Design and implementation of low complexity multiplier less reconfigurable band tuning filter structure with sharp sub bands

Abstract

Digital flter banks are extensively used for communication purposes for channelization. Reconfgurable non-uniform multi-channels with sharp transition widths are necessary for channelization in digital channelizer and spectrum sensing in wireless communication networks. The aim of this research work is to design reconfgurable flter structures featuring non-uniform and sharp transition newlinewidth channels with reduced number of flter coeffcients. The four different flter structures are proposed in this research for achieving low complexity reconfgurable structure for the design of multiple non-uniform sharp transition width arbitrary bandwidth channels. The foundational newlineelement of this research is centered around the design of a prototype flter. This prototype flter serves as a basis for developing various reconfgurable flter structures. Leveraging the prototype newlineflter s bandwidth characteristics, these structures are categorized into two main groups: narrow band prototype flters and wide band prototype flters. The narrow band prototype flter category comprises structures capable of designing a single fnite impulse response flter with a narrow passband characterized by sharp transition widths. In contrast, the wide band prototype flter category includes structures capable of designing a single FIR flter with a wide passband also characterized by sharp transition widths. A novel flter structures are designed with the help of interpolated newlinefnite impulse response, cosine modulation technique, complex exponential modulation technique and frequency response masking techniques. The proposed method is evaluated using MATLAB R2019b, where the linear phase FIR flter coeffcients are computed based on the Parks-McClellan algorithm. The examples are employed to illustrate the effcient operation of the proposed designs. The results point to the fact that the proposed designs have less multiplier complexity than existing cuttingedge techniques.