Recent Research Projects
RF Desense Model
Radio-frequency (RF) antenna tends to be susceptible for desense issue due to the compact customer electronic devices design and the high speed signals. Nowadays engineers have been aware of the RF interference coming from ICs, modules or high speed buses, thus the direct RF interference is less and less likely to create troubles. However, due to the nonlinearity of some components or modules, the RF antenna can be degraded even for relatively low-frequency modules.
Use LTE band5 as an example, the gap between TX & RX is 20MHz. This gap can be easily filled by several orders of harmonics created by a low-frequency clock driven component. As long as there exists an intermodulation and coupling path, the high-power TX signals can upconvert the low-frequency components to RX range by intermodulation and cause desense. Wide-band TX will worsen the issue because the modulated signal will also be wideband in RX range.
The quantification of the RF coupling to the victim antenna can be done using dipole-moment based reciprocity. Near-field scan will be used to obtain the equivalent representation to the noise sources. The complete problem is decomposed to be two parts: forward and reverse problem. Thus the RF coupling caused by each individual of the noise sources can be quantified and help to evaluate the priority of industrial solutions for solving the desense issue.
RF Desense Buzz Noise
In electronic devices with wireless communication functionality such as Wi-Fi communications in cellphones, tablets, and cameras, the audio system could be possibly affected by the modulated wireless signal via the near field coupling. The noise in the audio signal, which is called buzz noise, can be explained by the demodulation mechanism (square function) from the non-linearity behavior in the microphone module or the microphone codec IC. The goal of this study is to propose a SPIC-based model based on reciprocity theorem to allow for rapid simulation in the early design stage on: (1) estimation of the WiFi-induced buzz noise and coupling contribution from the antenna to different regions of the victim; (2) mitigation on the buzz noise; (3) estimation of the WiFi-induced buzz noise with different antenna (aggressor) structures.
RF Desense IC Radiation Model
Digital signals input to or output from digital ICs contains wide-spread frequency spectrums. The radiated signals in the radio frequency range can be picked up by radio receivers nearby, which results in RF desensitization on the receivers. Therefore, digital ICs are usually a primary source for many RF interference problems in modern electronic devices.
The objectives of this study are: (1) to understand the radiation mechanism in IC/package area; and (2) to develop methods to model the radiation from IC. At current stage, the investigation is based on a digital IC connecting to package structure by bonding wires. The radiation behavior is analyzed by investigating the signal and return current paths in full-wave simulations, and the conclusions are verified in measurements.
The fabricated IC and bonding configurations
Surface current distributions from full-wave simulation
RF Desense PIM Characterization, Nonlinearity
PIM is short for Passive Intermodulation. It is a non-linear distortion phenomenon caused by passive components. There are a variety of mechanisms for the root-cause of PIM but the consequences of PIM are typically the similar. For a multiple-tone situation or wideband signals, PIM can cause the intermodulation and generate new frequency components. Thus, the spectrum will be more spread, and the unwanted spectrum can be an issue.
The characterization of PIM caused by metallic contacts can be done based on a duplexer system using two-tone excitation. The two-tone signals can go through the contact junction path and any generated side-band spectrum falling into RX range will be captured by the spectrum analyzer.
The nonlinearity can be modeled using equivalent circuits based on the I-V characteristics. Also, for a rough estimation, DCR values can help judge to some extend due to the correlation of PIM for certain range in a statistical sense.