The Multipolynomial Channel

The residue number system (RNS) is an integer system appropriate for implementing fast digital signal processors since it can support parallel carry-free high-speed arithmetic. A recent development in residue arithmetic is the polynomial RNS (PRNS) which can perform a polynomial product modulo ( ) with only multiplications instead of , provided that arithmetic takes place in appropriate modular rings. The PRNS, however, has one major limitation in that the sizes of the modular rings used for the PRNS arithmetic are proportional to the size of the polynomials to be multiplied. As a result, if large polynomials need to be multiplied, large modular rings must be chosen, a fact which can imply severe performance degradation of the entire system. In this paper, a solution to the major limitation of the PRNS is offered. The solution is the multipolynomial channel PRNS, which is capable of performing large polynomial products requiring large dynamic ranges with arithmetic performed in many small modular rings. This way, very high-speed internal PRNS processing is ensured.

[1]  W. Kenneth Jenkins,et al.  The use of residue number systems in the design of finite impulse response digital filters , 1977 .

[2]  Fred J. Taylor,et al.  A Fault-Tolerant GEQRNS Processing Element for Linear Systolic Array DSP Applications , 1995, IEEE Trans. Computers.

[3]  Fred J. Taylor,et al.  A Radix-4 FFT Using Complex RNS Arithmetic , 1985, IEEE Transactions on Computers.

[4]  Michael A. Soderstrand,et al.  Residue number system arithmetic: modern applications in digital signal processing , 1986 .

[5]  G. Jullien,et al.  The modified quadratic residue number system (MQRNS) for complex high-speed signal processing , 1986 .

[6]  W. K. Jenkins,et al.  Redundant residue number systems for error detection and correction in digital filters , 1980 .

[7]  Graham A. Jullien,et al.  Processor Architectures for Two-Dimensional Convolvers Using a Single Multiplexed Computational Element with Finite Field Arithmetic , 1983, IEEE Transactions on Computers.

[8]  W. Kenneth Jenkins,et al.  The Design of Error Checkers for Self-Checking Residue Number Arithmetic , 1983, IEEE Transactions on Computers.

[9]  Piero Maestrini,et al.  Error Correcting Properties of Redundant Residue Number Systems , 1973, IEEE Transactions on Computers.

[10]  Rajendra S. Katti,et al.  A New Residue Arithmetic Error Correction Scheme , 1996, IEEE Trans. Computers.

[11]  F. Taylor,et al.  On the Polynomial Residue Number System , 1991 .

[12]  M. Soderstrand,et al.  A pipelined recursive residue number system digital filter , 1984 .

[13]  Alexander Skavantzos,et al.  On the binary quadratic residue system with noncoprime moduli , 1997, IEEE Trans. Signal Process..

[14]  A. Skavantzos Using quadratic residue arithmetic for computing skew cyclic convolutions , 1991 .

[15]  M. Soderstrand A high-speed low-cost recursive digital filter using residue number arithmetic , 1977, Proceedings of the IEEE.

[16]  W K Jenkins Recent advances in residue number techniques for recursive digital filtering , 1979 .

[17]  Thanos Stouraitis,et al.  Polynomial residue complex signal processing , 1993 .

[18]  Chin-Liang Wang New bit-serial VLSI implementation of RNS FIR digital filters , 1994 .

[19]  A. Skavantzos,et al.  Implementation issues of 2-dimensional polynomial multipliers for signal processing using residue arithmetic , 1993 .

[20]  W. A. Chren RNS-based enhancements for direct digital frequency synthesis , 1995 .

[21]  Thanos Stouraitis,et al.  Parallel Decomposition Of Complex Multipliers , 1988, Twenty-Second Asilomar Conference on Signals, Systems and Computers.

[22]  Application of Quadratic-Like complex residue number system arithmetic to ultrasonics , 1984, ICASSP.