Tracking Time-Varying Parameters in Massive MIMO IoT Networks: A Linear Coherent Decentralized Approach

This paper investigates the integration of Internet of Things (IoT) networks with modern massive multiple-input multiple-output (MIMO) wireless systems to enable various new use cases. Given the dynamic nature of parameters monitored by IoT nodes, efficient techniques for tracking these time-varying parameters are required. In a typical IoT networks, each IoT node linearly precodes its observations and transmits them over a coherent multiple access channel to a fusion center (FC). These IoT networks are power and bandwidth constrained in nature. Therefore, designing transmit precoders for the IoT nodes and a combiner for the FC is essential. This work proposes online linear receive combiner and transmit precoder designs that minimize the mean square error (MSE) under transmit power constraints. Using an alternating optimization technique, we derive closed-form solutions for the combiners and transmit precoders. Our numerical results validate the effectiveness of the proposed algorithms.