Optimization of Signal Processing Chains: Application to Cascaded Filters

The design of digital signal processing chains must meet competing requirements by maximizing performance (e.g. rejection in the case of a filter) while reducing resource consumption. In this paper, we explore a new methodology for designing chains assembled by cascading basic processing blocks. We apply this optimization strategy to the example of a cascade of Finite Impulse Response (FIR) filters. While the design of cascaded FIR filters generally focuses on low-level details, we provide a high-level model. This development strategy can be generalized for any signal processing chain made by assembling blocks whose resource consumption is qualified: a solver aims at meeting multiple objectives including minimizing resource consumption or optimizing performance. This result is then transformed into a synthesizable solution targeting a reconfigurable Field Programmable Gate Array (FPGA). The experiments show that this approach gives efficient results, both on the quality of the signal filtering and the processing resource used for the design.