Local interference pricing for distributed beamforming in MIMO networks

Changxin Shi*, Randall A. Berry, Michael L. Honig

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Scopus citations


We study a distributed algorithm for adjusting beamforming vectors in a peer-to-peer wireless network with multiple-input multiple-output (MIMO) channels. Each transmitter precoding matrix has rank one, and a linear minimum mean squared error (MMSE) filter is applied at each receiver. Our objective is to maximize the total utility summed over all users, where each user's utility is a function of the received signal-to-interference-plus-noise ratio (SINR). Given all users' beamforming vectors and receive filters, each receiver announces an interference price, representing the marginal cost of interference from other users. A particular transmitter updates its beamforming vector to maximize its utility minus the interference cost to other users. We show that if the utility functions satisfy certain concavity conditions, then the total utility is non-decreasing with each update. We also present numerical results that illustrate the effect of ignoring interference prices from all but the closest users, and relaxing requirements on the frequency of beam and price updates.

Original languageEnglish (US)
Title of host publicationMILCOM 2009 - 2009 IEEE Military Communications Conference
StatePublished - 2009
Event2009 IEEE Military Communications Conference, MILCOM 2009 - Boston, MA, United States
Duration: Oct 18 2009Oct 21 2009

Publication series

NameProceedings - IEEE Military Communications Conference MILCOM


Other2009 IEEE Military Communications Conference, MILCOM 2009
Country/TerritoryUnited States
CityBoston, MA

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


Dive into the research topics of 'Local interference pricing for distributed beamforming in MIMO networks'. Together they form a unique fingerprint.

Cite this