A framework is proposed for developing and evaluating algorithms for extracting multipath propagation components (MPCs) from measurements collected by sounders at millimeter-wave (mmW) frequencies. To focus on algorithmic performance, an idealized model is proposed for the spatial frequency response of the propagation environment measured by a sounder. The input to the sounder model is a pre-determined set of MPC parameters that serve as the "ground truth." A three-dimensional angle-delay (beamspace) representation of the measured spatial frequency response serves as a natural domain for implementing and analyzing MPC extraction algorithms. Metrics for quantifying the error in estimated MPC parameters are introduced. Initial results are presented for a greedy matching pursuit algorithm that performs a least-squares (LS) reconstruction of the MPC path gains within the iterations. The results indicate that the simple greedy-LS algorithm has the ability to extract MPCs over a large dynamic range, and suggest several avenues for further performance improvement through extensions of the greedy-LS algorithm as well as by incorporating features of other algorithms, such as SAGE and RIMAX.
翻译:为从毫米波频率声音测量器收集的测量中提取多途径传播组件(MPCs),提议了一个框架,用于开发和评估从多途径传播组件(MPCs)的算法。为侧重于算法性能,提议了一个理想化模型,用于由声音器测量的传播环境的空间频率反应。对声音模型的投入是一套预先确定的多途径传播组件(MPC)参数,作为“地面真相”的一组参数。测量的空间频率反应的三维角度缓冲(波段)代表作为实施和分析MPC提取算法的自然领域。引入了用于量化估计的MPC参数错误的尺度。初步结果为一种贪婪匹配算法提供了一种匹配算法,该算法在迭代中对MPC路径的增益进行最小方(LS)。结果显示,简单的贪婪-LS算法有能力在大动态范围内提取MPCs,并提出通过扩大贪婪-LS算法以及纳入其他算法特征(如SAGE和RIMAX)来进一步改进绩效的几种途径。