Autonomous System on a Chip Adaptation through Partial Runtime Reconfiguration

This paper presents a prototype autonomous signal processing system on a chip. The system is architected such that high performance digital signal processing occurs in the FPGA¿s configurable logic, while resulting higher level data products are monitored by cognitive algorithms residing on an embedded processor. The cognitive algorithms develop situational awareness about the platform¿s environment, and use this information to modify and tune signal processing in real-time using active partial reconfiguration. This system was realized on a Xilinx Virtex4 FX 100 device on a pulse parameter measurement application utilizing a Bayesian Network cognitive algorithm. Changes in the RF environment were correctly detected 96.7% of the time and mitigation filters which resulted in at least 3dB interference rejection improvement were instanced 81% of the time. This system realizes a 71.4× reduction in size compared to static implementations and a 26-43× reduction in reaction times compared to human in the loop systems.

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