Zobrazit v EDS

Lower Energy Consumption in Multi-CPU Cell-Free Massive MIMO Systems.

Uloženo v:
Podrobná bibliografie
Název: Lower Energy Consumption in Multi-CPU Cell-Free Massive MIMO Systems.
Autoři: Zhang, Heng, Li, Hui, Wang, Xin
Zdroj: Electronics (2079-9292); Nov2024, Vol. 13 Issue 22, p4392, 21p
Témata: CHANNEL estimation, MIMO systems, ENERGY consumption, SCALABILITY, ALGORITHMS
Abstrakt: Under the ideal assumption of deploying only one central processing unit (CPU) in the entire system, cell-free (CF) systems can achieve significant macro-diversity gain, thereby providing uniformly reliable service to each user equipment (UE). However, due to limitations in system scalability and the feasibility of strict phase synchronization, CF systems require a multi-CPU setup and perform coherent transmission at a smaller scale. Moreover, conventional CF systems typically operate in time-division duplex (TDD) mode and utilize statistical channel state information (CSI) for downlink (DL) decoding, but the channel hardening effect is not significant. These factors reduce downlink spectral efficiency (SE) and increase DL transmission time, leading to higher energy consumption in CF systems. To address these issues, we introduce downlink channel estimation (DLCE) in multi-CPU CF systems and derive the approximate achievable DL SE. To reduce DL pilot overhead, we propose an uplink–pilot-reuse-constrained DL pilot allocation principle. Based on this principle, we develop a farthest distance pilot allocation (FDPA) algorithm to mitigate pilot contamination. In addition, leveraging the characteristics of the heuristic distributed power allocation algorithm, we propose two access point (AP) clustering algorithms: one based on CSI (BCSI) and the other based on coherent group size (BCGS). Simulation results indicate that the introduction of DLCE significantly improves DL SE in multi-CPU CF massive MIMO systems, while the proposed FDPA algorithm further enhances DL SE. The BCSI and BCGS algorithms also effectively improve DL SE and help reduce energy consumption. By combining DLCE, the FDPA algorithm, and the proposed AP clustering algorithms, the energy consumption of multi-CPU CF systems can be significantly reduced. [ABSTRACT FROM AUTHOR]
Copyright of Electronics (2079-9292) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Databáze: Complementary Index
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://resolver.ebscohost.com/openurl?sid=EBSCO:edb&genre=article&issn=20799292&ISBN=&volume=13&issue=22&date=20241115&spage=4392&pages=4392-4412&title=Electronics (2079-9292)&atitle=Lower%20Energy%20Consumption%20in%20Multi-CPU%20Cell-Free%20Massive%20MIMO%20Systems.&aulast=Zhang%2C%20Heng&id=DOI:10.3390/electronics13224392
    Name: Full Text Finder
    Category: fullText
    Text: Full Text Finder
    Icon: https://imageserver.ebscohost.com/branding/images/FTF.gif
    MouseOverText: Full Text Finder
  – Url: https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=EBSCO&SrcAuth=EBSCO&DestApp=WOS&ServiceName=TransferToWoS&DestLinkType=GeneralSearchSummary&Func=Links&author=Zhang%20H
    Name: ISI
    Category: fullText
    Text: Nájsť tento článok vo Web of Science
    Icon: https://imagesrvr.epnet.com/ls/20docs.gif
    MouseOverText: Nájsť tento článok vo Web of Science
Header DbId: edb
DbLabel: Complementary Index
An: 181168213
RelevancyScore: 1007
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 1007.06079101563
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Lower Energy Consumption in Multi-CPU Cell-Free Massive MIMO Systems.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Zhang%2C+Heng%22">Zhang, Heng</searchLink><br /><searchLink fieldCode="AR" term="%22Li%2C+Hui%22">Li, Hui</searchLink><br /><searchLink fieldCode="AR" term="%22Wang%2C+Xin%22">Wang, Xin</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: Electronics (2079-9292); Nov2024, Vol. 13 Issue 22, p4392, 21p
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22CHANNEL+estimation%22">CHANNEL estimation</searchLink><br /><searchLink fieldCode="DE" term="%22MIMO+systems%22">MIMO systems</searchLink><br /><searchLink fieldCode="DE" term="%22ENERGY+consumption%22">ENERGY consumption</searchLink><br /><searchLink fieldCode="DE" term="%22SCALABILITY%22">SCALABILITY</searchLink><br /><searchLink fieldCode="DE" term="%22ALGORITHMS%22">ALGORITHMS</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Under the ideal assumption of deploying only one central processing unit (CPU) in the entire system, cell-free (CF) systems can achieve significant macro-diversity gain, thereby providing uniformly reliable service to each user equipment (UE). However, due to limitations in system scalability and the feasibility of strict phase synchronization, CF systems require a multi-CPU setup and perform coherent transmission at a smaller scale. Moreover, conventional CF systems typically operate in time-division duplex (TDD) mode and utilize statistical channel state information (CSI) for downlink (DL) decoding, but the channel hardening effect is not significant. These factors reduce downlink spectral efficiency (SE) and increase DL transmission time, leading to higher energy consumption in CF systems. To address these issues, we introduce downlink channel estimation (DLCE) in multi-CPU CF systems and derive the approximate achievable DL SE. To reduce DL pilot overhead, we propose an uplink–pilot-reuse-constrained DL pilot allocation principle. Based on this principle, we develop a farthest distance pilot allocation (FDPA) algorithm to mitigate pilot contamination. In addition, leveraging the characteristics of the heuristic distributed power allocation algorithm, we propose two access point (AP) clustering algorithms: one based on CSI (BCSI) and the other based on coherent group size (BCGS). Simulation results indicate that the introduction of DLCE significantly improves DL SE in multi-CPU CF massive MIMO systems, while the proposed FDPA algorithm further enhances DL SE. The BCSI and BCGS algorithms also effectively improve DL SE and help reduce energy consumption. By combining DLCE, the FDPA algorithm, and the proposed AP clustering algorithms, the energy consumption of multi-CPU CF systems can be significantly reduced. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Electronics (2079-9292) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://erproxy.cvtisr.sk/sfx/access?url=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edb&AN=181168213
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3390/electronics13224392
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 21
        StartPage: 4392
    Subjects:
      – SubjectFull: CHANNEL estimation
        Type: general
      – SubjectFull: MIMO systems
        Type: general
      – SubjectFull: ENERGY consumption
        Type: general
      – SubjectFull: SCALABILITY
        Type: general
      – SubjectFull: ALGORITHMS
        Type: general
    Titles:
      – TitleFull: Lower Energy Consumption in Multi-CPU Cell-Free Massive MIMO Systems.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Zhang, Heng
      – PersonEntity:
          Name:
            NameFull: Li, Hui
      – PersonEntity:
          Name:
            NameFull: Wang, Xin
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 11
              Text: Nov2024
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-print
              Value: 20799292
          Numbering:
            – Type: volume
              Value: 13
            – Type: issue
              Value: 22
          Titles:
            – TitleFull: Electronics (2079-9292)
              Type: main
ResultId 1