Improving Generalized Discrete Fourier Transform (GDFT) Filter Banks with Low-Complexity and Reconfigurable Hybrid Algorithm

With ever-increasing wireless network demands, low-complexity reconfigurable filter design is expected to continue to require research attention. Extracting and reconfiguring channels of choice from multi-standard receivers using a generalized discrete Fourier transform filter bank (GDFT-FB) is computationally intensive. In this work, a lower compexity algorithm is written for this transform. The design employs two different approaches: hybridization of the generalized discrete Fourier transform filter bank with frequency response masking and coefficient decimation method 1; and the improvement and implementation of the hybrid generalized discrete Fourier transform using a parallel distributed arithmetic-based residual number system (PDA-RNS) filter. The design is evaluated using MATLAB 2020a. Synthesis of area, resource utilization, delay, and power consumption was done on a Quartus 11 Altera 90 using the very high-speed integrated circuits (VHSIC) hardware description language. During MATLAB simulations, the proposed HGDFT algorithm attained a 66% reduction, in terms of number of multipliers, compared with existing algorithms. From co-simulation on the Quartus 11 Altera 90, optimization of the filter with PDA-RNS resulted in a 77% reduction in the number of occupied lookup table (LUT) slices, an 83% reduction in power consumption, and an 11% reduction in execution time, when compared with existing methods.