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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In fifth generation (5G) new radio (NR), the demodulation reference signal(DMRS) is employed for channel estimation as part of coherent demodulation ofthe physical uplink shared channel. However, DMRS spoofing poses a seriousthreat to 5G NR since inaccurate channel estimation will severely degrade thedecoding performance. In this correspondence, we propose to exploit the spatialsparsity structure of the channel to detect the DMRS spoofing, which ismotivated by the fact that the spatial sparsity structure of the channel willbe significantly impacted if the DMRS spoofing happens. We first extract thespatial sparsity structure of the channel by solving a sparse feature retrievalproblem, then propose a sequential sparsity structure anomaly detection methodto detect DMRS spoofing. In simulation experiments, we exploit clustered delayline based channel model from 3GPP standards for verifications. Numericalresults show that our method outperforms both the subspace dimension based andenergy detector based methods.

Sequential Anomaly Detection Against Demodulation Reference Signal Spoofing in 5G NR