The rapid rise in computational performance offered by computer systems has greatly increased the number of practical software defined radio applications. The addition of FPGAs to these flexible systems has resulted in platforms that can address a multitude of applications with performance levels that were once only known to ASICs. This work presents an embedded heterogeneous scalable cluster platform with software defined radio applications. The Xilinx Zynq chip provides a hybrid platform consisting of an embedded ARM general-purpose processing core and a low-power FPGA. The ARM core provides all of the benefits and ease of use common to modern high-level software languages while the FPGA segment offers high performance for computationally intensive components of the application. Four of these chips were combined in a scalable cluster and a task assigner was written to automatically place data flows across the FPGAs and ARM cores. The rapid reconfiguration software tFlow was used to dynamically build arbitrary FPGA images out of a library of pre-built modules. / Master of Science

Two research projects are proposed that rely on Tools for open Reconfigurable Computing (TORC) and the openness of the Xilinx tool chain. The first project, the Embedded FPGA Transmitter, relies on the ability to add arbitrary routes to a physical FPGA which serve no obvious purpose. These routes can then mimic an antenna and transmit directly from the FPGA. This mechanism is not supported utilizing standard hardware description languages; however, the Embedded FPGA Transmitter requires measurements on a real FPGA to determine success. The second project is a back-end tools accelerator designed to reduce the compilation time for FPGA times. As the complexity of FPGAs have exceeded over a million logic cells, the compilation problem size has greatly expanded. The open-source project, TORC, provides an excellent framework for new FPGA research that provides physical, real-world results to ensure the applicability of the research. / Master of Science

Traditional hardware radios provide very rigid solutions to radio problems. Intelligent software defined radios, also known as cognitive radios, provide flexibility and agility compared to hardware radio systems. Cognitive radios are well suited for radio applications in a changing radio frequency environment, such as dynamic spectrum access. In this thesis, a cognitive radio is demonstrated where the system self reconfigures to demodulate a detected waveform. The GNU Radio framework is used to provide basic software defined radio building blocks and is supplemented with FPGA accelerators. The use of GNU Radio compliant hardware interfaces allows for seamless hardware/software radio deployments. Dynamic resource mapping allows radio designers to operate at a layer of abstraction above the physical radio implementation. By establishing lower level abstraction layers, future researchers can focus on larger picture concepts such as learning algorithms and behavioral models for the cognitive engine. / Master of Science