Reducing Processing Latency with a Heterogeneous FPGA-Processor Framework

Abstract

Both Xilinx and Altera have released SoCs that tightly couple programmable logic with a dual core Cortex A9 ARM processor. These SoCs show promise in accelerating applications that exploit both the FPGA's parallel processing architecture and the CPU's sequential processing. %Spectrum sensing in cognitive radios is one such application. For example, before accessing a wireless channel, a cognitive radio does spectrum sensing to detect channel occupancy and then makes a decision based on spectrum policies. Spectrum sensing maps well to FPGA fabric, while spectrum decision can be implemented with a CPU. Both algorithms are highly sensitive to latency as a faster decision improves spectrum utilization. This paper introduces CRASH: Cognitive Radio Accelerated with Software and Hardware -- a new software and programmable logic framework for Xilinx's Zynq SoC targeting cognitive radio. We implement spectrum sensing and the spectrum decision in three configurations: both algorithms in the FPGA, both in software only, and spectrum sensing on the FPGA and spectrum decision on the CPU. We measure the end-to-end latency to detect and acquire unoccupied spectrum for these configurations. Results show that CRASH can successfully partition algorithms between FPGA and CPU and reduce processing latency.