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

Electronic engineering

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