Block diagonalized vector perturbation for multiuser MIMO systems

Chan Byoung Chae, Seijoon Shim, Robert W. Heath

Research output: Contribution to journalArticlepeer-review

68 Citations (Scopus)


Precoding with block diagonalization (BD) is an attractive technique for approaching the sum capacity in the multiuser multiple-input multiple-output (MIMO) broadcast channel. Unfortunately, BD requires either global channel state information at every receiver or an additional training phase, which demands additional control overhead and additional system planning. In this paper we propose a new multiuser MIMO algorithm that combines BD with vector perturbation (VP). The proposed algorithm avoids the second training phase, reduces each user's receiver complexity thanks to pre-equalization with VP at the transmitter, and has comparable diversity performance to BD with maximum likelihood decoding algorithm. A bound on the achievable sum rate for the proposed technique is derived and used to show that BD with VP approaches the achievable sum rate of BD with water-filling. Numerical simulations confirm that the proposed technique provides better bit error rate and diversity performance than BD with a zero-forcing receiver as well as BD with zero-forcing precoding.

Original languageEnglish
Article number4684576
Pages (from-to)4051-4057
Number of pages7
JournalIEEE Transactions on Wireless Communications
Issue number11
Publication statusPublished - 2008 Nov

Bibliographical note

Funding Information:
Manuscript received January 27, 2007; revised November 21, 2007 and July 26, 2008; accepted September 17, 2008. The associate editor coordinating the review of this paper and approving it for publication was S. Blostein. This work was supported in part by Samsung Electronics, and also supported in part by the Korea Research Foundation Grant (KRF-2005-214-D00319) funded by the Korean Government (MOEHRD). This paper was presented in part at the IEEE Global Telecommunications Conference, San Francisco, CA, November/December 2006.

All Science Journal Classification (ASJC) codes

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


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