Linear MIMO Precoders With Finite Alphabet Inputs via Stochastic Optimization and Deep Neural Networks (DNNs)

In this paper, we investigate designs of linear precoders for vector Gaussian channels via stochastic optimizations and deep neural networks (DNNs). We assume that the channel inputs are drawn from practical finite alphabets, and we search for precoders maximizing the mutual information between chan...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE transactions on signal processing Ročník 69; s. 4269 - 4281
Hlavní autoři:	Jing, Shusen, Xiao, Chengshan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Alphabets Artificial neural networks autoencoders Bit error rate Codes deep neural networks Entropy (Information theory) finite alphabet High speed rail linear precoders Lower bounds Mathematical analysis Maximization MIMO MIMO communication Mutual information Neural networks Optimization Precoding Signal processing algorithms Task analysis Training
ISSN:	1053-587X, 1941-0476
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!