Interference-Aware Queuing Analysis for Distributed Transmission Control in UAV Networks

Masoud Ghazikor, Keenan Roach, Kenny Cheung, Morteza Hashemi
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Abstract

In this paper, we investigate the problem of distributed transmission control for unmanned aerial vehicles (UAVs) operating in unlicensed spectrum bands. We develop a rigorous interference-aware queuing analysis framework that jointly considers two inter-dependent factors: (i) limited-size queues with delay-constrained packet arrival, and (ii) in-band interference introduced by other ground/aerial users. We aim to optimize the expected throughput by jointly analyzing these factors. In the queuing analysis, we explore two packet loss probabilities including, buffer overflow model and time threshold model. For interference analysis, we investigate the outage probability and packet losses due to low signal-to-interference-plus-noise ratio (SINR). We introduce two algorithms namely, Interference-Aware Transmission Control (IA-TC), and Interference-Aware Distributed Transmission Control (IA-DTC). These algorithms maximize the expected throughput by adjusting transmission policies to balance the trade-offs between packet drop from queues vs. transmission errors due to low SINRs. We implement the proposed algorithms and demonstrate that the optimal transmission policy under various scenarios is found.
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无人机网络分布式传输控制的干扰感知排队分析
在本文中,我们研究了在未授权频段运行的无人驾驶飞行器(UAV)的分布式传输控制问题。我们开发了一个严格的干扰感知队列分析框架,该框架联合考虑了两个相互依存的因素:(i) 有限大小的队列和延迟受限的数据包到达,以及 (ii) 其他地面/空中用户引入的带内干扰。我们的目标是通过联合分析这些因素来优化预期吞吐量。在队列分析中,我们探讨了两种丢包概率,包括缓冲区溢出模型和时间阈值模型。在干扰分析中,我们研究了低信号干扰加噪声比(SINR)导致的中断概率和丢包情况。我们引入了两种算法,即干扰感知传输控制(IA-TC)和干扰感知分布式传输控制(IA-DTC)。这些算法通过调整传输策略来平衡队列中的数据包丢弃与低信噪比导致的传输错误之间的权衡,从而最大限度地提高预期吞吐量。我们实现了所提出的算法,并证明在各种情况下都能找到最佳传输策略。
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