Efficient Architectures for Wideband Receivers

Reducing power consumption of radio receivers is becoming more critical with the advancement of biomedical portable and implantable devices due to the stringent power requirements in such applications. Compressive sensing promises to tremendously reduce the power of radio receivers by allowing the reconstruction of sparse signals from measurements acquired at a sub-Nyquist rate. A key component in compressive sensing systems is the random signal which is used to acquire the measurements. Most efforts have been devoted to the design of signals with high randomness but little have been devoted to manipulating the random signal to suite a specific application, meet certain specifications, or enhance the performance of the system. This thesis tackles compressive sensing systems from this angle. We first propose an architecture that alleviates a critical requirement in compressive sensing: that the random signal should run at the Nyquist rate, which becomes prohibitive as the signal bandwidth increases. We provide theoretical and experimental results that demonstrate the effectiveness of the proposed architecture. Secondly, we propose a framework for manipulating the random signal in the frequency domain as suitable for specific applications. We use the framework to develop an architecture for reconfigurable ultra wide-band radios.