Wireless power transfer (WPT) systems are important in many areas, such as medical, communication, transportation, and consumer electronics. The underlying WPT system is comprised of a transmitter (TX) and receiver (RX). For biomedical applications, such systems can be implemented on rigid or flexible substrates and can be implanted or wearable. The efficiency of a WPT system is based on power transfer efficiency (PTE). Many WPT system optimization techniques have been explored to achieve the highest PTE possible. These are based on either a figure-of-merit (FOM) approach, quality factor (Q-factor) maximization, or by sweeping values for coil geometries. Four WPT systems for biomedical applications are implemented with inductive coupling. The thesis later presents an optimization technique for finding the maximum PTE of a range of frequencies and coil shapes through frequency, geometry and shape sweeping. Five optimized TX coil designs for different operating frequencies are fabricated for three shapes: square, hexagonal, and octagonal planar-spirals. The corresponding RX is implemented on polyimide tape with ink-jet-print (IJP) silver. At 80 MHz, the maximum measured PTE achieved is 2.781% at a 10 mm distance in the air for square planar-spiral coils.

This thesis presents the realization of an intelligent cognitive radio network that uses long short term memory (LSTM) neural network for sensing and predicting the spectrum activity at each instant of time. The simulation is done using Python and GNU Radio. The implementation is done using GNU Radio and Universal Software Radio Peripherals (USRP). Simulation results show that the confidence factor of opportunistic users not causing interference to licensed users of the spectrum is 98.75%. The implementation results demonstrate high reliability of the LSTM based cognitive radio network.

In this dissertation a computationally efficient cognitive multiple-input multiple-output (MIMO) orthogonal frequency division duplexing (OFDM) detector is designed to decode perfect space-time coded signals which are able maximize the diversity and multiplexing properties of a rich fading MIMO channel. The adaptive nature of the cognitive detector allows a MIMO OFDM communication system to better meet to needs of future wireless communication networks which require both high reliability and low run-time complexity depending on the propagation environment. The cognitive detector in conjunction with perfect space-time coding is able to achieve up to a 2 dB bit-error rate (BER) improvement at low signal-to-noise ratio (SNR) while also achieving comparable runtime complexity in high SNR scenarios.