Analog Product Coding for Over-the-Air Aggregation Over Burst-Sparse Interference Multiple-Access Channels

Over-the-Air aggregation (OTA) is a promising technology for Internet-of-Things (IoT) applications, but it can be vulnerable to burst interference from co-channel non-cooperative IoT communications. In this paper, we propose a robust OTA framework for IoT-OTA applications that mitigates burst sparse interference using analog product code. We first propose a hierarchical likelihood model and a Markov-based hierarchical prior model to capture the structural properties in the received coded observations and the statistics of the burst-sparse interference, respectively. Then, we design a low-complexity Bayesian decoder using online turbo variational Bayesian inference technique, which ensures good performance without prior knowledge of the model parameters. In addition, we propose an optimization-based design for the analog product code encoding matrix that minimizes the end-to-end decoding mean squared error. Extensive simulations demonstrate the effectiveness of the proposed solution on interference mitigation, outperforming various state-of-the-art baseline schemes.