Matches in SemOpenAlex for { <https://semopenalex.org/work/W3192028045> ?p ?o ?g. }
- W3192028045 endingPage "13402" @default.
- W3192028045 startingPage "13398" @default.
- W3192028045 abstract "In a time-varying massive multiple-input multiple-output (MIMO) system, the acquisition of the downlink channel state information at the base station (BS) is a very challenging task due to the prohibitively high overheads associated with downlink training and uplink feedback. In this paper, we consider the hybrid precoding structure at BS and examine the antenna-time domain channel extrapolation. We design a latent ordinary differential equation (ODE)-based network under the variational auto-encoder (VAE) framework to learn the mapping function from the partial uplink channels to the full downlink ones at the BS side. Specifically, the gated recurrent unit is adopted for the encoder and the fully-connected neural network is used for the decoder. The end-to-end learning is utilized to optimize the network parameters. Simulation results show that the designed network can efficiently infer the full downlink channels from the partial uplink ones, which can significantly reduce the channel training overhead." @default.
- W3192028045 created "2021-08-16" @default.
- W3192028045 creator A5030054597 @default.
- W3192028045 creator A5060613485 @default.
- W3192028045 creator A5062714111 @default.
- W3192028045 creator A5077149719 @default.
- W3192028045 creator A5081898263 @default.
- W3192028045 date "2022-12-01" @default.
- W3192028045 modified "2023-09-27" @default.
- W3192028045 title "Deep Learning Based Antenna-Time Domain Channel Extrapolation for Hybrid Mmwave Massive MIMO" @default.
- W3192028045 cites W2141682101 @default.
- W3192028045 cites W2231026252 @default.
- W3192028045 cites W2740088812 @default.
- W3192028045 cites W2807609521 @default.
- W3192028045 cites W2886124254 @default.
- W3192028045 cites W2963532871 @default.
- W3192028045 cites W2968019094 @default.
- W3192028045 cites W2970840827 @default.
- W3192028045 cites W3002914655 @default.
- W3192028045 cites W3013594094 @default.
- W3192028045 cites W3019262619 @default.
- W3192028045 cites W3081455451 @default.
- W3192028045 cites W3163787681 @default.
- W3192028045 cites W3189202224 @default.
- W3192028045 cites W3200422671 @default.
- W3192028045 doi "https://doi.org/10.1109/tvt.2022.3197452" @default.
- W3192028045 hasPublicationYear "2022" @default.
- W3192028045 type Work @default.
- W3192028045 sameAs 3192028045 @default.
- W3192028045 citedByCount "2" @default.
- W3192028045 countsByYear W31920280452023 @default.
- W3192028045 crossrefType "journal-article" @default.
- W3192028045 hasAuthorship W3192028045A5030054597 @default.
- W3192028045 hasAuthorship W3192028045A5060613485 @default.
- W3192028045 hasAuthorship W3192028045A5062714111 @default.
- W3192028045 hasAuthorship W3192028045A5077149719 @default.
- W3192028045 hasAuthorship W3192028045A5081898263 @default.
- W3192028045 hasBestOaLocation W31920280452 @default.
- W3192028045 hasConcept C111919701 @default.
- W3192028045 hasConcept C118505674 @default.
- W3192028045 hasConcept C127162648 @default.
- W3192028045 hasConcept C127413603 @default.
- W3192028045 hasConcept C132459708 @default.
- W3192028045 hasConcept C134306372 @default.
- W3192028045 hasConcept C138660444 @default.
- W3192028045 hasConcept C148063708 @default.
- W3192028045 hasConcept C160562895 @default.
- W3192028045 hasConcept C207987634 @default.
- W3192028045 hasConcept C24326235 @default.
- W3192028045 hasConcept C2779960059 @default.
- W3192028045 hasConcept C31258907 @default.
- W3192028045 hasConcept C33923547 @default.
- W3192028045 hasConcept C41008148 @default.
- W3192028045 hasConcept C555944384 @default.
- W3192028045 hasConcept C68649174 @default.
- W3192028045 hasConcept C76155785 @default.
- W3192028045 hasConcept C79403827 @default.
- W3192028045 hasConceptScore W3192028045C111919701 @default.
- W3192028045 hasConceptScore W3192028045C118505674 @default.
- W3192028045 hasConceptScore W3192028045C127162648 @default.
- W3192028045 hasConceptScore W3192028045C127413603 @default.
- W3192028045 hasConceptScore W3192028045C132459708 @default.
- W3192028045 hasConceptScore W3192028045C134306372 @default.
- W3192028045 hasConceptScore W3192028045C138660444 @default.
- W3192028045 hasConceptScore W3192028045C148063708 @default.
- W3192028045 hasConceptScore W3192028045C160562895 @default.
- W3192028045 hasConceptScore W3192028045C207987634 @default.
- W3192028045 hasConceptScore W3192028045C24326235 @default.
- W3192028045 hasConceptScore W3192028045C2779960059 @default.
- W3192028045 hasConceptScore W3192028045C31258907 @default.
- W3192028045 hasConceptScore W3192028045C33923547 @default.
- W3192028045 hasConceptScore W3192028045C41008148 @default.
- W3192028045 hasConceptScore W3192028045C555944384 @default.
- W3192028045 hasConceptScore W3192028045C68649174 @default.
- W3192028045 hasConceptScore W3192028045C76155785 @default.
- W3192028045 hasConceptScore W3192028045C79403827 @default.
- W3192028045 hasFunder F4320321001 @default.
- W3192028045 hasFunder F4320334593 @default.
- W3192028045 hasFunder F4320335787 @default.
- W3192028045 hasIssue "12" @default.
- W3192028045 hasLocation W31920280451 @default.
- W3192028045 hasLocation W31920280452 @default.
- W3192028045 hasOpenAccess W3192028045 @default.
- W3192028045 hasPrimaryLocation W31920280451 @default.
- W3192028045 hasRelatedWork W2023409468 @default.
- W3192028045 hasRelatedWork W2042521024 @default.
- W3192028045 hasRelatedWork W2587236994 @default.
- W3192028045 hasRelatedWork W2903335080 @default.
- W3192028045 hasRelatedWork W3092731089 @default.
- W3192028045 hasRelatedWork W3190774574 @default.
- W3192028045 hasRelatedWork W3197035501 @default.
- W3192028045 hasRelatedWork W3201343766 @default.
- W3192028045 hasRelatedWork W4287642618 @default.
- W3192028045 hasRelatedWork W4291722335 @default.
- W3192028045 hasVolume "71" @default.
- W3192028045 isParatext "false" @default.
- W3192028045 isRetracted "false" @default.
- W3192028045 magId "3192028045" @default.