Signal detection for mobile devices

Wen Long Chin; Ming Ju Lu

doi:10.1109/ICoICT.2019.8835236

Signal detection for mobile devices

Wen Long Chin, Ming Ju Lu

Department of Engineering Science

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	2019 7th International Conference on Information and Communication Technology, ICoICT 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538680520
DOIs	https://doi.org/10.1109/ICoICT.2019.8835236
Publication status	Published - 2019 Jul
Event	7th International Conference on Information and Communication Technology, ICoICT 2019 - Kuala Lumpur, Malaysia Duration: 2019 Jul 24 → 2019 Jul 26

Publication series

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

Conference

Conference	7th International Conference on Information and Communication Technology, ICoICT 2019
Country	Malaysia
City	Kuala Lumpur
Period	19-07-24 → 19-07-26

All Science Journal Classification (ASJC) codes

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

Access to Document

10.1109/ICoICT.2019.8835236

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Cite this

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title = "Signal detection for mobile devices",

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.",

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year = "2019",

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doi = "10.1109/ICoICT.2019.8835236",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2019 7th International Conference on Information and Communication Technology, ICoICT 2019",

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note = "7th International Conference on Information and Communication Technology, ICoICT 2019 ; Conference date: 24-07-2019 Through 26-07-2019",

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Chin, WL & Lu, MJ 2019, Signal detection for mobile devices. in 2019 7th International Conference on Information and Communication Technology, ICoICT 2019., 8835236, 2019 7th International Conference on Information and Communication Technology, ICoICT 2019, Institute of Electrical and Electronics Engineers Inc., 7th International Conference on Information and Communication Technology, ICoICT 2019, Kuala Lumpur, Malaysia, 19-07-24. https://doi.org/10.1109/ICoICT.2019.8835236

Signal detection for mobile devices. / Chin, Wen Long; Lu, Ming Ju.

2019 7th International Conference on Information and Communication Technology, ICoICT 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8835236 (2019 7th International Conference on Information and Communication Technology, ICoICT 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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