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arXiv 1205.0835cs.ITmath.IT
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模拟传感器网络中基于最优分布式波束形成的参数跟踪

Parameter Tracking via Optimal Distributed Beamforming in an Analog Sensor Network

Feng Jiang, Jie Chen, A. Lee Swindlehurst

摘要:

我们考虑传感器网络中的最优分布式波束形成问题,其中传感器在噪声中观察动态参数,并将其观测结果相干放大并转发到融合中心(FC)。FC使用一个卡尔曼滤波器跟踪的参数,使用从传感器的观察,我们展示了如何找到最佳的增益和相位的传感器传输下的全球和个人的功率约束,以最小化的参数估计的均方误差(MSE)。对于全局功率约束的情况,可以获得封闭形式的解。一个数值优化是需要个人的权力约束,但问题可以放宽到一个半定规划问题(SDP),我们展示了如何构建的最佳解决方案的SDP的解决方案。仿真结果表明,与等功率传输相比,采用优化功率控制可以显著降低均方误差。

英文摘要:

We consider the problem of optimal distributed beamforming in a sensor network where the sensors observe a dynamic parameter in noise and coherently amplify and forward their observations to a fusion center (FC). The FC uses a Kalman filter to track the parameter using the observations from the sensors, and we show how to find the optimal gain and phase of the sensor transmissions under both global and individual power constraints in order to minimize the mean squared error (MSE) of the parameter estimate. For the case of a global power constraint, a closed-form solution can be obtained. A numerical optimization is required for individual power constraints, but the problem can be relaxed to a semidefinite programming problem (SDP), and we show how the optimal solution can be constructed from the solution to the SDP. Simulation results show that compared with equal power transmission, the use of optimized power control can significantly reduce the MSE.

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。

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