Probe Selection and Power Weighting in Multiprobe OTA Testing: A Neural Network-Based Approach
Joint Authors
Li, Yong
Sun, Hao
Chen, Xingyu
Xin, Lijian
Zhang, Xiang
Source
International Journal of Antennas and Propagation
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-09-10
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Over-the-air (OTA) radiated testing is an efficient solution to evaluate the performance of multiple-input multiple-output (MIMO) capable devices, which can emulate realistic multipath channel conditions in a controlled manner within lab environment.
In a multiprobe anechoic chamber- (MPAC-) based OTA setup, determining the most appropriate probe locations and their power weights is critical to improve the accuracy of channel emulation at reasonable system costs.
In this paper, a novel approach based on neural networks (NNs) is proposed to derive suitable angular locations as well as power weights of OTA probe antennas; in particular, by using the regularization technique, active probe locations and their weights can be optimized simultaneously with only one training process of the proposed NN.
Simulations demonstrate that compared with the convex optimization-based approach to perform probe selection in the literature, e.g., the well-known multishot algorithm, the proposed NN-based approach can yield similar channel emulation accuracy with significantly reduced computational complexity.
American Psychological Association (APA)
Li, Yong& Sun, Hao& Chen, Xingyu& Xin, Lijian& Zhang, Xiang. 2019. Probe Selection and Power Weighting in Multiprobe OTA Testing: A Neural Network-Based Approach. International Journal of Antennas and Propagation،Vol. 2019, no. 2019, pp.1-8.
https://search.emarefa.net/detail/BIM-1157219
Modern Language Association (MLA)
Li, Yong…[et al.]. Probe Selection and Power Weighting in Multiprobe OTA Testing: A Neural Network-Based Approach. International Journal of Antennas and Propagation No. 2019 (2019), pp.1-8.
https://search.emarefa.net/detail/BIM-1157219
American Medical Association (AMA)
Li, Yong& Sun, Hao& Chen, Xingyu& Xin, Lijian& Zhang, Xiang. Probe Selection and Power Weighting in Multiprobe OTA Testing: A Neural Network-Based Approach. International Journal of Antennas and Propagation. 2019. Vol. 2019, no. 2019, pp.1-8.
https://search.emarefa.net/detail/BIM-1157219
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1157219