FPGA implementation of adaptive filters based on GSFAP using log arithmetic

Abstract

Adaptive filters are used in many applications of digital signal processing. Digital communications and digital video broadcasting are just two examples. The GSFAP algorithm, discussed in the paper, is characterized by convergence superior to the popular NLMS, with only slightly higher complexity. The paper deals with floating-point-like implementation of algorithm using FPGA hardware. We present an optimized core for the GSFAP, built using logarithmic arithmetic which provides very low cost multiplication and division. The design is crafted to make efficient use of the pipelined logarithmic addition units. The resulting GSFAP core can be clocked at more than 80 MHz on the one million gate Xilinx XC2VI000-4 device. It can be used to implement filters of orders 20 to 1000 with a sampling rate exceeding 50 kHz. For comparison, we implemented a similar NLMS core and found that although it is slightly smaller than the GSFAP core and it allows a higher signal sampling rate (around 70 kHz) for the corresponding filter orders, GSFAP has adaptation properties that are much superior to NLMS, and that our core can provide very sophisticated adaptive filtering capabilities for resource-constrained embedded systems