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 this paper, we consider the interference rejection combining (IRC)receiver, which improves the cell-edge user throughput via suppressinginter-cell interference and requires estimating the covariance matrix includingthe inter-cell interference with high accuracy. In order to solve the problemof sample covariance matrix estimation with limited samples, a regularizationparameter optimization based on the minimum eigenvalue criterion is developed.It is different from traditional methods that aim at minimizing the meansquared error, but goes straight at the objective of optimizing the finalperformance of the IRC receiver. A lower bound of the minimum eigenvalue thatis easier to calculate is also derived. Simulation results demonstrate that theproposed approach is effective and can approach the performance of the oracleestimator in terms of the mutual information metric.

Minimum Eigenvalue Based Covariance Matrix Estimation with Limited Samples