Sensing Quality Constrained Packet Rate Optimization via Multi-UAV Collaborative Compression and Relay

Kaitao Meng, Xiaofan He, Deshi Li, Mingliu Liu, Chan Xu
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引用次数: 3

Abstract

Due to the on-demand deployable and flexible-observation features, unmanned aerial vehicles (UAVs) is considered as one of the key enabling techniques in next-generation sensing systems. In many sensing applications (e.g., disaster rescue and environment monitoring), a single UAV is not sufficient to fulfill the requirements of transmission delay and sensing quality. Considering this, a multi-UAV collaborative compression and relaying scheme is proposed in this work. The sensory data is packed according to the sensing quality requirement and the sensory data packet rate can be maximized to improve the freshness of the sensory data. To tackle the non-convex problem of finding the optimal compression ratios and UAVs locations with packet rate maximization, the considered problem is converted into a monotonic optimization (MO) by deriving the closed-form expression of the optimal compression ratio for given UAV locations. Then, by exploiting the inherent structure of the optimal UAV locations, a novel region-elimination-based fast location search algorithm is proposed, which can effectively avoid unnecessary search and achieve a substantially faster convergence as compared to the standard MO algorithm. Besides, numerical simulations are conducted to validate the effectiveness of the proposed scheme.
基于多无人机协同压缩中继的感知质量约束分组速率优化
由于无人机具有按需部署和灵活观测的特点,被认为是下一代传感系统的关键使能技术之一。在许多传感应用(如灾害救援和环境监测)中,单架无人机不足以满足传输延迟和传感质量的要求。为此,本文提出了一种多无人机协同压缩中继方案。根据传感质量要求对传感数据进行分组,最大限度地提高传感数据的分组速率,提高传感数据的新鲜度。通过推导给定无人机位置的最优压缩比的封闭表达式,将所考虑的问题转化为单调优化(MO)问题,以解决在数据包速率最大化的情况下寻找最优压缩比和无人机位置的非凸问题。然后,利用无人机最优位置的固有结构,提出了一种新的基于区域消除的快速位置搜索算法,该算法可以有效地避免不必要的搜索,收敛速度比标准MO算法快得多。通过数值仿真验证了该方案的有效性。
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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