Adaptive Channel Division and Subchannel Allocation for Orthogonal Frequency Division Multiple Access-Based Airborne Power Line Communication Networks

This paper addresses the critical needs of the aviation industry in advancing towards More Electric Aircraft (MEA) by leveraging power line communication (PLC) technology, which merges data and power transmission to offer substantial reductions in aircraft system weight and cost. We introduce pioneering algorithms for channel division and subchannel allocation within Orthogonal Frequency Division Multiple Access (OFDMA)-based airborne PLC networks, aimed at optimizing network performance in key areas such as throughput, average delay, and fairness. The proposed channel division algorithm dynamically adjusts the count of subchannels to maximize Channel Division Gain (CDG), responding adeptly to fluctuations in network conditions and node density. Concurrently, the subchannel allocation algorithm employs a novel metric, the Subchannel Preference Score (SPS), which factors in both the signal quality and the current occupancy levels of each subchannel to determine their optimal allocation among nodes. This method ensures efficient resource utilization and maintains consistent network performance. Extensive simulations, conducted using the OMNeT++ simulator, have demonstrated that our adaptive algorithms significantly outperform existing methods, providing higher throughput, reduced delays, and improved fairness across the network. These advancements represent a significant leap in MAC protocol design for airborne PLC systems. The outcomes suggest that our algorithms offer a robust and adaptable solution, aligning with the rigorous demands of modern avionics and paving the way for the future integration of MEA technologies.

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Publication Details

Journal
Sensors
Published
2024-11-29
DOI
https://doi.org/10.3390/s24237644
Citations
2
Primary Topic
Power Line Communications and Noise
Type
article
Field-Weighted Citation Impact
0.42
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article

Adaptive Channel Division and Subchannel Allocation for Orthogonal Frequency Division Multiple Access-Based Airborne Power Line Communication Networks

Qiao Li, Ruowen Yan, Huagang Xiong
2 citations
Sensors
Power Line Communications and Noise
0.42
article

Adaptive Channel Division and Subchannel Allocation for Orthogonal Frequency Division Multiple Access-Based Airborne Power Line Communication Networks

Qiao Li, Ruowen Yan, Huagang Xiong
article en
2 citations

Abstract

This paper addresses the critical needs of the aviation industry in advancing towards More Electric Aircraft (MEA) by leveraging power line communication (PLC) technology, which merges data and power transmission to offer substantial reductions in aircraft system weight and cost. We introduce pioneering algorithms for channel division and subchannel allocation within Orthogonal Frequency Division Multiple Access (OFDMA)-based airborne PLC networks, aimed at optimizing network performance in key areas such as throughput, average delay, and fairness. The proposed channel division algorithm dynamically adjusts the count of subchannels to maximize Channel Division Gain (CDG), responding adeptly to fluctuations in network conditions and node density. Concurrently, the subchannel allocation algorithm employs a novel metric, the Subchannel Preference Score (SPS), which factors in both the signal quality and the current occupancy levels of each subchannel to determine their optimal allocation among nodes. This method ensures efficient resource utilization and maintains consistent network performance. Extensive simulations, conducted using the OMNeT++ simulator, have demonstrated that our adaptive algorithms significantly outperform existing methods, providing higher throughput, reduced delays, and improved fairness across the network. These advancements represent a significant leap in MAC protocol design for airborne PLC systems. The outcomes suggest that our algorithms offer a robust and adaptable solution, aligning with the rigorous demands of modern avionics and paving the way for the future integration of MEA technologies.

SensorsVol. 24(23)
Beihang University (CN)
Openalex Percentile: Top 36%
Power Line Communications and Noise
0.42
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