Impedance Variation Detection at MISO Receivers

TL;DR

This paper introduces a hypothesis testing approach using a generalized likelihood-ratio test to detect impedance changes at MISO receivers, improving detection accuracy and false alarm trade-offs.

Contribution

It formulates impedance variation detection as a hypothesis test and develops an efficient binary search algorithm for the GLRT, enhancing detection performance.

Findings

The GLRT detector outperforms a reference detector in simulations.

Transmit diversity improves detection accuracy in slow fading channels.

The proposed method offers a better detection and false alarm trade-off.

Abstract

Techniques have been proposed to estimate unknown antenna impedance due to time-varying near-field loading conditions at multiple-input single-output (MISO) receivers. However, it remains unclear when a change occurs and impedance estimation becomes necessary. In this letter, we address this problem by formulating it as a hypothesis test. Our contributions include deriving a generalized likelihood-ratio test (GLRT) detector to decide if the antenna impedance has changed over two groups of packets. This GLRT formulation leads to a novel optimization problem, but we propose a binary search based algorithm to solve it efficiently. Our derived GLRT detector enjoys a better detection and false alarm trade-off when compared with a well-known, reference detector in simulations. As one result, more transmit diversity significantly improves detection accuracy at a given false alarm rate, especially in slow fading channels.