一新技术，我们实现了与标准变分自编码器及Wasserstein自编码器相当的分布匹配效果。该方法还可推广至其他潜在分布。