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

Massive multiple-input multiple-output (MIMO) is a key technology for fifthgeneration (5G) communication system. MIMO symbol detection is one of the mostcomputationally intensive tasks for a massive MIMO baseband receiver. In thispaper, we analyze matrix decomposition algorithms for massive MIMO systems,which were traditionally used for small-scale MIMO detection due to theirnumerical stability and modular design. We present the computational complexityof linear detection mechanisms based on QR, Cholesky and LDL-decompositionalgorithms for different massive MIMO configurations. We compare them with thestate-of-art approximate inversion-based massive MIMO detection methods. Theresults provide important insights for system and very large-scale integration(VLSI) designers to select appropriate massive MIMO detection algorithmsaccording to their requirement.

Matrix Decomposition for Massive MIMO Detection