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Mode Identification of OAM with Compressive Sensing in the Secondary Frequency Domain

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Communications and Networking (ChinaCom 2019)

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Abstract

The Electro-Magnetic (EM) waves with Orbital Angular Momentum (OAM) can achieve high spectral efficiency by multiplexing different OAM modes. Different modes are mapped to the frequency shifts in the secondary frequency domain at the receiving end, in order to effectively identify the OAM modes received in partial phase plane. The traditional method requires high-speed acquisition equipment in the process of receiving Radio Frequency (RF) signals directly and its hardware cost is high. Even if analog devices are used for down-conversion to Intermediate Frequency (IF) sampling, the IF bandwidth limits the transmission rate. However, Compressive Sensing (CS) can break the Nyquist restriction by random observation, and is expected to realize the detection and identification of different OAM modes at a lower sampling rate, so that the cost is low. Therefore, this paper proposes an OAM mode identification method based on CS. At the same time, the random sampling is carried out based on the existing hardware device, i.e. Analog-to-Information Converter (AIC), to realize the OAM modes identification with the low sampling rate. The simulation results verify the correctness and effectiveness of the method.

This work is supported by National Natural Science Foundation of China with project number 61731011.

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Authors and Affiliations

  1. Labs of Avionics, School of Aerospace Engineering, Tsinghua University, Beijing, 100084, People’s Republic of China

    Jin Li & Chao Zhang

Authors
  1. Jin Li
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  2. Chao Zhang
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Correspondence to Chao Zhang .

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Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Honghao Gao

  2. School of Computer Software, Tianjin University, Tianjin, China

    Zhiyong Feng

  3. Hangzhou Dianzi University, Hangzhou, China

    Jun Yu

  4. Tongji University, Shanghai Shi, China

    Jun Wu

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Li, J., Zhang, C. (2020). Mode Identification of OAM with Compressive Sensing in the Secondary Frequency Domain. In: Gao, H., Feng, Z., Yu, J., Wu, J. (eds) Communications and Networking. ChinaCom 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 312. Springer, Cham. https://doi.org/10.1007/978-3-030-41114-5_23

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  • DOI: https://doi.org/10.1007/978-3-030-41114-5_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-41113-8

  • Online ISBN: 978-3-030-41114-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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