Mike Koivisto

Papers

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About

Mike Koivisto is a researcher whose work sits at the intersection of wireless communications, positioning systems, and the Internet of Things (IoT), with a particular focus on industrial and high-frequency applications. His most influential contribution, "Benefits of Positioning-Aided Communication Technology in High-Frequency Industrial IoT" (2018, 48 citations), established a compelling vision for how location awareness can enhance dynamic radio connectivity for autonomous systems such as drones, factory robots, and connected vehicles — a paper that has become a touchstone in the field. Building on this foundation, Koivisto has advanced sophisticated algorithmic frameworks for positioning, notably developing MU-PoSAC, an Extended Kalman Filter (EKF)-based approach that jointly addresses multi-user positioning, synchronization, and anchor calibration in millimeter-wave environments, contributing to broader situational awareness beyond simple localization. His work on 5G-enabled indoor positioning further demonstrates a commitment to real-world industrial relevance, particularly for aerial robotics requiring precise three-dimensional accuracy. With a body of work spanning foundational concepts to advanced Bayesian estimation techniques, Koivisto has meaningfully shaped how researchers and engineers think about integrating positioning intelligence into next-generation wireless systems.