Decentralized joint precoding with pilot-aided beamformer estimation

Jarkko Kaleva*, Antti Tolli, Markku Juntti, Randall A. Berry, Michael L. Honig

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


Downlink beamforming techniques with low beamformer training overhead are proposed for joint processing (JP) coordinated multipoint transmission (CoMP). The objective is to maximize the weighted sum rate within joint transmission clusters without centralized beamformer processing, while accounting for uncertainty in the underlying channels. The proposed methods use time-division duplexing and pilot-based training with, possibly, nonorthogonal pilot sequences. The beamformer training is done without the explicit channel state information estimation, which greatly improves the robustness to pilot contamination. Best response and gradient-based decentralized algorithms are proposed and provide a tradeoff between computational complexity and fast convergence rate. The impact of feedback/backhaul quantization is also considered. The results show that JP CoMP is feasible with slow fading conditions and limited backhaul capacity by employing decentralized beamformer processing.

Original languageEnglish (US)
Pages (from-to)2330-2341
Number of pages12
JournalIEEE Transactions on Signal Processing
Issue number9
StatePublished - May 1 2018


  • Coordinated multi-point transmission
  • decentralized beamforming
  • joint processing
  • pilot training
  • weighted sum rate maximization

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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