Robust suboptimal decision fusion in wireless sensor networks

Ruixiang Jiang, Saswat Misra, Biao Chen, Ananthram Swami

Research output: Chapter in Book/Entry/PoemConference contribution

11 Scopus citations


We study decision fusion for decentralized detection in a wireless sensor network. Motivated by the sub-optimality of previously proposed fusion rules, we investigate a new set of rules, termed 'generalized nonlinearities'. Our approach seeks to preserve the optimality of the likelihood ratio (LR) test, without requiring a priori information about the channel statistics or the local sensor performance indices. We derive such rules for coherent and noncoherent detection. Performance evaluation reveals notable advantages of the proposed rules relative to existing ones. Under coherent detection, it is shown that the proposed technique outperforms the LR rule under channel mismatch (an indication of its robustness). For noncoherent detection, we apply the Central Limit Theorem in conjunction with generalized nonlinearities technique to provide insights not readily available under the LR rule.

Original languageEnglish (US)
Title of host publicationMILCOM 2005
Subtitle of host publicationMilitary Communications Conference 2005
StatePublished - 2005
EventMILCOM 2005: Military Communications Conference 2005 - Atlatnic City, NJ, United States
Duration: Oct 17 2005Oct 20 2005

Publication series

NameProceedings - IEEE Military Communications Conference MILCOM


OtherMILCOM 2005: Military Communications Conference 2005
Country/TerritoryUnited States
CityAtlatnic City, NJ


  • Censoring sensors
  • Decision fusion
  • Fading channels
  • Wireless sensor networks

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


Dive into the research topics of 'Robust suboptimal decision fusion in wireless sensor networks'. Together they form a unique fingerprint.

Cite this