Pipeline Architectures for Radix-2 New Mersenne Number Transform

Omar Nibouche, Said Boussakta, Michael Darnell

    Research output: Contribution to journalArticlepeer-review

    21 Citations (Scopus)


    Number theoretic transforms which operate in rings or fields of integers and use modular arithmetic operations can perform operations of convolution and correlation very efficiently and without round-off errors; thus, they are well matched to the implementation of digital filters. One such transform is the new Mersenne number transform, which relaxes the rigid relationship between the length of the transform and the wordlength in Fermat and Mersenne number transforms where the kernel is usually equal to a power of two. In this paper, three novel pipeline architectures that implement this transform are presented. The proposed architectures are scalable, parameterized, and can be easily pipelined; they are thus ideally suited to very high speed integrated circuit hardware-description-language (VHDL) descriptions. These architectures process data sequentially and have either one or two inputs and two or four outputs. The different input and output formats have resulted in the proposed architectures having different performances in terms of processing time and area requirements. Furthermore, they give the designer more choices in meeting the requirements of the application being implemented. A field-programmable gate array (FPGA) implementation of the proposed architectures has demonstrated that a throughput rate of up to 6.09 Gbit/s can be achieved for a 1024-sample transform, with samples coded to 31 bits.
    Original languageEnglish
    Pages (from-to)1668-1680
    JournalIEEE Transactions on Circuits and Systems I: Regular Papers
    Issue number8
    Publication statusPublished (in print/issue) - 14 Aug 2009

    Bibliographical note

    Reference text: [1] C. M. Rader, “Discrete convolutions via Mersenne transforms,” IEEE Trans. Comput., vol. C-21, no. 12, pp. 1269–1273, Dec. 1972.
    [2] R. C. Agarwal and C. S. Burrus, “Number theoretic transforms to implement fast digital convolution,” Proc. IEEE, vol. 63, no. 4, pp. 550–560, Apr. 1975.
    [3] R. C. Agarwal and C. S. Burrus, “Fast convolution using Fermat number transform with application to digital filtering,” IEEE Trans. Acoust., Speech, Signal Process., vol. ASSP-22, no. 2, pp. 87–97, Apr. 1974.
    [4] H. J. Nussbaumer, “Relative evaluation of various number theoretic transforms for digital filtering applications,” IEEE Trans. Acoust., Speech, Signal Process., vol. Vol. ASSP-26, no. 1, pp. 88–93, Feb. 1978.
    [5] R. Conway, “Modified overlap technique using Fermat and Mersenne transforms,” IEEE Trans. Circuits Syst. II, Exp. Briefs, vol. 53, no. 8, pp. 632–636, Aug. 2006.
    [6] V. M. Chernov, “Fast algorithm for error-free convolution computation using Mersenne–Lucas codes,” Chaos, Solitons Fractals, vol. 29, no. 2, pp. 372–380, Jul. 2006.
    [7] S. Gudvangen, “Practical applications of number theoretic transforms,” in Proc. NORSIG, Asker, Norway, Sep. 10–11, 1999, pp. 102–107.
    [8] R. Kumar, “A fast algorithm for solving a Toeplitz system of equations,” IEEE Trans. Acoust., Speech, Signal Process., vol. ASSP-33, no. 1, pp. 254–267, Feb. 1985.
    [9] J. J. Hsue and A. E. Yagle, “Fast algorithms for solving Toeplitz systems of equations using number theoretic transforms,” IEEE Trans. Signal Process., vol. 44, no. 1, pp. 89–101, Jun. 1995.
    [10] T. Lundy and J. V. Buskirk, “A new matrix approach to real FFTs and convolutions of length


    • New Mersenne number transform (NMNT)
    • number theoretic transform (NTT)
    • pipeline architectures.


    Dive into the research topics of 'Pipeline Architectures for Radix-2 New Mersenne Number Transform'. Together they form a unique fingerprint.

    Cite this