Low-complexity cyclostationarity feature detection scheme of localized SC-FDMA uplink system for application to detect and avoid

Wensheng Zhang, Yukitoshi Sanada

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This paper proposes a low-complexity cyclostationarity feature detection scheme for detect and avoid (DAA) of Ultra-Wideband (UWB) system in order to solve the coexistence issues between UWB system and Long Term Evolution-Advanced (LTE-Advanced) system. The proposed scheme is suitable for the detection of a localized Single-carrier Frequency Division Multiple Access (SC-FDMA) signal utilized in the uplink of LTEAdvanced system. Compared with conventional cyclostationarity feature detection, the proposed scheme utilizes all possible cyclic-spectrums located in a distributed window function, which is decided by the frequency distribution of the Primary User (PU) signal. The computational complexity of the proposed scheme is low, due to only one window width instead of all occupied spectrum interval will be searched for the possible cyclic-spectrums. On the other hand, the proposed scheme can also avoid the estimation of the cyclic-spectrums when the type of PU signal is unclear or the cyclic-spectrums are hard to estimate. Simulation results indicate that the proposed scheme can make a tradeoff between detection performance and computational complexity. The low-complexity cyclostationarity feature detection also provides a substitute for the energy detection when the later approach suffers from the noise uncertainty and cannot distinguish the target signal type.

Original languageEnglish
Pages (from-to)307-319
Number of pages13
JournalWireless Personal Communications
Volume66
Issue number2
DOIs
Publication statusPublished - 2012 Sep

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Frequency division multiple access
Ultra-wideband (UWB)
Computational complexity
Long Term Evolution (LTE)
Uncertainty

Keywords

  • Cyclostationarity feature detection
  • DAA
  • SC-FDMA

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications

Cite this

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abstract = "This paper proposes a low-complexity cyclostationarity feature detection scheme for detect and avoid (DAA) of Ultra-Wideband (UWB) system in order to solve the coexistence issues between UWB system and Long Term Evolution-Advanced (LTE-Advanced) system. The proposed scheme is suitable for the detection of a localized Single-carrier Frequency Division Multiple Access (SC-FDMA) signal utilized in the uplink of LTEAdvanced system. Compared with conventional cyclostationarity feature detection, the proposed scheme utilizes all possible cyclic-spectrums located in a distributed window function, which is decided by the frequency distribution of the Primary User (PU) signal. The computational complexity of the proposed scheme is low, due to only one window width instead of all occupied spectrum interval will be searched for the possible cyclic-spectrums. On the other hand, the proposed scheme can also avoid the estimation of the cyclic-spectrums when the type of PU signal is unclear or the cyclic-spectrums are hard to estimate. Simulation results indicate that the proposed scheme can make a tradeoff between detection performance and computational complexity. The low-complexity cyclostationarity feature detection also provides a substitute for the energy detection when the later approach suffers from the noise uncertainty and cannot distinguish the target signal type.",
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AB - This paper proposes a low-complexity cyclostationarity feature detection scheme for detect and avoid (DAA) of Ultra-Wideband (UWB) system in order to solve the coexistence issues between UWB system and Long Term Evolution-Advanced (LTE-Advanced) system. The proposed scheme is suitable for the detection of a localized Single-carrier Frequency Division Multiple Access (SC-FDMA) signal utilized in the uplink of LTEAdvanced system. Compared with conventional cyclostationarity feature detection, the proposed scheme utilizes all possible cyclic-spectrums located in a distributed window function, which is decided by the frequency distribution of the Primary User (PU) signal. The computational complexity of the proposed scheme is low, due to only one window width instead of all occupied spectrum interval will be searched for the possible cyclic-spectrums. On the other hand, the proposed scheme can also avoid the estimation of the cyclic-spectrums when the type of PU signal is unclear or the cyclic-spectrums are hard to estimate. Simulation results indicate that the proposed scheme can make a tradeoff between detection performance and computational complexity. The low-complexity cyclostationarity feature detection also provides a substitute for the energy detection when the later approach suffers from the noise uncertainty and cannot distinguish the target signal type.

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