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

As a key enabler for massive machine-type communications (mMTC), spatialmultiplexing relies on massive multiple-input multiple-output (mMIMO)technology to serve the massive number of user equipments (UEs). To exploitspatial multiplexing, accurate channel estimation through pilot signals isneeded. In mMTC systems, it is impractical to allocate a unique orthogonalpilot sequence to each UE as it would require too long pilot sequences,degrading the spectral efficiency. This work addresses the design of channelfeatures from correlated fading channels to assist the pilot assignment inmulti-sector mMTC systems under pilot reuse of orthogonal sequences. In orderto reduce pilot collisions and to enable pilot reuse, we propose to extractfeatures from the channel covariance matrices that reflect the level oforthogonality between the UEs channels. Two features are investigated:covariance matrix distance (CMD) feature and CMD-aided channel charting (CC)feature. In terms of symbol error rate and achievable rate, the CC-basedfeature shows superior performance than the CMD-based feature and baselinepilot assignment algorithms.

Exploiting Spatial Correlation for Pilot Reuse in Single-Cell mMTC