Device and method for realizing fpga of fblms algorithm based on block floating point

Abstract

The invention belongs to the technical field of real-time adaptive signal processing, and in particular relates to an FPGA implementation device and method for an FBLMS algorithm based on block floating point, aiming at solving the conflict between performance, speed and resources when the existing FPGA device implements the FBLMS algorithm The problem. The invention includes: the input buffer transform module reorganizes the reference signal block buffer, converts it to block floating point and then FFT transforms; the filter module filters in the frequency domain and dynamically truncates the bit; the error calculation and output buffer module buffers the target signal in blocks, in the After converting to block floating point, it is subtracted from the filtering output and converted to fixed-point system to obtain the final cancellation result; the weight adjustment calculation module and the weight update storage module obtain the adjustment amount of the weight value, and update the weight value by block. Aiming at the recursive structure of the FBLMS algorithm, the invention adopts the block floating point data format and the dynamic truncation method to ensure that the data has a large dynamic range and high precision, and solves the conflict between performance, speed and resources, and the modular design also Improved reusability and scalability.

Description

technical field [0001] The invention belongs to the technical field of real-time adaptive signal processing, and in particular relates to an FPGA implementation device and method of FBLMS algorithm based on block floating point. Background technique [0002] The theoretical research and hardware implementation of adaptive filtering algorithm has always been one of the research hotspots in the field of signal processing. When the statistical characteristics of the input signal and noise are unknown or changed, the adaptive filter can automatically adjust its parameters under the premise of satisfying certain criteria, and always achieve optimal filtering. Adaptive filters have been widely used in many fields such as signal detection, digital communication, radar, engineering geophysical exploration, satellite navigation and industrial control. From the point of view of system design, computational complexity, structure and robustness are the three most important criteria for...

AI Technical Summary

Problems solved by technology

Based on the above advantages, FPGA has been widely used in the hardware implementation of various signal processing algorithms. However, FPGA has shortcomings in processing high-precision floating-point operations, which will consume a lot of hardware resources, and even make complex algorithms difficult to implement.

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