Distributed scheduling for unmanned aerial vehicle networks with full-duplex radios and multi-packet reception

Yegui Cai, F. Yu, Jun Li, Yifeng Zhou, L. Lamont
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引用次数: 4

Abstract

Applications of unmanned aerial vehicle (UAV) ad-hoc networks have raised challenges in the design of distributed scheduling schemes since those applications require stringent quality of service (QoS) in complicated environments. Most existing scheduling designs for UAV ad-hoc networks are based on traditional physical layer techniques, such as half-duplex radios without multi-packet reception capability. However, recent advances in interference cancellation and signal processing techniques can enable full-duplex radios (FDR) and multi-packet reception (MPR) capability, which will have significant impacts on the design of link layer algorithm, especially scheduling. In this paper, we study the distributed scheduling issue in UAV ad-hoc networks with FDRs and MPR capability. The distributed scheduling problem in the presence of perfect and imperfect channel state information are formulated as a combinatorial optimization problem and a discrete stochastic optimization problem, respectively. Simulation results show that physical layer FDR and MPR capability have significant impacts on the performance of UAV ad-hoc networks. We also investigate the convergence property of proposed scheme and the effect of channel estimiation errors.
具有全双工无线电和多分组接收的无人机网络的分布式调度
无人机(UAV)自组织网络的应用对复杂环境下的服务质量(QoS)提出了严格的要求,给分布式调度方案的设计带来了挑战。大多数现有的无人机自组织网络调度设计是基于传统的物理层技术,如半双工无线电,没有多包接收能力。然而,干扰消除和信号处理技术的最新进展可以实现全双工无线电(FDR)和多包接收(MPR)能力,这将对链路层算法的设计产生重大影响,特别是调度。本文研究了具有fdr和MPR能力的无人机自组网中的分布式调度问题。将存在完全信道状态信息和不完全信道状态信息的分布式调度问题分别表述为组合优化问题和离散随机优化问题。仿真结果表明,物理层的FDR和MPR能力对无人机自组网的性能有显著影响。研究了该方案的收敛性和信道估计误差的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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