Radio-Frequency Interference Estimation for Multiple Random Noise Sources
As more compact designs and more assembled function modules are utilized in modern electronic devices, radio-frequency interference (RFI) source reconstruction is becoming more challenging because different noise sources may contribute simultaneously. This article presents a novel methodology to reconstruct multiple random noise sources on a real-world product, including several double-data-rate (DDR) memory modules and a high-speed connector. The DDR modules located beneath a heatsink cause random noise-like signals, which renders phase measurements challenging. An approach based on the tuned-receiver mode of a vector network analyzer is developed to measure the field phase from the random DDR signals, which can be further modeled with a Huygens' box using the measured field magnitude and phase. Moreover, the connector can be modeled using an equivalent magnetic dipole. Furthermore, the total RFI power from the DDR memory modules and the high-speed connector, which generate uncorrelated RFI noise, is found to equal the summation of the individual power values obtained by an root mean square detector, which can be mathematically corroborated. Using the proposed method, the reconstructed source model can predict RFI values close to measurement results with less than 5 dB deviation.
L. Zhang et al., "Radio-Frequency Interference Estimation for Multiple Random Noise Sources," IEEE Transactions on Electromagnetic Compatibility, Institute of Electrical and Electronics Engineers (IEEE), Nov 2021.
The definitive version is available at https://doi.org/10.1109/TEMC.2021.3117845
Electrical and Computer Engineering
Electromagnetic Compatibility (EMC) Laboratory
Keywords and Phrases
Connectors; Double-Data-Rate (DDR); Heating Systems; Huygens' Box; Integrated Circuit Modeling; Magnetic Dipole; Memory Modules; Multiple Sources; Noise Measurement; Phase Measurement; Radio-Frequency Interference (RFI); Radiofrequency Interference; Source Reconstruction; Uncorrelated Sources
International Standard Serial Number (ISSN)
Article - Journal
© 2021 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
15 Nov 2021