Unmanned aerial vehicles (UAVs) have been increasingly deployed in various real-time applications that require wireless communication with high reliability and low latency. To meet these demands, Low-Density Parity-Check (LDPC) codes, adopted in the 5G New Radio (NR) standard, has emerged as a promising solution. This paper analyzes the performance of standardized 5G NR LDPC codes using different lifting sizes for UAV communication under specific settings and multiple trajectories, including circular, helical, Lissajous, and lawn-mower paths. The reliability of communication is evaluated in terms of bit error rate (BER), considering both free-space path loss and additive white Gaussian noise (AWGN) as sources of channel degradation. Simulation results show that LDPC coding significantly reduces the BER of UAV communication, especially at longer distances. Although different trajectories cause an uneven distribution of BER, adapting the size of the LDPC sparse parity-check matrix helps maintain the reliability of UAV communication even under low-quality channel conditions.

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Performance Analysis of LDPC Codes in 5G NR for Unmanned Aerial Vehicle Communication

  • Dang Ninh Tran

摘要

Unmanned aerial vehicles (UAVs) have been increasingly deployed in various real-time applications that require wireless communication with high reliability and low latency. To meet these demands, Low-Density Parity-Check (LDPC) codes, adopted in the 5G New Radio (NR) standard, has emerged as a promising solution. This paper analyzes the performance of standardized 5G NR LDPC codes using different lifting sizes for UAV communication under specific settings and multiple trajectories, including circular, helical, Lissajous, and lawn-mower paths. The reliability of communication is evaluated in terms of bit error rate (BER), considering both free-space path loss and additive white Gaussian noise (AWGN) as sources of channel degradation. Simulation results show that LDPC coding significantly reduces the BER of UAV communication, especially at longer distances. Although different trajectories cause an uneven distribution of BER, adapting the size of the LDPC sparse parity-check matrix helps maintain the reliability of UAV communication even under low-quality channel conditions.