Detection of FHMA/MFSK signals based on SVM techniques

Jen Yang Liu*, Yu-Ted Su

*Corresponding author for this work

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

Abstract

This paper documents an initial effort in detecting frequency-hopped (FH) signals in a multiple access (MA) environment from a machine learning perspective. Although, the offline training might require very intensive computing power, the extracted information does has a concise representation, which then enables to detect a signal using only simple and low-power operations. Frequency-hopping is an attractive alternative multiple access technique for direct sequence based code division multiple access (CDMA) schemes. Other than the communication channel statistic, the capacity of an FHMA system is determined by two major related design concerns: waveform design and receiver structure. Given the FH waveform, one still has difficulty in designing an FHMA ML receiver due to the facts that our knowledge about the channel statistics is often incomplete and even if it is complete the associated conditional probability density function (pdf) does not render a closed-form expression. Regarding the FHMA/MFSK waveform as a time-frequency pattern, we convert the multiuser detection problem into a pattern classification problem and then resolve to the Support Vector Machine (SVM) approach for solving the resulting multiple-class classification problem. By using an appropriate kernel function, the SVM essentially transforms the received signal space into a higher dimension feature space. We propose a SVM-based FHMA/MFSK receiver by applying the Sequential Minimization Optimization (SMO) and Directed Acyclic Graph (DAG) algorithms to find the optimal separating hyperplanes in the feature space. Simulation results indicate that our design does yield robust and satisfactory performance.

Original languageEnglish
Title of host publicationIWCMC 2006 - Proceedings of the 2006 International Wireless Communications and Mobile Computing Conference
Pages1423-1428
Number of pages6
DOIs
StatePublished - 1 Dec 2006
EventIWCMC 2006 - 2006 International Wireless Communications and Mobile Computing Conference - Vancouver, BC, Canada
Duration: 3 Jul 20066 Jul 2006

Publication series

NameIWCMC 2006 - Proceedings of the 2006 International Wireless Communications and Mobile Computing Conference
Volume2006

Conference

ConferenceIWCMC 2006 - 2006 International Wireless Communications and Mobile Computing Conference
CountryCanada
CityVancouver, BC
Period3/07/066/07/06

Keywords

  • Support Vector Machine (SVM)

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  • Cite this

    Liu, J. Y., & Su, Y-T. (2006). Detection of FHMA/MFSK signals based on SVM techniques. In IWCMC 2006 - Proceedings of the 2006 International Wireless Communications and Mobile Computing Conference (pp. 1423-1428). (IWCMC 2006 - Proceedings of the 2006 International Wireless Communications and Mobile Computing Conference; Vol. 2006). https://doi.org/10.1145/1143549.1143834