Low-Power VLSI Architectures for DCT\/DWT: Precision vs Approximation for HD Video, Biomedical, and Smart Antenna Applications

• Published in: IEEE circuits and systems magazine (New York, N.Y. 2001) N.Y. 2001), 2015, Vol.15 (1), p.25-47
• Main Authors: Madanayake, Arjuna, Cintra, Renato J., Dimitrov, Vassil, Bayer, Fabio Mariano, Wahid, Khan A., Kulasekera, Sunera, Edirisuriya, Amila, Potluri, Uma Sadhvi, Madishetty, Shiva Kumar, Rajapaksha, Nilanka
• Format: Magazinearticle
• Language: English
• Subjects: Approximation methods; Artificial intelligence; Biomedical monitoring; Computer architecture; Discrete cosine transforms; Filter banks; Low power electronics; Smart antennas; Very large scale integration
• ISSN: 1531-636X; 1558-0830
• DOI: 10.1109/MCAS.2014.2385553

The DCT and the DWT are used in a number of emerging DSP applications, such as, HD video compression, biomedical imaging, and smart antenna beamformers for wireless communications and radar. Of late, there has been much interest on fast algorithms for the computation of the above transforms using multiplier-free approximations because they result in low power and low complexity systems. Approximate methods rely on the trade-off of accuracy for lower power and/or circuit complexity/chip-area. This paper provides a detailed review of VLSI architectures and CAS implementations for both DCT/DWTs, which can be designed either for higher-accuracy or for low-power consumption. This article covers both recent theoretical advancements on discrete transforms in addition to an overview of existing VLSI architectures. The paper also discusses error free VLSI architectures that provides high accuracy systems and approximate architectures that offer high computational gain making them highly attractive for real-world applications that are subject to constraints in both chip-area as well as power. The methods discussed in the paper can be used in the design of emerging low-power digital systems having lowest complexity at the cost of a loss in accuracy?the optimal trade-off of computational accuracy for lowest possible complexity and power. A complete synopsis of available techniques, algorithms and FPGA/VLSI realizations are discussed in the paper.