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 Plus annual

Presents the access of premium content as premium feature

Premium Content

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 annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The limited coexistence capabilities of current Internet of Things (IoT) wireless standards produce inefficient spectrum utilization and mutual performance impairment. The problem becomes critical in industrial IoT (IIoT) applications, which have stringent quality-of-service (QoS) requirements and very low error tolerance. The constant growth of wireless applications over unlicensed bands mandates then the adoption of dynamic spectrum-access techniques, which can significantly benefit from interference mapping over multiple dimensions of the radio space. In this article, we analyze the critical role of real-time interference detection and classification mechanisms that rely on only IIoT devices, without the added complexity of specialized hardware. The tradeoffs between classification performance and feasibility are analyzed in connection with the implementation on low-complexity IIoT devices. Moreover, we explain how to use such mechanisms for enabling IIoT networks to construct and maintain multidimensional interference maps at runtime in an autonomous fashion. Finally, we give an overview of the opportunities and challenges of using interference maps to enhance the performance of IIoT networks under interference.

Autonomous Interference Mapping for Industrial Internet of Things Networks Over Unlicensed Bands: Identifying Cross-Technology Interference