Adaptive Multirate Filter Bank Architecture for High-Performance Digital Signal Processing Applications

Abstract

Compile a signal processing workload for performance verification to build a better product.Reduce the number of iterations in signal processing tasks and verify the performance in a modern digital signal processing (DSP) system. The filtering banks which are widely used for efficient subband decomposition and reconstruction are used in communication, audio, biomedical and embedded signal processing systems. But traditional filter bank designs are generally complex, less flexible and slower in the dynamic operation. The adaptive multirate filter bank architecture for high performance DSP applications proposed in this paper utilizes the polyphase decomposition and adaptive analysis–synthesis filter. The proposed architecture is designed to be an 8-channel filter bank which has adaptive coefficient optimization and capability of perfect reconstruction to maximize processing efficiency without compromising the fidelity of the reconstructed signal. A comprehensive mathematical model is developed which describe the operations of decimation, interpolation and polyphases in the system. The Matlab simulation is done using the sample rate of 48kHz and filter size varying from 32 to 128 taps. The proposed architecture is able to reconstruct with an accuracy of 99.3%, SNR of 48.6 dB and mean square error of 1.8 × 10⁻⁴. Moreover, the architecture can decrease the computation complexity by 34.7% when compared with the traditional FIR filter bank and 21.5% when compared with the DFT-based filter bank implementation. The throughput analysis indicates that the processor can process 215 MSamples/s with an average latency of 0.82ms, making it suitable for real-time applications in high-speed DSP systems. A comparison of the results reveals that the proposed algorithm improves the accuracy of reconstruction by 12.4% and increases the efficiency of computation by 28.9% compared with the non-adaptive multirate systems. The proposed architecture also shows good communication systems, speech and audio processing, biomedical signal analysis, software-defined radio and embedded-processing scalability. The outcomes validate that adaptive multirate filter bank architectures are an attractive solution for achieving both high performance and low complexity real-time digital signal processing (DSP) in the next-generation intelligent systems.