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首页> 外文期刊>IEEE transactions on wireless communications >Backscatter Data Collection With Unmanned Ground Vehicle: Mobility Management and Power Allocation
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Backscatter Data Collection With Unmanned Ground Vehicle: Mobility Management and Power Allocation

机译：无人地面车辆的反向散射数据收集：机动性管理和功率分配

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Collecting data from the massive Internet of Things (IoT) devices is a challenging task since communication circuits are power-demanding while energy supply at IoT devices is limited. To overcome this challenge, backscatter communication emerges as a promising solution as it eliminates radio frequency components in the loT devices. Unfortunately, the transmission range of backscatter communication is short. To facilitate backscatter communication, this paper proposes to integrate unmanned ground vehicle (UGV) with backscatter data collection. With such a scheme, the UGV could improve the communication quality by approaching various IoT devices. However, moving also costs energy consumption and a fundamental question is: what is the right balance between spending energy on moving versus on communication? To answer this question, this paper studies energy minimization under a joint graph mobility and backscatter communication model. With the joint model, the mobility management and power allocation problem, unfortunately, involves nonlinear coupling between discrete variables brought by mobility and continuous variables brought by communication. Despite the optimization challenges, an algorithm that theoretically achieves the minimum energy consumption is derived, and it leads to automatic trade-off between spending energy on moving versus on communication in the UGV backscatter system. The simulation results show that if the noise power is small (e.g., <=-100 dBm), the UGV should collect the data with small movements. However, if the noise power is increased to a larger value (e.g., -60 dB m), the UGV should spend more motion energy to get closer to the IoT users.
机译：从大型物联网（IoT）设备收集数据是一项具有挑战性的任务，因为通信电路耗电，而IoT设备的能源供应有限。为了克服这一挑战，后向散射通信消除了loT设备中的射频成分，成为一种很有前途的解决方案。不幸的是，反向散射通信的传输范围很短。为了促进反向散射通信，本文提出将无人地面飞行器（UGV）与反向散射数据收集集成在一起。通过这种方案，UGV可以通过接近各种物联网设备来提高通信质量。但是，移动也要消耗能源，基本问题是：在移动和通信上花费能量之间的正确平衡是什么？为了回答这个问题，本文研究了联合图移动性和反向散射通信模型下的能量最小化。不幸的是，使用联合模型，移动性管理和功率分配问题涉及移动性带来的离散变量与通信带来的连续变量之间的非线性耦合。尽管存在优化方面的挑战，但还是可以得出一种理论上可以实现最低能耗的算法，并且该算法可以在UGV背向散射系统中，在移动与通信上的能量消耗与通信上的能量消耗之间实现自动权衡。仿真结果表明，如果噪声功率较小（例如<=-100 dBm），则UGV应当以较小的运动来收集数据。但是，如果将噪声功率增加到更大的值（例如-60 dB m），则UGV应该花费更多的运动能量以更接近IoT用户。

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