# Near/Far-Field Channel Estimation For Terahertz Systems With ELAAs: A Block-Sparse-Aware Approach

arXiv: https://arxiv.org/abs/2404.05544 · HTML: https://mlsanity.com/paper/2404.05544/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Apr 2024.

## Built on by (most cited first, 1 of 1)

- [SPP-SBL: Space-Power Prior Sparse Bayesian Learning for Block Sparse Recovery](https://mlsanity.com/paper/2505.08518/) (2025)

## Abstract (arXiv)

Millimeter wave/Terahertz (mmWave/THz) communication with extremely large-scale antenna arrays (ELAAs) offers a promising solution to meet the escalating demand for high data rates in next-generation communications. A large array aperture, along with the ever increasing carrier frequency within the mmWave/THz bands, leads to a large Rayleigh distance. As a result, the traditional plane-wave assumption may not hold valid for mmWave/THz systems featuring ELAAs. In this paper, we consider the problem of hybrid near/far-field channel estimation by taking spherical wave propagation into account. By analyzing the coherence properties of any two near-field steering vectors, we prove that the hybrid near/far-field channel admits a block-sparse representation on a specially designed orthogonal dictionary. Specifically, the percentage of nonzero elements of such a block-sparse representation decreases in the order of 1/√N, which tends to zero as the number of antennas, N, grows. Such a block-sparse representation allows to convert channel estimation into a block-sparse signal recovery problem. Simulation results are provided to verify our theoretical results and illustrate the performance of the proposed channel estimation approach in comparison with existing state-of-the-art methods.