Hierarchical-block conditioning approximations for high-dimensional multivariate normal probabilities
Sign Up to like & getrecommendations! Published in 2019 at "Statistics and Computing"
DOI: 10.1007/s11222-018-9825-3
Abstract: This paper presents a new method to estimate large-scale multivariate normal probabilities. The approach combines a hierarchical representation with processing of the covariance matrix that decomposes the n-dimensional problem into a sequence of smaller m-dimensional… read more here.
Keywords: conditioning; multivariate normal; normal probabilities; method ... See more keywords
Hierarchical-Block Sparse Bayesian Learning for Spatial Non-Stationary Massive MIMO Channel Estimation
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DOI: 10.1109/lwc.2022.3146026
Abstract: This letter provides a novel hierarchical-block channel estimation scheme for massive multiple-input multiple-output (MIMO) systems based on Bayesian learning frameworks. Specifically, considering the spatial non-stationarity of massive MIMO channels introduced by a large-scale antenna array,… read more here.
Keywords: hierarchical block; spatial non; mimo; block ... See more keywords