Online Downlink MIMO Wireless Network Virtualization in Fading Environments

Juncheng Wang, Min Dong, Ben Liang, Gary Boudreau

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

5 Citations (Scopus)


We consider downlink multiple-input multiple-output (MIMO) wireless network virtualization (WNV) in a fading environment, via a base station (BS) precoding design. The BS is owned by an infrastructure provider (InP) and is shared by several service providers (SPs) who are oblivious to each other. The SPs realize their virtual-cell transmissions via MIMO precoding provided by the InP. We aim to minimize the time-averaged expected deviation of the precoding provided by the InP from the SPs' virtualization demands, considering both long-term and short-term transmit power limits at the BS. We propose an online MIMO WNV algorithm to provide a precoding solution through Lyapunov optimization. Our online precoding solution only requires the current channel state information, and it has a semi-closed form with low computational complexity. We provide an upper bound on the performance of the proposed algorithm, showing that it can be arbitrarily close to the optimum over any given time horizon. Simulation results validate the performance of our proposed algorithm under typical urban micro-cell settings.
Original languageEnglish
Title of host publicationProceedings of 2019 IEEE Global Communications Conference (GLOBECOM)
Number of pages6
ISBN (Electronic)9781728109626
ISBN (Print)9781728109633
Publication statusPublished - Dec 2019
Event2019 IEEE Global Communications Conference, GLOBECOM 2019 - Waikoloa, United States
Duration: 9 Dec 201913 Dec 2019

Publication series

NameProceedings of IEEE Global Communications Conference (GLOBECOM)
ISSN (Print)1930-529X
ISSN (Electronic)2576-6813


Conference2019 IEEE Global Communications Conference, GLOBECOM 2019
Country/TerritoryUnited States
Internet address

User-Defined Keywords

  • MIMO
  • Wireless network virtualization
  • Precoding design
  • Lyapunov optimization
  • Long-term constraints


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