Optimal channel training in uplink network MIMO systems

Jakob Hoydis, Mari Kobayashi, Mérouane Debbah

Research output: Contribution to journalArticlepeer-review

58 Scopus citations

Abstract

We consider a multicell frequency-selective fading uplink channel (network MIMO) from K single-antenna user terminals (UTs) to B cooperative base stations (BSs) with M antennas each. The BSs, assumed to be oblivious of the applied codebooks, forward compressed versions of their observations to a central station (CS) via capacity limited backhaul links. The CS jointly decodes the messages from all UTs. Since the BSs and the CS are assumed to have no prior channel state information (CSI), the channel needs to be estimated during its coherence time. Based on a lower bound of the ergodic mutual information, we determine the optimal fraction of the coherence time used for channel training, taking different path losses between the UTs and the BSs into account. We then study how the optimal training length is impacted by the backhaul capacity. Although our analytical results are based on a large system limit, we show by simulations that they provide very accurate approximations for even small system dimensions.

Original languageEnglish
Article number5733435
Pages (from-to)2824-2833
Number of pages10
JournalIEEE Transactions on Signal Processing
Volume59
Issue number6
DOIs
StatePublished - Jun 2011
Externally publishedYes

Keywords

  • Channel estimation
  • coordinated multi-point (CoMP)
  • imperfect channel state information (CSI)
  • multicell processing
  • network MIMO
  • random matrix theory

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