Coefficient decimation approach for realizing reconfigurable finite impulse response filters

A new approach to implement computationally efficient reconfigurable finite impulse response (FIR) filter is presented in this paper. If the coefficients of an FIR filter are decimated by M, i.e., if every M^th coefficient of the filter is kept unchanged and remaining coefficients are changed to zeros, a multi-band frequency response will be obtained. The resulting frequency responses will have centre frequencies at 2πk/M, where k is an integer ranging from 0 to M-1. If these multiband frequency responses are selectively masked using inherently low complex wide transition-band masking filters, different low-pass, high-pass, bandpass, and bandstop filters can be obtained. If every M^th coefficient is grouped together removing the zero coefficients in between, a decimated frequency response in comparison to the original frequency response is obtained. In this paper, we also show the design of a reconfigurable filter bank using the above approach.

I. Introduction

Linear phase finite impulse response (FIR) filters are widely employed in wireless and mobile communication systems because of the advantages such as guaranteed stability, linear phase and low coefficient sensitivity. But the main disadvantage of FIR filters is its high implementation complexity due to the requirement of higher order compared to its counterpart - infinite impulse response (IIR) filters. Several methods have been proposed in the literature for reducing the complexity of FIR filters. In [1], a frequency response masking (FRM) technique was employed for the synthesis of sharp transition-band FIR filters. The key idea of FRM technique is that, a sharp transition-band filter can be obtained by combining several wide transition-band FIR sub-filters. The resulting FRM filter structure has lower filter order and consequently low complexity. Several approaches have been proposed in literature which improved the frequency response characteristics and reduced the complexity of the FRM technique [2], [3]. But the main disadvantage of the FRM technique is that there is no control over the passband width which makes the design of the resulting filter tedious.