A Communication Model to Decouple the Path Planning and Connectivity Optimization and Support Cooperative Sensing

A Communication Model to Decouple the Path Planning and Connectivity Optimization and Support Cooperative Sensing
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解耦路径规划和连接优化并支持协作感知的通信模型

DOI:
10.1109/tvt.2014.2305474
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发表时间:
2014
影响因子:
6.8
通讯作者:
Luo C
Luo C
中科院分区:
计算机科学2区
文献类型:
--
作者:
Luo C

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当多个移动的机器人(例如,机器人设备和无人机(UAV))被部署以协同工作,通常难以联合优化涉及以下两个方面的算法:找到最优路径和保持可靠的网络连接。这是因为这两个目标都需要操纵传感器的物理位置。我们引入了一个新的中继辅助通信模型来解耦这两个方面,使每一个都可以独立优化。然而,使用额外的中继节点是以增加传输次数和降低频谱效率为代价的。基于模型互信息和平均数据速率的理论结果表明,如果传感器节点仔细分组,这些缺陷可以得到补偿。基于这些结果,我们进一步提出了一种配对策略,以最大限度地提高频谱效率增益。仿真实验证实了该策略在提高效率方面的性能。我们提供了一个简单的例子来演示该模型在协作感知场景中的应用,其中部署了多个无人机来探索未知区域。
When multiple mobile robots (e.g., robotic equipment and unmanned aerial vehicles (UAVs)) are deployed to work cooperatively, it is usually difficult to jointly optimize the algorithms involving the following two aspects: finding optimal paths and maintaining reliable network connectivity. This is due to the fact that both these objectives require the manipulation of sensors' physical locations. We introduce a new relay-assisted communication model to decouple these two aspects so that each one can be optimized independently. However, using additional relay nodes is at the expense of an increased number of transmissions and reduced spectrum efficiency. Theoretical results based on mutual information and average data rate of the model reveal that such drawbacks can be compensated if the sensor nodes are carefully arranged into groups. Based on these results, we further propose a pairing strategy to maximize the spectrum efficiency gain. Simulation experiments have confirmed the performance of this strategy in terms of improved efficiency. We provide a simple example to demonstrate the application of this model in cooperative sensing scenarios where multiple UAVs are deployed to explore an unknown area.
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