A New Approach for Enhanced Detection Using Chirp Reference Signals

Ana Belen Martinez, Atul Kumar, Marwa Chafii, Gerhard Fettweis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Matched filtering based on linear frequency modulated (LFM) or chirp signals constitutes a reliable approach for frame detection even in the presence of high carrier frequency offsets (CFOs). However, the use of polyphase codes as discrete versions of LFM signals can lead to strong degradation at the output of the matched filter for certain CFO conditions and sequence lengths, yielding missed detection. This work proposes a new approach to improve the probability of detection achievable with matched filtering for these unfavorable situations. The proposed approach exploits the symmetry of a reference sequence that consists of a polyphase code followed by its complex conjugate with an algorithm based on reversed autocorrelation (RC) and successfully utilizes the robustness of RC against CFO for detection. It is shown that joint detection based on matched filtering and RC can enhance the detection performance significantly compared to conventional matched filtering.

Original languageEnglish (US)
Title of host publication2020 IEEE 92nd Vehicular Technology Conference, VTC 2020-Fall - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728194844
DOIs
StatePublished - Nov 2020
Event92nd IEEE Vehicular Technology Conference, VTC 2020-Fall - Virtual, Victoria, Canada
Duration: Nov 18 2020 → …

Publication series

NameIEEE Vehicular Technology Conference
Volume2020-November
ISSN (Print)1550-2252

Conference

Conference92nd IEEE Vehicular Technology Conference, VTC 2020-Fall
Country/TerritoryCanada
CityVirtual, Victoria
Period11/18/20 → …

Keywords

  • Detection probability
  • carrier frequency offset
  • chirp
  • matched filter
  • polyphase code
  • reversed autocorrelation

ASJC Scopus subject areas

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

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