Complexity-aware design of a DA-based FIR filters

This work presents a novel technique to reduce the area of the hardwired lookup table (LUT) of DA-based FIR filters. It explores the optimal quantization on the real-valued LUT with optimal global scaling and error distribution, and we apply an effective error measure to estimate the quantization error on the FIR coefficients. Our approach enables designers to explicitly trade the quality for simple implementations at finer granularity than that solely by reducing the coefficient wordlengths. Moreover, in our simulations, the proposed method can save 30%-40% silicon area of conventional DA-based FIR filters under identical error constraints.