Optimal Transmission Scheduling in Small Multimodal Underwater Networks

Filippo Campagnaro, Paolo Casari, Michele Zorzi, Roee Diamant

Research output: Contribution to journalArticlepeer-review


We describe a scheduling protocol for multimodal networks of relatively limited size, whose nodes encompass various underwater communication technologies. For such a case, we show that significant improvement in the network operations is possible when the transmission schedule is set to jointly utilize all communication technologies. Our solution is based on per-technology time-division multiple access frames, whose time slots are determined optimally to maximize the overall channel utilization while preserving flow limitations and maintaining fairness in resource allocation. Our numerical simulations and experimental results for multimodal networks with several acoustic technologies show that, while maintaining a fair resource allocation, our scheduling solution provides both high throughput and low packet delivery delay.

Original languageEnglish
Article number8478330
Pages (from-to)368-371
Number of pages4
JournalIEEE Wireless Communications Letters
Issue number2
StatePublished - Apr 2019

Bibliographical note

Funding Information:
Manuscript received July 25, 2018; revised September 10, 2018; accepted September 17, 2018. Date of publication October 1, 2018; date of current version April 9, 2019. This work was supported by the NATO Science for Peace and Security Programme under Grant G5293. The associate editor coordinating the review of this paper and approving it for publication was S. De. (Corresponding author: Filippo Campagnaro.) F. Campagnaro and M. Zorzi are with the Department of Information Engineering, University of Padova, 35131 Padua, Italy (e-mail: campagn1 @dei.unipd.it; zorzi@dei.unipd.it).

Publisher Copyright:
© 2012 IEEE.


  • Underwater communication networks
  • multi-modal systems
  • transmission scheduling
  • underwater acoustic communications

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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