MMSE based block diagonalization for cognitive radio MIMO broadcast channels

Kyoung Jae Lee, Inkyu Lee

Research output: Contribution to journalArticlepeer-review

42 Citations (Scopus)


In this paper, we present a linear precoder design for cognitive radio (CR) multi-user multiple-input multiple-output (MU-MIMO) downlink systems where unlicensed secondary users (SUs) can simultaneously utilize the same spectrum used by a licensed primary user (PU). Although a zero-forcing block diagonalization (ZF-BD) precoder is extended to the CR network with the PU, a transmit power boost problem occurs. Therefore, we propose a regularized BD precoder method based on the minimum mean-squared error (MMSE) criteria subject to the interference power constraint under a predetermined threshold for the PU. As a result, the proposed CR-MMSE-BD scheme improves the signal-to- interference-plus-noise ratio at each SU's receiver, compared to the ZF-BD based method. The simulation results demonstrate that the proposed algorithm outperforms the ZF based technique for CR MU-MIMO downlink systems.

Original languageEnglish
Article number6002431
Pages (from-to)3139-3144
Number of pages6
JournalIEEE Transactions on Wireless Communications
Issue number10
Publication statusPublished - 2011 Oct

Bibliographical note

Funding Information:
Manuscript received October 19, 2010; revised April 10, 2011 and July 6, 2011; accepted July 7, 2011. The associate editor coordinating the review of this paper and approving it for publication was G. Colavolpe. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea Government (MEST) (No. 2010-0017909). The material in this paper was presented in part at IEEE ICC, June 2011. The authors are with the School of Electrical Engineering, Korea University, Seoul, Korea (e-mail: {kyoungjae, inkyu} Digital Object Identifier 10.1109/TWC.2011.081611.101853


  • Cognitive radio
  • block diagonalization (BD)
  • minimum mean-squared error (MMSE)
  • multi-user MIMO

ASJC Scopus subject areas

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


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