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Volume 43 Issue 12
Dec.  2021
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Guihui XIE, Xiaoqing TANG, Xiangkai JIAO, Ruyan LI. A Lightweight Enhanced Long Range Physical Layer Design Method for Internet of Things[J]. Journal of Electronics & Information Technology, 2021, 43(12): 3612-3620. doi: 10.11999/JEIT200734
Citation: Guihui XIE, Xiaoqing TANG, Xiangkai JIAO, Ruyan LI. A Lightweight Enhanced Long Range Physical Layer Design Method for Internet of Things[J]. Journal of Electronics & Information Technology, 2021, 43(12): 3612-3620. doi: 10.11999/JEIT200734

A Lightweight Enhanced Long Range Physical Layer Design Method for Internet of Things

doi: 10.11999/JEIT200734
Funds:  The Natural Science Foundation of Hubei Province (2019CFB271), The Science and Technology Project of Zhongshan City(2019AG032)
  • Received Date: 2020-08-20
  • Rev Recd Date: 2021-02-07
  • Available Online: 2021-03-22
  • Publish Date: 2021-12-21
  • To improve the bit error rate performance of LoRa (Long Range) in fading channels, a lightweight Enhanced Long Range (EnLoRa) physical layer is designed. First, Cyclic Code Shift Keying (CCSK) is chosen as the error correction code, and the diagonal matrix interleaving and Chirp Spread Spectrum (CSS) modulation techniques are concatenated to construct a new Bit Interleaved Coded Modulation (BICM) structure. Then, based on this structure, a soft CSS demodulation and soft decoding algorithm based on bit log-likelihood ratio information is proposed. Further, the decoded external information is fed back to the demodulation module as a priori information for iteration decoding. The simulation results show that, compared with the LoRa system of the same code rate, the coding gain of the EnLoRa system under the Gaussian channel is increased by 0.8 dB, and the coding gain under the Rayleigh channel is increased by 7 dB. On this basis, through multiple iterations, an additional gain of up to 2.5 dB can be obtained. The time complexity is only increased by 10%, and the increase in space complexity is negligible. This method is expected to reduce further the power consumption of LoRa nodes and has great application value to complex multipath scenarios such as indoors, urban areas and industries.
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