Statistical QoS-Aware Precoding Scheme for Downlink Multiuser MIMO Systems

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Abstract

1 In this paper, a downlink multi-user multiple-input multiple-output (MU-MIMO) system operating under statistical QoS constraints is investigated. Effective capacity, which is defined as the maximal constant arrival rate that can be supported by a given service process while satisfying the statistical queueing constraints, is adopted as the performance metric. Initially, perfect CSI is assumed at the base station (BS). An optimization problem is formulated to determine the optimal precoding matrix that maximizes the weighted sum effective capacity under total transmit power constraints at the BS. Then, an optimality condition that the optimal precoding matrix needs to satisfy is derived, which is proven to always have a feasible solution. Subsequently, fixed point iteration algorithms are designed to find a solution. Through extensive numerical results, the superiority of the proposed scheme is demonstrated under stringent delay constraints. Overall, this work provides an effective precoder design incorporating the statistical QoS constraints for the downlink MU-MIMO systems that outperforms existing strategies.

Original languageEnglish
Title of host publicationICC 2023 - IEEE International Conference on Communications
Subtitle of host publicationSustainable Communications for Renaissance
EditorsMichele Zorzi, Meixia Tao, Walid Saad
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6510-6515
Number of pages6
ISBN (Electronic)9781538674628
DOIs
StatePublished - 2023
Event2023 IEEE International Conference on Communications, ICC 2023 - Rome, Italy
Duration: 28 May 20231 Jun 2023

Publication series

NameIEEE International Conference on Communications
Volume2023-May
ISSN (Print)1550-3607

Conference

Conference2023 IEEE International Conference on Communications, ICC 2023
Country/TerritoryItaly
CityRome
Period28/05/231/06/23

Keywords

  • Effective capacity
  • multiantenna system
  • multiuser MIMO
  • precoding
  • statistical QoS constraints

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