A Comprehensive Review of Millimeter-Wave RFID: Retrodirective Topologies, Passive and Semi-Passive Energy Architectures, and the Integration of Advanced Communication Methods

Millimeter-wave Identification (mmID) is a key enabler for next-generation Internet of Things (IoT) applications. This paper provides a comprehensive review of recent advancements which have improved localization, sensing, and communication through increased read ranges and angular coverages, reduced power consumption, and improved localization accuracies. These advancements are achieved through innovative designs integrating retrodirective arrays, planar and three-dimensional lenses, energy-autonomous solutions, and machine learning techniques. Trade-offs between the different types of mmID tags are discussed and ways of mitigating these challenges are addressed. Additionally, the paper highlights key applications, including wireless sensing, motion tracking for VR/AR applications, structural health monitoring, and high-data-rate backscatter communication. Current limitations and future directions are discussed highlighting the role of machine learning, energy harvesting, and reconfigurable intelligent surfaces (RIS) in advancing next-generation mmID networks. By addressing these factors, this review provides insights into the continued development of mmID technology for widespread adoption in advanced IoT and wireless communication systems.