With the electromagnetic (EM) parameter demands of wireless link prediction such as ray-tracing (RT), using field wireless measurements to calibrate environmental EM parameters becomes a promising solution to obtain accurate EM parameters in a given area. In this letter, we propose a modified generalized approximate message passing (GAMP) algorithm with trust region to estimate permittivity parameters in RT model based on path loss data. The aim of trust region is to constrain the parameters and reduce the inaccuracy while dealing with messages updated in GAMP for nonlinear estimation. Numerical results demonstrate that the proposed algorithm outperforms GAMP without trust region in two aspects: the accuracy of permittivity estimation, as well as the errors in path loss prediction utilizing the calibrated parameters.

中文翻译：

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基于GAMP的路径损耗数据进行光线追踪中的介电常数估计


由于光线追踪 （RT） 等无线链路预测的电磁 （EM） 参数需求，使用现场无线测量校准环境 EM 参数成为在给定区域获得准确 EM 参数的一种有前途的解决方案。在本文中，我们提出了一种改进的具有信任区的广义近似消息传递 （GAMP） 算法，以基于路径损耗数据估计 RT 模型中的介电常数参数。信任区域的目的是在处理 GAMP 中更新的消息以进行非线性估计时约束参数并减少不准确。数值结果表明，所提算法在两个方面优于无信任域的 GAMP：介电常数估计的准确性，以及利用校准参数进行路径损耗预测的误差。