A Stochastic Proximal WMMSE for Ergodic Sum Rate Maximization

Xiaotong Zhao, Xi Wang, Juncheng Wang, Qingjiang Shi*

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

Abstract

We consider ergodic weighted sum rate (WSR) maximization in a massive multi-user multiple-input multiple-output system. Existing solutions iteratively minimize the average WSR based on all the historical information, and use bisection search to satisfy the power constraint at each iteration, resulting in both high storage burden and high computational complexity. In contrast, we propose an efficient stochastic proximal weighted minimum mean-square error (SPWMMSE) algorithm, which updates the precoder only based on the current single channel realization, without checking the power constraint at each iteration. Furthermore, we propose a novel proximal term to incorporate all the previous channel and surrogate function information in precoder updates. Our analysis shows that SPWMMSE converges to the stationary point of the original ergodic WSR maximization problem almost surely. Simulation results demonstrate the effectiveness of SPWMMSE over the current best alternatives.
Original languageEnglish
Title of host publicationProceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2024
PublisherIEEE
Pages8906-8910
Number of pages5
ISBN (Electronic)9798350344851
ISBN (Print)9798350344868
DOIs
Publication statusPublished - 17 Apr 2024
Event2024 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024 - COEX, Seoul, Korea, Republic of
Duration: 14 Apr 202419 Apr 2024
https://2024.ieeeicassp.org/
https://2024.ieeeicassp.org/program-schedule/
https://ieeexplore.ieee.org/xpl/conhome/10445798/proceeding

Publication series

NameProceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
PublisherIEEE
ISSN (Print)1520-6149
ISSN (Electronic)2379-190X

Conference

Conference2024 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024
Country/TerritoryKorea, Republic of
CitySeoul
Period14/04/2419/04/24
Internet address

Scopus Subject Areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

User-Defined Keywords

  • Massive MU-MIMO
  • precoding
  • imperfect CSI
  • stochastic WMMSE
  • sum-rate maximization

Fingerprint

Dive into the research topics of 'A Stochastic Proximal WMMSE for Ergodic Sum Rate Maximization'. Together they form a unique fingerprint.

Cite this