Incremental coding over MIMO channels

Anatoly Khina*, Yuval Kochman, Uri Erez, Gregory W. Wornell

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations


The problem of multicasting common data to several users over multiple-input multiple-output (MIMO) Gaussian channels is studied. A closed-loop setup is considered where the channel matrices are known to the transmitter and respective receivers. An incremental-redundancy (rateless) scenario is considered, where the effective rate is measured by the time that each user needs to stay online until it is able to decode the message. A practical transmission scheme for the two-user case is proposed which, by linear pre and post-processing combined with successive decoding and interference cancellation, transforms the two MIMO channels into a set of parallel channels with no loss of mutual information, where each user needs to tune in for a duration of time proportional to its individual capacity. This scheme is used for designing a practical transmission scheme for the Gaussian MIMO half-duplex relay channel. We then turn to the related scenario of transmission to a single user over a MIMO channel with unknown but constant signal-to-noise ratio (SNR), for which we develop an optimal low-complexity hybrid ARQ coding scheme, which is optimal for two SNRs and propose a scheme for more SNRs, the loss of which vanishes when the SNRs are high. Finally, we show that even when applied to single-input single-output ("scalar") channels, the scheme provides a practical solution for cases not covered by previous work.

Original languageEnglish
Title of host publication2011 IEEE Information Theory Workshop, ITW 2011
Number of pages5
StatePublished - 2011
Event2011 IEEE Information Theory Workshop, ITW 2011 - Paraty, Brazil
Duration: 16 Oct 201120 Oct 2011

Publication series

Name2011 IEEE Information Theory Workshop, ITW 2011


Conference2011 IEEE Information Theory Workshop, ITW 2011


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