Distributed power control in the SINR model

Zvi Lotker, Merav Parter, David Peleg, Yvonne Anne Pignolet

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations


The power control problem for wireless networks in the SINR model requires determining the optimal power assignment for a set of communication requests such that the SINR threshold is met for all receivers. If the network topology is known to all participants, then it is possible to compute an optimal power assignment in polynomial time. In realistic environments, however, such global knowledge is usually not available to every node. In addition, protocols that are based on global computation cannot support mobility and hardly adapt when participants dynamically join or leave the system. In this paper we present and analyze a fully distributed power control protocol that is based on local information. For a set of communication pairs, each consisting of a sender node and a designated receiver node, the algorithm enables the nodes to converge to the optimal power assignment (if there is one under the given constraints) quickly with high probability. Two types of bounded resources are considered, namely, the maximal transmission energy and the maximum distance between any sender and receiver. It is shown that the restriction to local computation increases the convergence rate by only a multiplicative factor of O(log n + log log ψ max), where ψmax is the maximal power constraint of the network. If the diameter of the network is bounded by L max then the increase in convergence rate is given by O(log n + log log Lmax).

Original languageEnglish
Title of host publication2011 Proceedings IEEE INFOCOM
Number of pages9
StatePublished - 2011
Externally publishedYes
EventIEEE INFOCOM 2011 - Shanghai, China
Duration: 10 Apr 201115 Apr 2011

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


ConferenceIEEE INFOCOM 2011


Dive into the research topics of 'Distributed power control in the SINR model'. Together they form a unique fingerprint.

Cite this