A block sparsity based estimator for mmWave Massive MIMO channels with beam squint

Mingjin Wang, Feifei Gao, Nir Shlezinger, Mark F. Flanagan, Yonina C. Eldar

Research output: Contribution to journalArticlepeer-review

46 Scopus citations


Multiple-input multiple-output (MIMO) millimeter wave (mmWave) communication is a key technology for next generation wireless networks. One of the consequences of utilizing a large number of antennas with an increased bandwidth is that array steering vectors vary among different subcarriers. Due to this effect, known as beam squint, the conventional channel model is no longer applicable for mmWave massive MIMO systems. In this paper, we study channel estimation under the resulting non-standard model. To that aim, we first analyze the beam squint effect from an array signal processing perspective, resulting in a model which sheds light on the angle-delay sparsity of mmWave transmission. We next design a compressive sensing based channel estimation algorithm which utilizes the shift-invariant block-sparsity of this channel model. The proposed algorithm jointly computes the off-grid angles, the off-grid delays, and the complex gains of the multi-path channel. We show that the newly proposed scheme reflects the mmWave channel more accurately and results in improved performance compared to traditional approaches. We then demonstrate how this approach can be applied to recover both the uplink as well as the downlink channel in frequency division duplex (FDD) systems, by exploiting the angle-delay reciprocity of mmWave channels.

Original languageEnglish
Article number8917662
Pages (from-to)49-64
Number of pages16
JournalIEEE Transactions on Signal Processing
StatePublished - 1 Jan 2020
Externally publishedYes


  • angle-delay reciprocity
  • beam squint
  • block sparsity
  • channel estimation
  • massive MIMO
  • mmWave

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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