移动波束成形与空间控制中继通信
Mobile Beamforming & Spatially Controlled Relay Communications
AI总结：
本文研究了单源单目标机器人中继网络中的随机运动规划问题，提出了一种两阶段随机规划方法，通过优化中继位置以最大化总波束成形功率的期望倒数，采用随机因果信道状态信息进行决策。
摘要：
我们考虑了在合作波束成形框架下，单源单目标机器人中继网络中的随机运动规划问题。假设通信介质构成一个时空随机场，我们提出了一种两阶段随机规划方法，用于确定中继的位置，以最大化其总波束成形功率的期望倒数。随机决策基于随机因果信道状态信息。认识到原始问题的不可行性，我们提出一个下界松弛，导致一个非平凡的中继位置优化问题，等价于一个小的简单可解子问题集。我们的方法导致具有预测特性的空间控制器；在每个时间槽中，新的中继位置应使得下一个时间槽的期望功率倒数最大化。很有趣的是，松弛问题的最优控制策略是纯粹选择性的；在某种意义上，只有最佳中继应移动。
英文摘要：
We consider stochastic motion planning in single-source single-destination robotic relay networks, under a cooperative beamforming framework. Assuming that the communication medium constitutes a spatiotemporal stochastic field, we propose a 2-stage stochastic programming formulation of the problem of specifying the positions of the relays, such that the expected reciprocal of their total beamforming power is maximized. Stochastic decision making is made on the basis of random causal CSI. Recognizing the intractability of the original problem, we propose a lower bound relaxation, resulting to a nontrivial optimization problem with respect to the relay locations, which is equivalent to a small set of simple, tractable subproblems. Our formulation results in spatial controllers with a predictive character; at each time slot, the new relay positions should be such that the expected power reciprocal at the next time slot is maximized. Quite interestingly, the optimal control policy to the relaxed problem is purely selective; under a certain sense, only the best relay should move.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
