Switching-Based Selection Techniques for Tripolar Antennas in Multihop IoT Networks

Abstract

Adaptive multielement antennas can be leveraged to improve the reliability of wireless systems deployed in cluttered, depolarizing environments, such as those expected for Internet of Things (IoT) applications. While the performance improvement provided by such antennas has been well studied for individual links, multiple-hop networks have received little attention. In this work, we consider the problem of how devices in a multihop network should configure a three-element, tripolar antenna when deployed in a Rayleigh fading environment. We propose two switching-based antenna selection strategies: 1) Max-Sum and 2) Max–Min, each of which considers the channel conditions for communicating to nodes both higher and lower in the network hierarchy. We first derive the outage performance of the proposed schemes analytically and compare their performance with the well-known approaches of selection and switched diversity. Through simulations, which utilize empirical channel data from IoT devices equipped with a tripolar antenna, we show that the proposed Max-Sum and Max-Min schemes reduce antenna switching by over 80%, when compared to selection diversity. In addition, these two approaches lead to a median gain of 1.8 and 0.3 dB and a 1% diversity gain of 3.6 and 1.4 dB, respectively, relative to switched diversity.