[论文解读] Node Placement and Distributed Magnetic Beamforming Optimization for Wireless Power Transfer

Mohammad R. Vedady Moghadam, Rui Zhang|arXiv (Cornell University)|Aug 1, 2016

Wireless Power Transfer Systems参考文献 28被引用 3

一句话总结

本文提出了一种针对近场无线能量传输的优化节点部署与分布式磁波束成形方案，采用磁共振耦合技术。通过联合优化发射机位置与自适应波束成形电流，系统在1D或2D区域上最大化最小接收功率，实现了均匀的功率覆盖，并显著优于非自适应与启发式基准方案。

ABSTRACT

In multiple-input single-output (MISO) wireless power transfer (WPT) via magnetic resonant coupling (MRC), multiple transmitters are deployed to enhance the efficiency of power transfer to the electric load at a single receiver by jointly optimizing their source currents/voltages to constructively combine the induced magnetic fields at the receiver, known as magnetic beamforming. In practice, since the transmitters (power chargers) are usually at fixed locations and the receiver (e.g. mobile phone) is desired to be freely located in a target region for wireless charging, its received power can fluctuate significantly over locations even with adaptive magnetic beamforming applied. To achieve uniform coverage, the transmitters need to be optimally placed in the region, which motivates this paper. First, we derive the optimal magnetic beamforming solution in closed-form for a distributed MISO WPT system with given locations of the transmitters and receiver to maximize the deliverable power to the receiver load subject to a given sum-power constraint at all transmitters. With the optimal magnetic beamforming solution, we then jointly optimize the locations of all transmitters to maximize the minimum power deliverable to the receiver when it is being moved over a given one-dimensional (1D) region, i.e., a line of finite length. Although the formulated node placement problem is non-convex, we propose an iterative algorithm for solving it efficiently. Extensive simulation results are provided which show the significant performance gains by the proposed design with optimized transmitter locations and magnetic beamforming as compared to other benchmark schemes with non-adaptive or heuristic currents allocation and transmitters placement. Last, we extend the node placement problem to the more general case of two-dimensional (2D) region, and draw the key insights.

研究动机与目标

• 解决由于接收机移动导致的磁共振WPT系统中接收功率波动的问题，即使采用自适应波束成形亦难以避免。
• 通过联合优化发射机位置与波束成形权重，确保目标区域内功率传输的均匀性。
• 在发射机总功率约束下，最大化1D或2D区域上的最小接收功率。
• 为分布式MISO-WPT系统中的非凸优化问题设计高效算法。
• 将设计扩展至2D区域，采用实际且可扩展的节点部署策略。

提出的方法

• 推导出在固定发射机与接收机位置下，满足总功率约束时最大化功率传输的闭式最优磁波束成形解。
• 提出一种迭代算法，联合优化发射机位置与波束成形权重，以最大化1D区域上的最小接收功率。
• 应用旋转对称性与基于质数的环形结构约束，确保配置具有唯一性与对称性，同时保持波束成形增益。
• 通过使用每环质数个发射机的结构化发射机环排列，将1D解扩展至2D区域。
• 利用KKT条件证明波束成形解的最优性，并借助对称性降低设计复杂度。
• 采用数学分析，建立多环配置中旋转对称性与结构差异性的必要与充分条件。

实验结果

研究问题

• RQ1 在分布式MISO-WPT系统中，如何优化发射机位置以确保1D区域内的均匀功率传输？
• RQ2 在发射机与接收机位置固定时，何种波束成形策略可使在总功率约束下接收功率最大化？
• RQ3 在多环发射机配置中，如何从数学上表征旋转对称性与结构差异性？
• RQ4 与非自适应或启发式方案相比，通过联合优化节点部署与波束成形可实现多大的性能增益？
• RQ5 如何将1D节点部署优化扩展至具有实际可扩展性的二维区域？

主要发现

• 所提出的闭式波束成形解在总功率约束下，对固定发射机与接收机位置实现了最优功率传输。
• 针对1D节点部署的迭代算法显著提升了最小接收功率，优于采用固定或启发式发射机位置的基准方案。
• 每环使用质数个发射机可确保旋转对称性与结构差异性，从而支持可扩展且对称的系统设计。
• 仿真结果表明，当同时联合优化节点部署与波束成形时，均匀功率覆盖性能获得显著提升。
• 2D区域的扩展保持了高性能，且采用基于对称性的高效发射机环形配置。
• 理论分析证实，该波束成形解在KKT条件下为全局最优，验证了该方法在非凸优化中的有效性。