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DNN assisted Sphere Decoder

  • Telecom Paris

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

19 Citations (Scopus)

Abstract

A modified sphere decoding (SD) scheme is proposed for multiple-input multiple-output (MIMO) communication systems in this paper. The contribution of the paper includes the introduction of a systematic approach to sphere radius design and control based on Deep Neural Networks (DNNs) as well as the complexity advantage yielded by the proposed scheme. The learning model is introduced to predict the number of lattice points inside the sphere with some radius. Since this number is cleverly learnt by a neural network (NNW), the SD updates the radius until expecting a small number of points and then starts the search hypersphere, which greatly reduces the computational complexity. We show through simulation that for high dimensional MIMO systems the number of lattice points highly reduces in the new SD algorithm, which leads to a complexity only 3 times of the MMSE decoder complexity.

Original languageEnglish
Title of host publication2019 IEEE International Symposium on Information Theory, ISIT 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1172-1176
Number of pages5
ISBN (Electronic)9781538692912
DOIs
Publication statusPublished - 1 Jul 2019
Event2019 IEEE International Symposium on Information Theory, ISIT 2019 - Paris, France
Duration: 7 Jul 201912 Jul 2019

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2019-July
ISSN (Electronic)2157-8117

Conference

Conference2019 IEEE International Symposium on Information Theory, ISIT 2019
Country/TerritoryFrance
CityParis
Period7/07/1912/07/19

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