This paper presents a novel approach for implementing area-efficient parallel (block) finite impulse response (FIR) filters that require less hardware than traditional block FIR filter implementations. Parallel processing is a powerful technique because it can be used to increase the throughput of a FIR filter or reduce the power consumption of a FIR filter. However, a traditional block filter implementation causes a linear increase in the hardware cost (area) by a factor of L, the block size. In many design situations, this large hardware penalty cannot be tolerated. Therefore, it is important to design parallel FIR filter structures that require less area than traditional block FIR filtering structures. In this paper, we propose a method to design parallel FIR filter structures that require a less-than-linear increase in the hardware cost. A novel adjacent coefficient sharing based sub-structure sharing technique is introduced and used to reduce the hardware cost of parallel FIR filters. A novel coefficient quantization technique, referred to as a scalable maximum absolute difference (MAD) quantization process, is introduced and used to produce quantized filters with good spectrum characteristics. By using a combination of fast FIR filtering algorithms, a novel coefficient quantization process and area reduction techniques, we show that parallel FIR filters can be implemented with up to a 45% reduction in hardware compared to traditional parallel FIR filters.
|Original language||English (US)|
|Number of pages||18|
|Journal||Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology|
|State||Published - Dec 1 1997|