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Novel Algorithm for Blind Classification of Space-Time Block Codes in Cognitive Radio

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Advances in Swarm Intelligence (ICSI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11656))

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Abstract

The blind classification of space-time block codes (STBCs) is a key research issue related to cognitive radio. There have been numerous studies attempting to classify STBCs, but the blind classification of STBCs with transmission impairments merits further research. The novel blind classification algorithm proposed in this paper exploits the fourth-order cyclostationarity of STBCs to classify them with a single receiver antenna in the presence of transmission impairments. The proposed algorithm relies on the fourth-order cyclic moment as a discriminating feature and employs the distance between adjacent spectral lines to classify the transmitted STBCs. As opposed to other methods, this algorithm does not require a priori information regarding the modulation scheme, channel coefficients, or noise power; consequently, it is very well-suited to non-cooperative scenarios. According to rough estimation of symbol duration and carrier frequency offset, the distance between adjacent spectral lines remains almost the same with value dependent on the transmitted STBCs. Simulations indicate that the proposed method performs well even at low signal-to-noise ratios (SNRs).

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Authors and Affiliations

  1. Naval Aviation University, Yantai, 264001, China

    Wenjun Yan, Qing Ling & Limin Zhang

Authors
  1. Wenjun Yan
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  2. Qing Ling
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  3. Limin Zhang
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Corresponding author

Correspondence to Wenjun Yan .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

  3. Shenzhen University, Shenzhen, China

    Ben Niu

Appendix

Appendix

The STBCs under consideration are SM, AL, ST3 and ST4. The corresponding transmission matrices are

$$\begin{aligned}&C^{(SM)}=\left[ \begin{array}{c} x_1 \\ x_2 \\ \end{array} \right] ,&C^{(ST3)}=\left[ \begin{array}{cccc} x_1 &{} -x_2^* &{} x_3^* &{} 0 \\ x_2 &{} x_1^* &{} 0 &{} -x_3^* \\ x_3 &{} 0 &{} -x_1^* &{} x_2^* \\ \end{array} \right]&\\&C^{(AL)}=\left[ \begin{array}{cc} x_1 &{} -x_2^* \\ x_2 &{} x_1^* \\ \end{array} \right] ,&C^{(ST4)}=\left[ \begin{array}{cccccccc} x_1 &{} -x_2 &{} -x_3 &{} -x_4 &{} x_1^* &{} -x_2^* &{} -x_3^* &{} -x_4^* \\ x_2 &{} x_1 &{} x_4 &{} -x_3 &{} x_2^* &{} x_1^* &{} x_4^* &{} -x_3^* \\ x_3 &{} -x_4 &{} x_1 &{} x_2 &{} x_3^* &{} -x_4^* &{} x_1^* &{} x_2^* \\ \end{array} \right] \end{aligned}$$

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Yan, W., Ling, Q., Zhang, L. (2019). Novel Algorithm for Blind Classification of Space-Time Block Codes in Cognitive Radio. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2019. Lecture Notes in Computer Science(), vol 11656. Springer, Cham. https://doi.org/10.1007/978-3-030-26354-6_15

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  • DOI: https://doi.org/10.1007/978-3-030-26354-6_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26353-9

  • Online ISBN: 978-3-030-26354-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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