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Complexity-Efficient Coherent Physical Cell Identity Detection Method for Cellular IoT Systems

Author

Listed:
  • Young-Hwan You

    (Department of Computer Engineering and Convergence Engineering for Intelligent Drone, Sejong University, Seoul 05006, Korea)

  • Yong-An Jung

    (ICT Convergence Research Division, Intelligent Device Research Center, Gumi Electronics & Information Technology Research Institute (GERI), Gumi 39171, Korea)

  • Sung-Hun Lee

    (ICT Convergence Research Division, Intelligent Device Research Center, Gumi Electronics & Information Technology Research Institute (GERI), Gumi 39171, Korea)

  • Intae Hwang

    (Department of Electronic Engineering, Chonnam National University, Yongbong-ro, Buk-gu, Gwangju 61186, Korea
    Department of ICT Convergence System Engineering, Chonnam National University, Yongbong-ro, Buk-gu, Gwangju 61186, Korea)

Abstract

Narrowband Internet of Things (NB-IoT) is one of the low-power wide-area network technologies that aim to support enormous connection, deep coverage, low power consumption, and low cost. Therefore, low cost of implementation and maintenance is one of the key challenges of NB-IoT terminals. This paper presents a low-complexity formulation for narrowband secondary synchronization signal (NSSS) detection in the NB-IoT system, supported by a coherent algorithm that requires a priori knowledge of the channel. By exploiting a symmetric conjugate feature of the NSSS sequence, a joint physical cell ID and radio frame number detection method with low complexity is proposed for coherent detection. The probability of erroneous detection of the presented NSSS detection method is computed, and the analytical model is verified by means of simulation. Numerical experiments will demonstrate that the proposed detection scheme remarkably reduces the computational complexity with almost the same detection ability compared to the existing detection scheme.

Suggested Citation

  • Young-Hwan You & Yong-An Jung & Sung-Hun Lee & Intae Hwang, 2022. "Complexity-Efficient Coherent Physical Cell Identity Detection Method for Cellular IoT Systems," Mathematics, MDPI, vol. 10(16), pages 1-18, August.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:16:p:3024-:d:894693
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    References listed on IDEAS

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    1. Arellano-Valle, Reinaldo B. & Genton, Marc G., 2005. "On fundamental skew distributions," Journal of Multivariate Analysis, Elsevier, vol. 96(1), pages 93-116, September.
    2. Reza Aghazadeh Ayoubi & Umberto Spagnolini, 2022. "Performance of Dense Wireless Networks in 5G and beyond Using Stochastic Geometry," Mathematics, MDPI, vol. 10(7), pages 1-30, April.
    3. Syed Kamran Haider & Ali Nauman & Muhammad Ali Jamshed & Aimin Jiang & Sahar Batool & Sung Won Kim, 2022. "Internet of Drones: Routing Algorithms, Techniques and Challenges," Mathematics, MDPI, vol. 10(9), pages 1-21, April.
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    1. Young-Hwan You & Yong-An Jung & Sung-Hun Lee & Intae Hwang, 2023. "Blockwise Joint Detection of Physical Cell Identity and Carrier Frequency Offset for Narrowband IoT Applications," Mathematics, MDPI, vol. 11(18), pages 1-18, September.

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