A random search framework for convergence analysis of distributed beamforming with feedback

Che Lin, Venugopal V. Veeravalli, Sean P. Meyn

Research output: Contribution to journalArticlepeer-review


The focus of this work is on the analysis of transmit beamforming schemes with a low-rate feedback link in wireless sensor/relay networks, where nodes in the network need to implement beamforming in a distributed manner. Specifically, the problem of distributed phase alignment is considered, where neither the transmitters nor the receiver has perfect channel state information, but there is a low-rate feedback link from the receiver to the transmitters. In this setting, a framework is proposed for systematically analyzing the performance of distributed beamforming schemes. To illustrate the advantage of this framework, a simple adaptive distributed beamforming scheme that was recently proposed by Mudambai is studied. Two important properties of the received signal magnitude function are derived. Using these properties and the systematic framework, it is shown that the adaptive distributed beamforming scheme converges both in probability and in mean. Furthermore, it is established that the time required for the adaptive scheme to converge in mean scales linearly with respect to the number of sensor/relay nodes.

Original languageEnglish (US)
Article number5625651
Pages (from-to)6133-6141
Number of pages9
JournalIEEE Transactions on Information Theory
Issue number12
StatePublished - Dec 2010


  • Array signal processing
  • convergence of numerical methods
  • detectors
  • distributed algorithms
  • feedback communication
  • networks
  • relays

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences


Dive into the research topics of 'A random search framework for convergence analysis of distributed beamforming with feedback'. Together they form a unique fingerprint.

Cite this