This thesis examines the use of two coupled loops as an alternative method of connection for high frequency signals between passive elements on microwave laminates and integrated circuits; replacing traditional interconnect methods such as wire bonds and solder bumps which require costly back end of line processing. The loops harness both electric and magnetic fields in order to create the interconnection, and can be placed around the perimeter of the IC; here they do not interfere with placement of the existing electronics on the chip, or occupy space which may be required for large components such as spiral inductors. A parametric model for these coupled loops was developed in this thesis. This model allows for rapid initial dimension choice when provided a variety of different parameters such as the IC process geometry, and loop stack geometry. Once initial dimensions are obtained from the model, full-wave simulation can be used to finalize the design and examine effects of process design rules such as metal density requirements. Following model development a prototype system, consisting of a two metallic loops (one located on a low-loss microwave laminate, the other on a 0.13 u m CMOS IC), was fabricated. These loops were then stacked in order to couple the signal from a planar antenna array (printed on the laminate) onto the IC. This antenna-to-chip system was simulated and measured to have center frequencies of 25 GHz and 23 GHz respectively, with a peak gain greater than 5 dBi at the beams broadside (8 dBi in simulation). These results agree quite well, with discrepancies arising primarily from the presence of adhesive between the loops. This adhesive wicked underneath the IC during assembly, which was not accounted for during simulation, but can easily be done so. The radiation pattern from the antenna was measured to have a HPBW of 16 degrees in the elevation plane and 100 degrees in the azimuth plane. These correspond nicely with simulated results and produce a suitable system for automotive radar application; where harsh environments present difficulties to current interconnects such as wire bonds. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2013-09-09 21:55:06.971

In this thesis, a new approach combining neural networks and genetic algorithms is presented for microwave design. In this method, an accurate neural network model is developed from the experimental data. This neural network model is used to perform sensitivity analysis and derive response surfaces. An innovative technique is then applied in which genetic algorithms are coupled with the neural network model to assist in synthesis and optimization. The proposed method is used for modeling and analysis of circuit parameters for flip chip interconnects up to 35 GHz, as well as for design of multilayer inductors and capacitors at 1.9 GHz and 2.4 GHz. The method was also used to synthesize mm wave low pass filters in the range of 40-60 GHz. The devices obtained from layout parameters predicted by the neuro-genetic design method yielded electrical response close to the desired value (95% accuracy). The proposed method also implements a weighted priority scheme to account for tradeoffs in microwave design. This scheme was implemented to synthesize bandpass filters for 802.11a and HIPERLAN wireless LAN applications in the range of 5-6 GHz. This research also develops a novel neuro-genetic design centering methodology for yield enhancement and design for manufacturability of microwave devices and circuits. A neural network model is used to calculate yield using Monte Carlo methods. A genetic algorithm is then used for yield optimization. The proposed method has been used for yield enhancement of SiGe heterojunction bipolar transistor and mm wave voltage-controlled oscillator. It results in significant yield enhancement of the SiGe HBTs (from 25 % to 75 %) and VCOs (from 8 % to 85 %). The proposed method is can be extended for device, circuit, package, and system level integrated co-design since it can handle a large number of design variables without any assumptions about the component behavior. The proposed algorithm could be used by microwave community for design and optimization of microwave circuits and systems with greater accuracy while consuming less computational time.