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Two-Layer Decoding in Cellular Massive MIMO Systems with Spatial Channel Correlation
Linköping Univ, Dept Elect Engn ISY, SE-58183 Linköping, Sweden..
Linköping Univ, Dept Elect Engn ISY, SE-58183 Linköping, Sweden..ORCID iD: 0000-0002-5954-434x
2019 (English)In: ICC 2019 - 2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), IEEE , 2019Conference paper, Published paper (Refereed)
Abstract [en]

This paper studies a two-layer decoding method that mitigates inter-cell interference in multi-cell Massive MIMO systems. In layer one, each base station (BS) estimates the channels to intra-cell users and uses the estimates for local decoding on each BS, followed by a second decoding layer where the BSs cooperate to mitigate inter-cell interference. An uplink achievable spectral efficiency (SE) expression is computed for arbitrary two-layer decoding schemes, while a closed-form expression is obtained for correlated Rayleigh fading channels, maximum-ratio combining (MRC), and large-scale fading decoding (LSFD) in the second layer. We formulate a non-convex sum SE maximization problem with both the data power and LSFD vectors as optimization variables and develop an algorithm based on the weighted MMSE (minimum mean square error) approach to obtain a stationary point with low computational complexity.

Place, publisher, year, edition, pages
IEEE , 2019.
Series
IEEE International Conference on Communications, ISSN 1550-3607
National Category
Signal Processing Telecommunications
Identifiers
URN: urn:nbn:se:kth:diva-296038ISI: 000492038802139OAI: oai:DiVA.org:kth-296038DiVA, id: diva2:1664545
Conference
IEEE International Conference on Communications (IEEE ICC), MAY 20-24, 2019, Shanghai, PEOPLES R CHINA
Note

Part of ISBN 978-1-5386-8088-9

QC 20220620

Available from: 2022-06-03 Created: 2022-06-03 Last updated: 2024-03-11Bibliographically approved

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Björnson, Emil

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Citation style
  • apa
  • ieee
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  • Other style
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Language
  • de-DE
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  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
  • html
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  • asciidoc
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