TABLE OF CONTENTS The rapid growth of communication and multimedia technologies over the last decade has dramatically expanded the range of digital signal processing (DSP) applications. The ongoing need to implement an increasingly complex algorithm at higher speeds and lower price points is a result of increasing demand for advanced information services, increased bandwidth and expanded media handling capability. Some of the evolving high performance applications include advanced wired and wireless voice, data and video processing.
The growth of communications and multimedia applications such as internet communications, secure wireless communications and consumer entertainment devices has driven the need for devices and structures capable of efficiently implementing complex math and signal processing algorithms.
Some typical DSP algorithms required by these applications include fast Fourier transform (FFT), discrete cosine transform (DCT), Wavelet Transform, and digital filters (finite impulse response (FIR), infinite impulse response (IIR) and adaptive filters), and digital up and down converter. Each of these algorithms have structural elements that may be implemented with parallel functionality. FPGA architectures are able to implement parallel architectures efficiently.
FPGA architectures include resources capable of more advanced, higher-performance signal processing with each new FPGA device family. FPGA technology supports an increasing range of complex math and signal processing intellectual property. Advances in tool integration now support simplified system-level design. With front-end tools such as MATLAB , pushbutton conversion from block-level system design to HDL-level code is possible. Chip density and process technology advances also support larger, more capable signal processing implementations.
FPGA implementation provides the...
