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

We derive novel bounds for the performance of algorithms that estimate thedownlink covariance matrix from the uplink covariance matrix in frequencydivision duplex (FDD) massive multiple-input multiple-output (MIMO) systems.The focus is on algorithms that use estimates of the angular power spectrum asan intermediate step. Unlike previous results, the proposed bounds follow fromsimple arguments in possibly infinite dimensional Hilbert spaces, and they donot require strong assumptions on the array geometry or on the propagationmodel. Furthermore, they are suitable for the analysis of set-theoretic methodsthat can efficiently incorporate side information about the angular powerspectrum. This last feature enables us to derive simple techniques to enhanceset-theoretic methods without any heuristic arguments. In particular, we showthat the performance of a simple algorithm that requires only a simplematrix-vector multiplication cannot be improved significantly in some practicalscenarios, especially if coarse information about the support of the angularpower spectrum is available.

Error Bounds for FDD Massive MIMO Channel Covariance Conversion with Set-Theoretic Methods