Resolution Limits of Non-Adaptive 20 Questions Estimation for Tracking Multiple Moving Targets
Chunsong Sun, Lin Zhou, Jingjing Wang, Weijie Yuan, Chunxiao Jiang, Alfred Hero

TL;DR
This paper investigates the fundamental limits of non-adaptive 20 questions estimation for tracking multiple moving targets, providing bounds, algorithms, and applications in wireless beam tracking.
Contribution
It derives non-asymptotic and asymptotic bounds for resolution, introduces a computationally efficient thresholding estimator, and extends results to dynamic target models and practical 5G applications.
Findings
Bounds on resolution are achieved by a threshold-based estimator.
The proposed method reduces computational complexity compared to previous schemes.
Results are applicable to practical beam tracking in 5G wireless networks.
Abstract
Motivated by the practical application of beam tracking of multiple devices in Multiple Input Multiple Output (MIMO) communication, we study the problem of non-adaptive twenty questions estimation for locating and tracking multiple moving targets under a query-dependent noisy channel. Specifically, we derive a non-asymptotic bound and a second-order asymptotic bound on resolution for optimal query procedures and provide numerical examples to illustrate our results. In particular, we demonstrate that the bound is achieved by a state estimator that thresholds the mutual information density over possible target locations. This single threshold decoding rule has reduced the computational complexity compared to the multiple threshold scheme proposed for locating multiple stationary targets (Zhou, Bai and Hero, TIT 2022). We discuss two special cases of our setting: the case with unknown…
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