Leveraging the Near-Far Effect for Improved Spatial-Reuse Scheduling in Underwater Acoustic Networks

Roee Diamant, Paolo Casari, Filippo Campagnaro, Michele Zorzi

Research output: Contribution to journalArticlepeer-review


We present a spatial reuse resource allocation scheme for underwater acoustic networks that organizes communications so as to avoid destructive collisions. One prime source of collisions in underwater acoustic networks is the so called near-far effect, where a node located farther from the receiver is jammed by a closer node. While common practice considers such a situation a challenge, in this paper we consider it a resource, and use it to increase the network throughput of spatial-reuse time-division multiple access. Our algorithm serves two types of communications: 1) contention-free and 2) opportunistic. Our objective is to maximize the time slot allocation, while guaranteeing a minimum per-node packet transmission rate. The result is an increase in the number of contention-free packets received, and a decrease in the scheduling delay of opportunistic packets. Numerical results show that, at a slight cost in terms of fairness, our scheduling solutions achieve higher throughput and lower transmission delay than benchmark spatial-reuse scheduling protocols. These results are verified in a field experiment conducted in the Garda Lake, Italy, where we demonstrated our solution using off-the-shelf acoustic modems. To allow the reproducibility of our results, we publish the implementation of our proposed algorithm.

Original languageEnglish
Article number7802543
Pages (from-to)1480-1493
Number of pages14
JournalIEEE Transactions on Wireless Communications
Issue number3
StatePublished - Mar 2017

Bibliographical note

Publisher Copyright:
© 2016 IEEE.


  • Underwater acoustic networks
  • desert underwater
  • long propagation delay
  • near-far effect
  • optimization
  • sea trial
  • simulation
  • spatial-reuse scheduling
  • time-division-multiple-access (TDMA)

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics


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