Recently, the growing advances in communication systems has led to urgent demand for low power, low cost, and highly integrated circuit topologies for transceiver designs, as key components of nearly every wireless application. Regarding to the usually weak input signal of such systems, the primary purpose of the wireless transceivers is consequently amplifying the signal without adding additional noise as much as possible. As a result, the performance of the low noise amplifier (LNA), measured in terms of features like gain, noise figure, dynamic range, return loss and stability, can highly determine the system’s achievement. Along with the evolution in wireless technologies, people get closer to the global seamless communication, which means people can unlimitedly communicates with each other under any circumstances. This achievement, as a result, paves the way for realizing wireless body area network (WBAN), the required applications for wireless sensor network, healthcare technology, and continuous health monitoring. This thesis suggests a number of LNA designs that can meet a wide range of requirements viz gain, noise figure, impedance matching, and power dissipation at 2.4Ghz frequency based on 0.13μm and 65nm CMOS technologies. This dissertation focused on the low power, high gain, CMOS reused current (CICR) LNA with noise optimization for on-body wireless body area networks (WBAN). A new design methodology is introduced for optimization of the LNA to attain gain and noise match concurrently. The designed LNA achieves a 28.5 dB gain, 2.4 dB noise figure, -18 dB impedance matching, while dissipating 1mW from a 1.2V power supply at 2.4 GHz frequency which is intended for WBAN applications. The tests and simulations of LNA are utilized in Cadence IC6.15 with IBM 130nm CMRF-8-SF library. The provided CICR LNA results inclusively prove the advantages of our design over other recorded structures. In the second step, a new linearization method is proposed based on Cascade LNA structure (CC-LNA). The proposed negative feedback intermodulation sink (NF-IMS) method benefits from the feedback to improve the linearity of CC-LNA. It proves that the additional negative feedback enhances the linearity of LNA despite the previous research. Furthermore, the heavily mathematical calculations of NF-IMS technique are carried on with the proposed modified Volterra series method. The NF-IMS method demonstrates more than 9.5dBm improvement in IIP3. Comparing to the previous techniques like: MDS and IMS, the improvement in the linearity aspect of the CC-LNA with is significant while it achieves a sufficient gain and noise performance of 16.7dB and 1.26db, respectively. Besides, the NF-IMS method presents a noise cancellation behavior as well. To increase the practical reliability of simulation, the real element model from TSMC 65nm CRN65GP library is applied. The CC-LNA that employed NF-IMS method is an excellent match with the market demands in WBAN’s gateway applications.
Machine Learning Assisted Inverse Design for Ultrafine, Dynamic and Arbitrary Gain Spectrum Shaping of Raman Amplification
