Uplink Power Allocation for Distributed Interference Cancellation With Channel Estimation Error

Khalid Zeineddine, Michael L. Honig, Shirish Nagaraj

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

A distributed interference cancellation scheme for cellular networks is considered, in which a subset of receivers forward their decoded messages to another subset of receivers. The messages can then be used to cancel interference with estimated cross-channel gains. A distributed power control algorithm is presented that harnesses the gain of interference cancellation and that considers channel estimation error. The algorithm is based on the exchange of interference prices, but in this case, the local power updates are not concave due to nonlinear terms introduced by channel estimation errors. A partial cancellation scheme is then presented, where the power updates are derived in closed form. We show that the algorithm converges to a local optimum of the weighted sum-rate maximization problem. Two methods for sorting users into the two groups that, respectively, forward and receive the decoded messages are presented. The first is sequential and is shown to converge to a local optimum. The second is a simple heuristic that is based on a stochastic geometric approach. Numerical results show that power control and adaptive partitioning of the users can add substantial gains to interference cancellation.

Original languageEnglish (US)
Article number7509642
Pages (from-to)6785-6796
Number of pages12
JournalIEEE Transactions on Wireless Communications
Volume15
Issue number10
DOIs
StatePublished - Oct 2016

Funding

This work was supported in part by Nokia and in part by Northwestern University.

Keywords

  • Distributed power control
  • channel estimation error
  • coordinated multi-point
  • distributed interference cancellation
  • fractional power control
  • interference prices
  • multi-cell processing
  • stochastic geometry
  • uplink channel

ASJC Scopus subject areas

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

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