Efficient Mutliplierless Polyphase FIR Filter based on New Distributed Arithmetic Architecture

Abstract

This paper present an efficient polyphase multiplierless finite impulse response (FIR) architecture based on New Distributed Arithmetic (NEDA). The polyphase structure is based on the decomposition of the transfer function in subfilters connected in parallel. The multiplications involved on each subfilter are replaced by an adder array implemented by NEDA. These subblocks presents a different distribution of Is and Os on the NEDA matrix compared with the implementation of the filter in a direct form or transposed form. NEDA presents a bottleneck that is reduced by a balance between a larger filter order and a reduced coefficient wordlength size impacting the whole structure with this tradeoff. This new architecture involves a reduced number of adders in their implementation without significant overhead. The results presented are compared with previous approaches showing superior result around of 34% average reduction on the total number of adders. Additionally, the proposed design method for FIR filter is simple.

A Novel Approach for Polyphase Filter Bank Design Using ABC Algorithm

“…The realized design provides a number of advantages that increase easy portability by optionally using logic sources and Hardware Description Language (HDL) sources. Tecpanecatl-Xihuitl, Aguilar-Ponce, Ismail, and Bayoumi [4] explained the polyphase filter using a new distributed arithmetic algorithm with fewer multipliers. In accordance with the aims of making the filter multiplier less, the new Distributed Arithmetic (DA) algorithm and the designed adder array are used.…”

“…Polyphase filter structures reduce the number of computations per cycle because they remove inputs and data samples that are discarded due to interpolation and sample dilution processes. The polyphase realization process increases the efficiency of the Finite Impulse Response (FIR) filter in terms of the variation in the sampling rate [4]. Polyphase filter banks (PFBs), based on quadrature mirror filters (QMFs), have been successfully used to divide a signal into N subbands and allow resynthesis of the signal arriving from the subbands, creating a very fast signal processing system.…”