Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Ranasinghe, Vismika"'
Wireless networks are inherently graph-structured, which can be utilized in graph representation learning to solve complex wireless network optimization problems. In graph representation learning, feature vectors for each entity in the network are ca
Externí odkaz:
http://arxiv.org/abs/2212.01904
A graph neural network (GNN) based access point (AP) selection algorithm for cell-free massive multiple-input multiple-output (MIMO) systems is proposed. Two graphs, a homogeneous graph which includes only AP nodes representing the structure of the A
Externí odkaz:
http://arxiv.org/abs/2107.02884
Belief propagation (BP) is an iterative decoding algorithm for polar codes which can be parallelized effectively to achieve higher throughput. However, because of the presence of error floor due to cycles and stopping sets in the factor graph, the pe
Externí odkaz:
http://arxiv.org/abs/1911.08868
Polar codes have been gaining a lot of interest due to it being the first coding scheme to provably achieve the symmetric capacity of a binary memoryless channel with an explicit construction. However, the main drawback of polar codes is the low thro
Externí odkaz:
http://arxiv.org/abs/1911.03201
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
IEEE Communications Magazine. :1-8
Wireless networks are inherently graph-structured, which can be utilized in graph representation learning to solve complex wireless network optimization problems. In graph representation learning, feature vectors for each entity in the network are ca
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3569bd6a0d3179594e6bc7582b283645
https://doi.org/10.1109/mcom.001.2200810
https://doi.org/10.1109/mcom.001.2200810
