A wearable body temperature sensor would allow for early detection of fever or infection, as well as frequent and accurate hassle-free recording. This thesis explores the design of a body-temperature-sensing device inkjet-printed on a flexible substrate. All structures were first modeled by first-principles, theoretical calculations, and then simulated in HFSS. A variety of planar square inductor geometries were studied before selecting an optimal design. The designs were fabricated using multiple techniques and compared to the simulation results. It was determined that inductance must be carefully measured and documented to ensure good functionality. The same is true for parallel-plate and interdigitated capacitors. While inductance remains relatively constant with temperature, the capacitance of the device with a temperature-sensitive dielectric layer will result in a shift in the resonant frequency as environmental or ambient temperature changes. This resonant frequency can be wirelessly detected, with no battery required for the sensing device, from which the temperature can be deduced. From this work, the optimized version of the design comprises of conductive silver in with a temperature-sensitive graphene oxide layer, intended for inkjet-printing on flexible polyimide substrates. Graphene oxide demonstrates a high dielectric permittivity with good sensing capabilities and high accuracy. This work pushes the state-of-the-art in applying these novel materials and techniques to enable flexible body temperature sensors for future biomedical applications.
This thesis offers the design and improvement of a 2 GHz to 20 GHz low noise amplifier (LNA) utilizing pHEMT technology. The pHEMT technology allows the LNA to generate a boosted signal at a lower noise figure (NF) while consuming less power and achieving smooth overall gain. The design achieves an overall gain (S21) of ≥ 10 dB with an NF ≤ 2 dB while consuming ≤ 30 mA of power while using commercial off-the-shelf (COTS) components.
With the rapid development of wireless communication technology, the demands for higher communication rates are increasing. Higher communication rate corresponds to higher DoF. Interference alignment, which is an emerging interference management technique, is able to substantially increase the DoF of wireless communication systems. This thesis mainly studies the delay-based interference alignment technique. The key problem lies in the design of the transmission scheme and the appropriate allocation of the propagation delay, so as to achieve the desired DoF of different wireless networks. In addition, through delay-based interference alignment, the achievability of extreme points of the DoF region of different wireless networks can be proved.
The new developments in coding theory research have revolutionized the application of coding to practical systems. Low-Density Parity Check (LDPC) codes form a class of Shannon limit approaching codes opted for digital communication systems that require high reliability. This thesis investigates the underlying relationship between the spectral properties of the parity check matrix and LDPC decoding convergence. The bit error rate of an LDPC code is plotted for the parity check matrix that has different Second Smallest Eigenvalue Modulus (SSEM) of its corresponding Laplacian matrix. It is found that for a given (n,k) LDPC code, large SSEM has better error floor performance than low SSEM. The value of SSEM decreases as the sparseness in a parity-check matrix is increased. It was also found from the simulation that long LDPC codes have better error floor performance than short codes. This thesis outlines an approach to analyze LDPC decoding based on the eigenvalue analysis of the corresponding parity check matrix.
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