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 Tools annual

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 monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

In soft decoding of data bits, the log-likelihood ratios are evaluated fromthe estimated data symbols. For proper constellation diagrams such as QPSK or16-QAM, these data symbols are often estimated using the linear minimum meansquare error (LMMSE) estimator. The LMMSE estimator only fulfills the weakBayesian unbiasedness constraint. Recently, estimators fulfilling the morestringent component-wise conditionally unbiased (CWCU) constraints have beeninvestigated, such as the CWCU LMMSE estimator. In this paper, we prove thatthe CWCU LMMSE estimates result in the very same log-likelihood ratios as theLMMSE estimates. For improper constellation diagrams such as 8-QAM, widelylinear estimators are used. For this case, we show that the widely linearversions of the LMMSE estimator and the CWCU LMMSE estimator also yieldidentical log-likelihood ratios. Finally, we give a simulation example whichillustrates a number of interesting properties of the discussed widely linearestimators.

On the Log-Likelihood Ratio Evaluation of CWCU Linear and Widely Linear MMSE Data Estimators