Special Issue Article
High Throughput, Low Area, Low Power Distributed Arithmetic Formulation for Adaptive Filter
DA formulation employed for two separate blocks weight update block and filteringoperations requires larger area and is not suited for higher order filters therefore causes reduction in the throughput.These problems have been overcome by efficient distributed formulation of Adaptive filters. LMS adaptation performed on a sample-bysample basis is replaced by a dynamic LUT update using a weight update scheme. Further, parallelLUT update and concurrent implementation of filtering and weight-update operations significantly increases throughput rate. Adder based shift accumulation for inner product computation replaced by conditional signed carry-save accumulation reduces the sampling period and area complexity. Fast bit clock reduction for carry-save accumulation reduces power consumption. It involves the same number of multiplexers, smaller LUT, and nearly half the number of adders compared to the previous DA-based design.