English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

In recent years, there has been a growing interest in using networks ofUnmanned Aerial Vehicles (UAV) that collectively perform complex tasks fordiverse applications. An important challenge in realizing UAV networks is theneed for a communication platform that accommodates rapid network topologychanges. For instance, a timely prediction of network topology changes canreduce communication link loss rate by setting up links with prolongedconnectivity.  In this work, we develop an optimal tracking policy for each UAV to perceiveits surrounding network configuration in order to facilitate more efficientcommunication protocols. More specifically, we develop an algorithm based onparticle swarm optimization and Kalman filtering with intermittent observationsto find a set of optimal tracking policies for each UAV under time-varyingchannel qualities and constrained tracking resources such that the overallnetwork estimation error is minimized.

Optimal Measurement Policy for Predicting UAV Network Topology