Die-Level Thermal Modeling of a Silicon Germanium (Sige) Bicmos Radio Frequency Integrated Circuit (Rfic) for Wireless Communications

2021 ◽  
Author(s):  
Todd Salamon
2003 ◽  
Vol 13 (01) ◽  
pp. 221-237
Author(s):  
KARL E. FRITZ ◽  
BARBARA A. RANDALL ◽  
GREGG J. FOKKEN ◽  
MICHAEL J. DEGERSTROM ◽  
MICHAEL J. LORSUNG ◽  
...  

Under the auspices of Defense Advanced Research Project Agency's Microsystems Technology Office (DARPA/MTO) Low Power Electronics Program, the Mayo Foundation Special Purpose Processor Development Group is exploring ways to reduce circuit power consumption, while maintaining or increasing functionality, for existing military systems. Applications presently being studied include all-digital radar receivers, electronic warfare receivers, and other types of digital signal processors. One of the integrated circuit technologies currently under investigation to support such military systems is the IBM Corporation silicon germanium (SiGe) BiCMOS process. In this paper, design methodology, simulations and test results from demonstration circuits developed for these applications and implemented in the IBM SiGe BiCMOS 5HP (50 GHz fT HBTs with 0.5 μm CMOS) and 7HP (120 GHz fT HBTs with 0.18 μm CMOS) technologies will be presented.


Frequenz ◽  
2012 ◽  
Vol 66 (5-6) ◽  
Author(s):  
Ralph Mende

AbstractA highly integrated 24 GHz radar sensor is presented, based on a Radio Frequency Integrated Circuit (RFIC) which was specifically developed for a Frequency Modulated Shift Keying (FMSK) based Radar system design. Antenna, waveform, the Radio Frequency (RF) and Digital Signal Processor (DSP) module, the software design, cost and performance aspects will be described. The significant technical and economical advantages of the implemented Silicon-Germanium (SiGe) Bipolar CMOS (BiCMOS) transceiver are demonstrated. Some automotive and other applications based on this technology and new radar system design will be explained.


Author(s):  
Amy Poe ◽  
Steve Brockett ◽  
Tony Rubalcava

Abstract The intent of this work is to demonstrate the importance of charged device model (CDM) ESD testing and characterization by presenting a case study of a situation in which CDM testing proved invaluable in establishing the reliability of a GaAs radio frequency integrated circuit (RFIC). The problem originated when a sample of passing devices was retested to the final production test. Nine of the 200 sampled devices failed the retest, thus placing the reliability of all of the devices in question. The subsequent failure analysis indicated that the devices failed due to a short on one of two capacitors, bringing into question the reliability of the dielectric. Previous ESD characterization of the part had shown that a certain resistor was likely to fail at thresholds well below the level at which any capacitors were damaged. This paper will discuss the failure analysis techniques which were used and the testing performed to verify the failures were actually due to ESD, and not caused by weak capacitors.


Author(s):  
D. Tamilarasi ◽  
P. Ramesh ◽  
Raja Krishnamoorthy ◽  
C. Bharatiraja ◽  
T. Jayasankar

2006 ◽  
Vol 22 (1) ◽  
pp. S236-S243 ◽  
Author(s):  
B Gaucher ◽  
B Floyd ◽  
S Reynolds ◽  
U Pfeiffer ◽  
J Grzyb ◽  
...  

Author(s):  
Hong-xin Zhang ◽  
Jia Liu ◽  
Jun Xu ◽  
Fan Zhang ◽  
Xiao-tong Cui ◽  
...  

Abstract The electromagnetic radiation of electronic equipment carries information and can cause information leakage, which poses a serious threat to the security system; especially the information leakage caused by encryption or other important equipment will have more serious consequences. In the past decade or so, the attack technology and means for the physical layer have developed rapidly. And system designers have no effective method for this situation to eliminate or defend against threats with an absolute level of security. In recent years, device identification has been developed and improved as a physical-level technology to improve the security of integrated circuit (IC)-based multifactor authentication systems. Device identification tasks (including device identification and verification) are accomplished by monitoring and exploiting the characteristics of the IC’s unintentional electromagnetic radiation, without requiring any modification and process to hardware devices, thereby providing versatility and adapting existing hardware devices. Device identification based on deep residual networks and radio frequency is a technology applicable to the physical layer, which can improve the security of integrated circuit (IC)-based multifactor authentication systems. Device identification tasks (identification and verification) are accomplished by passively monitoring and utilizing the inherent properties of IC unintended RF transmissions without requiring any modifications to the analysis equipment. After the device performs a series of operations, the device is classified and identified using a deep residual neural network. The gradient descent method is used to adjust the network parameters, the batch training method is used to speed up the parameter tuning speed, the parameter regularization is used to improve the generalization, and finally, the Softmax classifier is used for classification. In the end, 28 chips of 4 models can be accurately identified into 4 categories, then the individual chips in each category can be identified, and finally 28 chips can be accurately identified, and the verification accuracy reached 100%. Therefore, the identification of radio frequency equipment based on deep residual network is very suitable as a countermeasure for implementing the device cloning technology and is expected to be related to various security issues.


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