Low complexity codebook-based beamforming for MIMO-OFDM systems in millimeter-wave WPAN

Hyun Ho Lee, Young Chai Ko

    Research output: Contribution to journalArticlepeer-review

    43 Citations (Scopus)

    Abstract

    In this paper, we consider a beamforming system in millimeter-wave wireless personal area networks (WPAN), where transmit and receive weight vectors are jointly derived by exchanging a training sequence repeatedly with different combinations of transmit and receive weight vectors. We propose a low complexity codebook-based beamforming scheme that consists of multiple levels and level-adaptive antenna selection in order to reduce the beamforming setup time. For each level, 1) the transmit and receive antennas are selected according to pre-determined inter-element spacings, 2) the training sequences are sent with different weight vectors from a pre-defined codebook and 3) the receiver selects the best transmit and receive weight vectors in order to optimize an effective signal-to-noise ratio (SNR) and these vectors are used to determine the codebook for the next following level. Even with low complexity, we show from the numerical results that our proposed scheme can provide an effective SNR gain and an average spectral efficiency approaching those of the codebook-based beamforming with exhaustive search.

    Original languageEnglish
    Article number6030130
    Pages (from-to)3607-3612
    Number of pages6
    JournalIEEE Transactions on Wireless Communications
    Volume10
    Issue number11
    DOIs
    Publication statusPublished - 2011 Nov

    Bibliographical note

    Funding Information:
    This research was supported by the MKE (The Ministry of Knowledge Economy), Korea, under the ITRC (Information Technology Research Center) support program supervised by the NIPA (National IT Industry Promotion Agency) (NIPA-2011-(C1090-1111-0011)).

    Keywords

    • Codebook-based beamforming
    • MIMO-OFDM
    • millimeter-wave wireless personal area networks

    ASJC Scopus subject areas

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

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