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Joint Optimization of Switching Point and Power Control in Dynamic TDD Cell-Free Massive MIMO
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-3469-726X
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-8342-4567
Ericsson Res, S-58330 Linkoping, Sweden.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-7599-4367
2023 (English)In: FIFTY-SEVENTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, IEEECONF, IEEE , 2023, p. 988-992Conference paper, Published paper (Refereed)
Abstract [en]

We consider a cell-free massive multiple-input multiple-output (CFmMIMO) network operating in dynamic time division duplex (DTDD). The switching point between the uplink (UL) and downlink (DL) data transmission phases can be adapted dynamically to the instantaneous quality-of-service (QoS) requirements in order to improve energy efficiency (EE). To this end, we formulate a problem of optimizing the DTDD switching point jointly with the UL and DL power control coefficients, and the large-scale fading decoding (LSFD) weights for EE maximization. Then, we propose an iterative algorithm to solve the formulated challenging problem using successive convex approximation with an approximate stationary solution. Simulation results show that optimizing switching points remarkably improves EE compared with baseline schemes that adjust switching points heuristically.

Place, publisher, year, edition, pages
IEEE , 2023. p. 988-992
Series
Conference Record of the Asilomar Conference on Signals Systems and Computers, ISSN 1058-6393, E-ISSN 2576-2303
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:liu:diva-208694DOI: 10.1109/IEEECONF59524.2023.10476848ISI: 001207755100178ISBN: 9798350325744 (electronic)ISBN: 9798350325751 (print)OAI: oai:DiVA.org:liu-208694DiVA, id: diva2:1907439
Conference
57th Asilomar Conference on Signals, Systems and Computers, ELECTR NETWORK, oct 29-nov 01, 2023
Note

Funding Agencies|Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation; ELLIIT; European Union [101013425]; Swedish Research Council [2022-06725]

Available from: 2024-10-22 Created: 2024-10-22 Last updated: 2024-10-22

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Output format
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