Decoding Algorithm Based on LDPC for UAV MISO Ultraviolet Communication System

Xue, Xingle; Ji, Junyang; Su, Ping; Ma, Jianshe; Xia, Bizhong; Li, Xingguang

doi:10.1109/lcomm.2024.3371217

IEEE Commun. Lett.

2024

DOI: 10.1109/lcomm.2024.3371217

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Decoding Algorithm Based on LDPC for UAV MISO Ultraviolet Communication System

Xingle Xue,

Junyang Ji,

Ping Su

et al.

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2024

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Cited by 2 publications

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Wireless UV collaborative RSSI and the AOA hybrid localization method for UAV swarms

Zhao,

Li,

Liu

et al. 2024

Appl. Opt.

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Wireless ultraviolet (UV) light can guarantee the inter-copter positioning accuracy of cluster-flying unmanned aerial vehicles (UAVs) in an electromagnetic confrontation environment. By combining wireless UV received signal strength indication (RSSI) localization and the angle of arrival (AOA) localization algorithm, a UV-hybrid localization method is proposed for UV communication collaboration between UAV swarms. The method collects the UV signal strength between the anchor UAV node and the unknown UAV node to obtain the inter-aircraft distance information, establishes a Gaussian hybrid noise model based on semi-definite relaxation, and uses the UV angle of the arrival estimation to solve the angle between the UAVs to achieve the maximum likelihood estimation of node positions in UAV swarms. A simulation comparison of the UV-hybrid localization algorithm, weighted least squares, and the Gaussian hybrid semi-definite planning localization algorithm is carried out. The results show that the performance of the UV-hybrid localization algorithm is close to the Cramer–Rao lower bound, and the average localization error is reduced by 32.9% and 15.6% compared to weighted least squares and Gaussian hybrid semi-definite planning algorithms; the algorithm of this paper achieves the node localization with fewer iterations, and it has a higher accuracy and efficiency of localization than the other algorithms.

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Wireless UV collaborative RSSI and the AOA hybrid localization method for UAV swarms

Zhao,

Li,

Liu

et al. 2024

Appl. Opt.

View full text Add to dashboard Cite

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Omnidirectional path loss model for non-line-of-sight ultraviolet communications

Luo,

Zuo,

et al. 2024

Opt. Express

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To analyze the channel characteristics in omnidirectional reception scenarios for non-line-of-sight ultraviolet (UV) communication, we derive expressions for the reception direction distribution based on the incident photons at the receiver and propose an omnidirectional reception path loss (PL) channel model based on the Monte Carlo (MC) method. Furthermore, we validate the proposed omnidirectional model by comparing it with the existing MC numerical model that traverses all reception directions. Results indicate that the average computation time of the proposed omnidirectional PL model is less than 0.03% of the traversal model while maintaining comparable accuracy. Additionally, we present the variations in off-axis and inclination angles corresponding to the receiver’s direction at different coordinate positions. Therefore, this paper provides valuable guidance for rapidly determining the omnidirectional energy field distribution and optimizing receiver orientation in UV communication systems.

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Decoding Algorithm Based on LDPC for UAV MISO Ultraviolet Communication System

Cited by 2 publications

References 15 publications

Wireless UV collaborative RSSI and the AOA hybrid localization method for UAV swarms

Wireless UV collaborative RSSI and the AOA hybrid localization method for UAV swarms

Omnidirectional path loss model for non-line-of-sight ultraviolet communications

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