Cross-Field Channel Estimation for Ultra Massive-MIMO THz Systems

Simon Tarboush, Anum Ali, Tareq Y. Al-Naffouri

Research output: Contribution to journalArticlepeer-review


The large bandwidth combined with ultra-massive multiple-input multiple-output (UM-MIMO) arrays enables terahertz (THz) systems to achieve terabits-per-second throughput. The THz systems are expected to operate in the near, intermediate, as well as the far-field. As such, channel estimation strategies suitable for the near, intermediate, or far-field have been introduced in the literature. In this work, we propose a cross-field, i.e., able to operate in near, intermediate, and farfield, compressive channel estimation strategy. For an array-of-subarrays (AoSA) architecture, the proposed method compares the received signals across the arrays to determine whether a near, intermediate, or far-field channel estimation approach will be appropriate. Subsequently, compressed estimation is performed in which the proximity of multiple subarrays (SAs) at the transmitter and receiver is exploited to reduce computational complexity and increase estimation accuracy. Numerical results show that the proposed method can enhance channel estimation accuracy and complexity at all distances of interest.

Original languageEnglish (US)
Pages (from-to)1
Number of pages1
JournalIEEE Transactions on Wireless Communications
StateAccepted/In press - 2024


  • array-of-subarrays
  • far-field
  • hybrid spherical-planar wave model
  • intermediate-field
  • Near-field
  • planar wave model
  • spherical wave model

ASJC Scopus subject areas

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


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