Continuously Variable Bandwidth Sharp FIR Filters with Low Complexity

Abstract

In software defined radio (SDR), sharp filters of different bandwidth are required to fine tune the desired channel. This requires different computational resources and large number of filter coefficients. This paper proposes a continuously variable bandwidth sharp finite impulse response (FIR) filter with low distortion and low complexity. For this, a fixed length FIR filter is used with two arbitrary sampling rate converters. This system can be used for both the continuous increase as well as decrease of the effective bandwidth of a filter. The low complexity and sharpness are achieved by using the frequency-response masking (FRM) approach for the design of the fixed length FIR filter. The sharp transition width leads to maximum rejection to channel interference in SDR

Design of Multiplier-less Continuously Variable Bandwidth Sharp FIR Filters using Modified Gravitational Search Algorithm

“…In [8], a VBF which is capable of bandwidth reduction as well as enhancement has been proposed by us. The FRM filter in the middle block of the Figure 1 is replaced with the proposed GSA optimized filter and the simulation result of the overall system for the bandwidth reduction and enhancement are given in Figure 9 and Figure 10 respectively.…”

“…n(x) denotes the average number of non zero SPT coefficients after optimization and n b is the upper bound of n(x). The penalty method [19] can be used for keeping the optimization problem as an unconstrained one by including the penalty function given by Equation (7) and the final objective function for the coefficient synthesis of FRM filter can be formulated as Equation (8).…”

“…So we can change the absolute bandwidth of a filter by operating it at a different sampling rate. The technique used in [8] is used for changing the bandwidth continuously in decreasing and increasing fashion.…”

“…This effectively changes the bandwidth. The complexity reductions as well as the sharp transition bandwidth are achieved by using a FRM based FIR filter which is having large number of zero valued multiplier coefficients [8].…”

Reducing Complexity of FIR Filters using Narrowband Filters

“…(1) (2) Where "f s " is sampling frequency & "Δf" is Transition Bandwidth [1].Conventional FIR filters with narrow transition bands and high orders might be too complex to implement. We might consider designing narrowband filters using the IIR filters.…”