光通信研究, 2020 (4): 74, 网络出版: 2020-11-02  

一种低时延无人机自组网阈值自适应接入协议

An Low-Delay Threshold Adaptive Access Protocol for Unmanned Aerial Vehicle Ad Hoc Networks
作者单位
重庆邮电大学 通信与信息工程学院, 重庆 400065
摘要
针对现有无人机自组网(UANET)媒体接入控制协议统计优先级的多址接入协议(SPMA)中存在的满载门限计算过程收敛慢, 满载门限不能随信道承载能力自适应变化的问题, 文章提出了一种低时延UANET阈值自适应接入协议。采用信道满载门限快速收敛机制, 使系统开机后的阈值计算时间缩短, 降低了初始阶段堆积数据的传输时延, 同时采用满载门限自适应调整机制, 使系统能在外部信道环境发生变化时自适应调整信道的满载门限, 从而使信道承载能力与实际的信道负载相匹配, 当信道承载能力下降时通过调整满载门限在维持吞吐量不变的同时提高了数据传输成功率, 降低了数据传输时延。仿真结果表明, 该协议在UANET中消息平均时延、成功率和信道利用率等方面的性能优于现有UANET SPMA。
Abstract
For the existing Unmanned Aerial Vehicle Ad-Hoc Network (UANET)media access control protocol Statistical Priority-based Multiple Access Protocol (SPMA), the full-load threshold calculation process has slow convergence, and the full-load threshold cannot be adaptively changed with the channel carrying capacity. This paper proposes a low-delay UANET threshold adaptive access protocol. The full-load threshold fast convergence mechanism shortens the threshold calculation time after the system is turned on, reduces the transmission delay of the accumulated data in the initial stage, and adopts the full-load threshold adaptive adjustment mechanism. Therefore, the system can be adapted when the external channel environment changes. The full-load threshold of the channel is adjusted, and the channel carrying capacity can match the actual transmission. When the external channel environment changes, the channel’s full load threshold is adaptively adjusted to match the channel load capacity with the actual channel load. When the channel load capacity is reduced, the data can be adjusted to increase the data transmission success rate while maintaining constant throughput with reduced data transmission delay. The simulation results show that the performance of the protocol in the UANET is better than that of the existing UANET SPMA protocol.

任智, 杨迪, 胡春, 朱克兰. 一种低时延无人机自组网阈值自适应接入协议[J]. 光通信研究, 2020, 46(4): 74. REN Zhi, YANG Di, HU Chun, ZHU Ke-lan. An Low-Delay Threshold Adaptive Access Protocol for Unmanned Aerial Vehicle Ad Hoc Networks[J]. Study On Optical Communications, 2020, 46(4): 74.

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