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Power Efficient Adaptive FIR Filter Design for Low Power DSP Applications


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1 Anna University, Chennai, India
     

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This paper presents the design of power efficient adaptive finite impulse response (FIR) filters where the filter order can be dynamically changed. The filter order can be changed by detecting the amplitude of the input samples and filter coefficients. The power consumption depends upon the filter order. In existing system coefficients are not programmable. An adaptive filtering is employed in proposed approach by means of Least Mean Square Algorithm (LMS).It uses feedback in the form of an error signal, which will again send to the amplitude detection logic and accordingly coefficient will get modified in order to get the desired output. Amplitude Detection (AD) block is used to detect the amplitude of the input signal. We can dynamically change the filter order by turning off some multipliers. The amount of computation and the corresponding power consumption of FIR filter are directly proportional to the filter order. significant power savings can be achieved, if the amplitude of input x(n)abruptly changes for every cycle then multiplier will be turned on and off continuously. Multiplier control decision window is used to solve the switching problem using ctrl signal generator inside MCSD. The number of input samples consecutively smaller than xth are counted and the multipliers are turned off only when m consecutive input samples are smaller than xth. The proposed scheme will improve the performance of the filter with the improvement in the power savings.

Keywords

Adaptive Filtering, AD, FIR Filter, LMS, MCSD.
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  • Power Efficient Adaptive FIR Filter Design for Low Power DSP Applications

Abstract Views: 157  |  PDF Views: 3

Authors

P. Dhanya
Anna University, Chennai, India

Abstract


This paper presents the design of power efficient adaptive finite impulse response (FIR) filters where the filter order can be dynamically changed. The filter order can be changed by detecting the amplitude of the input samples and filter coefficients. The power consumption depends upon the filter order. In existing system coefficients are not programmable. An adaptive filtering is employed in proposed approach by means of Least Mean Square Algorithm (LMS).It uses feedback in the form of an error signal, which will again send to the amplitude detection logic and accordingly coefficient will get modified in order to get the desired output. Amplitude Detection (AD) block is used to detect the amplitude of the input signal. We can dynamically change the filter order by turning off some multipliers. The amount of computation and the corresponding power consumption of FIR filter are directly proportional to the filter order. significant power savings can be achieved, if the amplitude of input x(n)abruptly changes for every cycle then multiplier will be turned on and off continuously. Multiplier control decision window is used to solve the switching problem using ctrl signal generator inside MCSD. The number of input samples consecutively smaller than xth are counted and the multipliers are turned off only when m consecutive input samples are smaller than xth. The proposed scheme will improve the performance of the filter with the improvement in the power savings.

Keywords


Adaptive Filtering, AD, FIR Filter, LMS, MCSD.