Joint precoding selection diversity with limited feedback

Hojae Lee, Sanghoon Lee

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Coordinated multiple-point transmission (CoMP) is one of important techniques for the reduction of inter-cluster interference. Three major schemes have been presented for CoMP-joint processing transmission (CoMP-JPT) under limited-feedback environments: global, local, and single-frequency network precoding methods. However, most previous studies have demonstrated effectiveness only in specific environments without presenting numerical analyses. In this paper, we verify the characteristics of each precoding scheme based on zero-forcing beamforming (ZFBF) with semi-orthogonal user selection (SUS) by exploiting numerical analysis. In addition, we propose a selection algorithm that achieves the diversity of the precoding schemes based on limited feedback according to the downlink channel status of cellular systems. In addition, for the 3rd Generation Partnership Project Long Term Evolution-Advanced (3GPP LTE-Advanced), a network protocol that is required to adapt the CoMP-JPT scheme is implemented. Through simulations, we demonstrate that the proposed system can effectively improve the quality of service for cell-edge users while guaranteeing fairness compared to the conventional precoding schemes.

Original languageEnglish
Pages (from-to)141-153
Number of pages13
JournalDigital Signal Processing: A Review Journal
Publication statusPublished - 2014 Jul

Bibliographical note

Funding Information:
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education ( NRF-2013R1A1A2A10011764 ). This research was funded by the MSIP (Ministry of Science, ICT & Future Planning), Korea in the ICT R&D Program 2013.

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Statistics, Probability and Uncertainty
  • Computational Theory and Mathematics
  • Electrical and Electronic Engineering
  • Artificial Intelligence
  • Applied Mathematics


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