Walter De Raedt

A wideband beamformer for a phased-array 60GHz receiver in 40nm digital CMOS

For high-data-rate wireless communication in the 7GHz band around 60GHz, the IEEE 802.15.3c standard [1] provides channels with a 0.88GHz bandwidth for the AV-OFDM mode. For the single-carrier modes, the ECMA 387 standard [2] foresees the possibility of bonding together adjacent channels, yielding higher data-rates. Radios for these 60GHz standards often use phased antenna arrays to relax the link budget. A phased-array receiver needs a variable phase shift on each antenna path and a combiner that sums the signals from the individual paths after phase shifting. The beamforming circuitry presented here handles 4 paths. It can operate both with one 0.88GHz channel and with bonding of two such channels. Phase shifts are realized with a resolution better than 20°. Bandwidth is high thanks to the use of current amplifiers with very low input impedance.

S‐parameter measurement based quasistatic large‐signal cold HEMT model for resistive mixer design

The nonlinear cold HEMT model generation procedure is described. It starts with the determination of the corresponding small-signal model by adapting the cold FET extraction approach for HEMTs. Then, the small-signal model is transformed to obtain a straightforward implementable, consistent small-signal cold HEMT model, suitable for resistive mixer design.

Ar Implantation, a Passivation Technique for High-Resistivity Silicon within the MCM-D Technology

High-resistivity silicon (HRSi) has excellent properties as substrate material to integrate microwave passive components and system in a package (SiP) modules. However, the existence of a layer of free surface charges under the silicon-silicon dioxide interface generated by impurities in the SiO2 and in the interface itself undermines the RF properties of the bulk HRSi. This paper demonstrates that the surface charges increase the RF loss of CPW lines processed on HRSi and make their loss DC dependent. It also presents how Ar implantation can successfully restore the excellent RF properties of the bulk HRSi in terms of loss and DC dependency. An Ar implant dose 10 times lower than previously reported is demonstrated to be sufficient, lowering the cost of the passivation step. The substrate loss of passivated HRSi is shown to be comparable to that of AF45 glass regarding inductors and a better Q for CPW lines has been measured in the case of HRSi. This approach withstands the most critical processing step of imecs MCM-D technology and therefore it is a suitable technique to passivate the surface of HRSi within this technology

Fine pitch 3D-TSV based high frequency components for RF MEMS applications

The development of interconnections suitable for radio-frequency (RF) and millimeter-wave (mm-wave) applications is of foremost importance for the feasibility of high-quality substrate-integrated devices. For this purpose, we introduce and validate the technology to implement fine-pitch high-aspect ratio tungsten-filled through-silicon vias (W-TSVs) adapted for high-frequency applications. The presented technology is optimized for integration with RF MEMS, for which we propose a compatible fabrication process flow. We designed and characterized RF test structures to assess the quality of the W-TSVs and their suitability for radio-frequency integrated circuits (RFIC) applications, showing low insertion loss for TSV in coplanar waveguides (CPW) and high-performance wideband mm-wave antennas.

Comparison of Machine Learning Techniques for Psychophysiological Stress Detection

Previous research has indicated that physiological signals can be used to detect mental stress. There is however no consensus on the optimal algorithm for this detection. The aim of this study is to compare different machine learning techniques for the measurement of stress based on physiological responses in a controlled environment. Electrocardiogram (ECG), galvanic skin response (GSR), temperature and respiration were measured during a laboratory stress test. Six machine learning techniques were investigated using a general and personal approach. The results show that personalized dynamic Bayesian networks and generalized support vector machines render the best average classification results with 84.6 % and 82.7 % respectively.

Compact and high-accuracy RF MEMS capacitive series devices

MEMS technology is presented as a promising technology to realize high Q variable capacitors and RF switches with high performance and with high levels of integration. These devices are key elements for systems like phase shifters, tunable filters and matching networks. However, the reliability and the yield of the RF MEMS devices remain the key limiting factors holding the MEMS technology from spreading in the industrial applications. From a RF designers point of view, reliability and yield are closely related to the accuracy of the definition of the up- and down-state capacitances of the devices. In this paper, we propose a novel compact series capacitive structure with improved predictability and RF performance. The new design mimics a clamped-clamped bridge to lower its sensitivity to the process-induced stress gradient in the up-state. The shape of the device and its consequent parameters, e.g. up- and down-capacitances, are thus more accurately defined even in presence of non-ideal clamping conditions. Unlike the series switchable capacitors with transverse restraining bridge, the novel device does not suffer from high frequency parasitic resonances. Finally, the novel device implements the floating top metal. This allows accurately defining the down-state capacitance of the design at will. Boosted series capacitive switches with inline-restrained cantilever beams have been realized and measured. The isolation is better than 20dB until 1GHz without optimization. The insertion loss in the down-state is better than 0.2dB in the range 1-20GHz. It further slowly and continuously decays to reach 0.4dB at 40GHz without any resonances.

Unsupervised Learning for Mental Stress Detection - Exploration of Self-organizing Maps

One of the major challenges in the field of ambulant stress detection lies in the model validation. Commonly, different types of questionnaires are used to record perceived stress levels. These only capture stress levels at discrete moments in time and are prone to subjective inaccuracies. Although, many studies have already reported such issues, a solution for these difficulties is still lacking. This paper explores the potential of unsupervised learning with Self-Organizing Maps (SOM) for stress detection. In unsupervised learning settings, the labels from perceived stress levels are not needed anymore. First, a controlled stress experiment was conducted during which relax and stress phases were alternated. The skin conductance (SC) and electrocardiogram (ECG) of test subjects were recorded. Then, the structure of the SOM was built based on a training set of SC and ECG features. A Gaussian Mixture Model was used to cluster regions of the SOM with similar characteristics. Finally, by comparison of features values within each cluster, two clusters could be associated to either relax phases or stress phases. A classification performance of 79.0% (±5.16) was reached with a sensitivity of 75.6% (±11.2). In the future, the goal is to transfer these first initial results from a controlled laboratory setting to an ambulant environment.

Comparing task‐induced psychophysiological responses between persons with stress‐related complaints and healthy controls: A methodological pilot study

Chronic stress is an important factor for a variety of health problems, highlighting the importance of early detection of stress‐related problems. This methodological pilot study investigated whether the physiological response to and recovery from a stress task can differentiate healthy participants and persons with stress‐related complaints.

3D TSV based high frequency components for RF IC and RF MEMS applications

We demonstrate and review the unique fine-pitch high-aspect ratio tungsten-filled through-silicon vias (W-TSVs) technology developed by Fraunhofer EMFT in high-resitivity silicon substrates. The proposed process flow is fully compatible with both CMOS and MEMS technology, allowing 3D heterogeneous integration of highperformance, low power, compact tunable RF front-ends. We have assessed the figures of merit of the technology for RF functionality by fabricating and characterizing different configurations for CPWs with TSV transitions, mm-wave antennas and LC resonators as well as record-high performance wideband out-of-plane micro-inductors.

Heterogeneous Integration of Passive Components for the Realization of RF-System-in-Packages

Applications using rf radios operating at frequencies above 1 GHz are proliferating. The highest operating frequencies continue to increase and applications above 10 GHz and up to 77 GHz are already emerging. Systems become more complex and devices need to operate at several different frequency bands using different wireless standards. The rf-front end sections of these devices are characterized by a high diversity of components, in particular high precision passive components. In order to be produced cost-effectively, these elements need to be integrated along with the semiconductor devices. This paper describes the requirements for successful integration of rf-passive devices and proposes multilayer thin film technology as an effective rf-integration technology.