Signal detection for mobile devices

Wen Long Chin, Ming Ju Lu

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

Abstract

This study addresses an important challenge of signal detection for the moving devices in cognitive radios over a general non-line-of-sight (NLOS) or line-of-sight (LOS) time-variant multipath fading channel, which is a practical environment for modern mobile communications. To this aim, we propose a new feature detector (FD) based on the likelihood-ratio test (LRT), which suggests us to employ the stationarity of received signals for the signal detection. As such, the detection performance can be greatly enhanced by the proposed technique without needing any channel equalization techniques on received signals. Additionally, two major synchronization impairments are considered which were often neglected in conventional detectors. According to simulation results, the performance of the proposed detector can achieve the detection probability of 0.9 under the false-alarm rate of 0.1 and vehicular speed of 100 km/hr.

Original languageEnglish
Title of host publication2019 7th International Conference on Information and Communication Technology, ICoICT 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538680520
DOIs
Publication statusPublished - 2019 Jul
Event7th International Conference on Information and Communication Technology, ICoICT 2019 - Kuala Lumpur, Malaysia
Duration: 2019 Jul 242019 Jul 26

Publication series

Name2019 7th International Conference on Information and Communication Technology, ICoICT 2019

Conference

Conference7th International Conference on Information and Communication Technology, ICoICT 2019
CountryMalaysia
CityKuala Lumpur
Period19-07-2419-07-26

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Hardware and Architecture

Fingerprint Dive into the research topics of 'Signal detection for mobile devices'. Together they form a unique fingerprint.

Cite this