30-07-2012, 03:22 PM
Field Programmable Gate Array (FPGA)
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INTRODUCTION
In the recent years, there has been a growing trend to implement digital signal processing functions in Field Programmable Gate Array (FPGA). In this sense, we need to put great effort in designing efficient architectures for digital signal processing functions such as FIR filters, which are widely used in video and audio signal processing, telecommunications and etc.
Traditionally, direct implementation of a K-tap FIR filter requires K multiply-and-accumulate (MAC) blocks, which are expensive to implement in FPGA due to logic complexity and resource usage. To resolve this issue, Croisier first presented DA, which is a multiplier-less architecture. This technique is based on using 2's complement binary representation of data, and the data can be pre-computed and stored in LUT. As DA is a very efficient solution especially suited for LUT-based FPGA architectures, many researchers put great effort in using DA to implement FIR filters in FPGA.
Partrick Longa introduced the structure of the FIR filter using DA algorithm and the functions of each part. Sangyun Hwang analyzed the power consumption of the filter using DA algorithm. Heejong Yoo proposed a modified DA architecture that gradually replaces LUT requirements with multiplexer/adder pairs.
The main problem of DA is that the requirement of LUT capacity increases exponentially with the order of the filter, given that DA implementations need 2Kwords (K is the number of taps of the filter). And if K is a prime, the hardware resource consumption will cost even higher.
To overcome these problems, this paper presents a hardware-efficient DA architecture. This method not only reduces the LUT size, but also modifies the structure of the filter to achieve high speed performance.
The proposed filter has been designed and synthesized with ISE 7.1, and implemented on a 4VLX40FF668 FPGA device. Our results show that the proposed DA architecture can implement FIR filters with higher speed and small resource usage in comparison to the previous DA architecture.
FILTERS
A system or network that selectively changes characteristics of a signal is a filter.
There are 2 types of filters
• Analog filter
• Digital filter
Analog Filter:
Analogue filters are a basic building block of signal processing much used in electronics. Amongst their many applications are the separation of an audio signal before application to bass, mid-range and tweeter loudspeakers; the combining and later separation of multiple telephone conversations onto a single channel.
Some of the examples are
Simple filters. The frequency dependence of electrical response was known for capacitors and inductors.
Image filters. Image filter theory grew out of transmission line theory and the design proceeded in a similar manner to transmission line analysis.
Network synthesis filters. The mathematical bases of network synthesis.
Digital filter:
Digital Filters can be very complicated devices, but they must be able to map to the difference equations of the filter design. This means that since difference equations only have a limited number of operations available (addition and multiplication), digital filters only have limited operations that they need to handle as well. There are only a handful of basic components to a digital filter, although these few components can be arranged in complex ways to make complicated filters.
There are two types of filters in the digital realm:
• Infinite Impulse Response (IIR) filters
• Finite Impulse Response (FIR) filters
Infinite Impulse Response (IIR) filters:
IIR filters are harder to design than the FIR filters, but the benefits are extraordinary: IIR filters are an order of magnitude more efficient than an equivalent FIR filter. Even though FIR is easier to design, IIR will do the same work with fewer components, and fewer components translate directly to less money. IIR filters differ from FIR filters because they always contain feedback elements in the circuit, which can make the transfer functions more complicated to work with.
The transfer function of an IIR filter contains both poles and zeros. Its impulse response never decays to zero (though it may get so close to zero that the response cannot be represented with the number of bits available in the system).
Finite Impulse Response (FIR) filters:
Finite impulse response (FIR) filters are the most popular type of filters implemented in software. This introduction will help you understand them both on a theoretical and a practical level.
Simple filters are usually defined by their responses to the individual frequency components that constitute the input signal. There are three different types of responses. A filter's response to different frequencies is characterized as pass band, transition band, or stop band.