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

This paper presents a new approach for automatic detection of low coverage and high interference scenarios (overshooting and pilot pollution) in Universal Mobile Telecommunications System (UMTS) /Long Term Evolution (LTE) networks. These algorithms, based on periodically extracted Drive Test (DT) measurements (or network trace information), identify the problematic cluster locations and compute harshness metrics, at cluster and cell level, quantifying the extent of the problem. Future work is in motion by adding self-optimization capabilities to the algorithms, which will automatically suggest physical and parameter optimization actions, based on the already developed harshness metrics. The proposed algorithms were validated for a live network urban scenario. 830 3rd Generation (3G) cells were self-diagnosed and performance metrics were computed. The most negative detected behaviors regards high interference control and not coverage verification.

Self-Diagnosing Low Coverage and High Interference in 3G/4G Radio Access Networks based on Automatic RF Measurement Extraction