Automatic modulation format/bit-rate classification and signal-to-noise ratio estimation using asynchronous delay-tap sampling

Faisal Nadeem Khan, Chiew Hoon Teow, Shiu Guong Kiu, Ming Chieng Tan, Yudi Zhou, Waled Hussein Al-Arashi, Pak Tao Lau, Chao Lu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

24 Citations (Scopus)


We propose a novel technique for automatic classification of modulation formats/bit-rates of digitally modulated signals as well as non-data-aided (NDA) estimation of signal-to-noise ratio (SNR) in wireless networks. The proposed technique exploits modulation format, bit-rate, and SNR sensitive features of asynchronous delay-tap plots (ADTPs) for the joint estimation of these parameters. Simulation results validate successful classification of three commonly-used modulation formats at two different bit-rates with an overall accuracy of 99.12%. Similarly, in-service estimation of SNR in the range of 0-30 dB is demonstrated with mean estimation error of 0.88 dB. The proposed technique requires low-speed asynchronous sampling of signal envelope and hence, it can enable simple and cost-effective joint modulation format/bit-rate classification and NDA SNR estimation in future wireless networks.
Original languageEnglish
Pages (from-to)126-133
Number of pages8
JournalComputers and Electrical Engineering
Publication statusPublished - 1 Jan 2015


  • Asynchronous delay-tap sampling
  • Automatic modulation classification
  • Automatic modulation format and bit-rate classification
  • SNR estimation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)
  • Electrical and Electronic Engineering

Cite this