Two-dimensional embedded sequence pilot-aided channel estimation scheme for OTFS systems
DOI:
CSTR:
Author:
Affiliation:

1.The 54th Research Institute of CETC,Shijiazhuang 050081, China; 2.School of Telecommunications Engineering, Xidian University,Xi′an 710071, China

Clc Number:

TN929.5

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Addressing the prevalent issues of low resource utilization, incompatibility with multi-antennas, and inadequate estimation accuracy in gonal frequency division multiplexing(OTFS) pilot designs, a novel embedded pilot sequence design scheme is proposed,based on which the high accuracy channel estimation algorithm is addressed. Specifically, the proposed pilot sequence is consisted of multiple ZC sequences deployed across the Doppler domain and cascaded in the delay domain, and each ZC sequence is derived from a common root sequence through cyclic shifts of varying lengths. At the receiver, multiple channel estimations are conducted using local sequences and each corresponding received signal sequence, followed by averaging for enhanced channel state information accuracy. Based on these estimates and local sequences, interference from the pilot signal to the data signal can be cancelled. Due to the excellent orthogonality of ZC sequences, this scheme can adapt to multi-antennas systems by employing different root sequences, and this scheme markedly improves pilot accumulated signal-to-noise ratio and correspondingly the channel estimation accuracy. Simulation results show that the proposed scheme has about 6 dB signal-to-noise ratio gain for the same channel estimation accuracy, and bit-to-error rate is better, as compared to the traditional scheme, which proves that the proposed scheme has the advantages of promising performance and being very valuable to promote practicality.

    Reference
    Related
    Cited by
Get Citation
Related Videos

Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:
  • Revised:
  • Adopted:
  • Online: September 04,2025
  • Published:
Article QR Code