A VLSI pipeline design of a fast prime factor DFT on a finite field

A conventional prime factor discrete Fourier transform (DFT) algorithm is used to realize a discrete Fourier-like transform on the finite field, GF(q sub n). A pipeline structure is used to implement this prime factor DFT over GF(q sub n). This algorithm is developed to compute cyclic convolutions of complex numbers and to decode Reed-Solomon codes. Such a pipeline fast prime factor DFT algorithm over GF(q sub n) is regular, simple, expandable, and naturally suitable for VLSI implementation. An example illustrating the pipeline aspect of a 30-point transform over GF(q sub n) is presented

Number theoretic techniques applied to algorithms and architectures for digital signal processing

Many of the techniques for the computation of a two-dimensional convolution of a small fixed window with a picture are reviewed. It is demonstrated that Winograd's cyclic convolution and Fourier Transform Algorithms, together with Nussbaumer's two-dimensional cyclic convolution algorithms, have a common general form. Many of these algorithms use the theoretical minimum number of general multiplications. A novel implementation of these algorithms is proposed which is based upon one-bit systolic arrays. These systolic arrays are networks of identical cells with each cell sharing a common control and timing function. Each cell is only connected to its nearest neighbours. These are all attractive features for implementation using Very Large Scale Integration (VLSI). The throughput rate is only limited by the time to perform a one-bit full addition. In order to assess the usefulness to these systolic arrays a 'cost function' is developed to compare them with more conventional techniques, such as the Cooley-Tukey radix-2 Fast Fourier Transform (FFT). The cost function shows that these systolic arrays offer a good way of implementing the Discrete Fourier Transform for transforms up to about 30 points in length. The cost function is a general tool and allows comparisons to be made between different implementations of the same algorithm and between dissimilar algorithms. Finally a technique is developed for the derivation of Discrete Cosine Transform (DCT) algorithms from the Winograd Fourier Transform Algorithm. These DCT algorithms may be implemented by modified versions of the systolic arrays proposed earlier, but requiring half the number of cells

Simulation of Parallel Pipeline Radix 2^2 Architecture

In popular orthogonal frequency division multiplexing (OFDM) communication system processing is one of the key procedures Fast Fourier transform (FFT) and inversely for that Fast Fourier Transform (IFFT) is one of them. In this VLSI implementation Structured pipeline architectures, low power consumption, high speed and reduced chip area are the important concerns. In this paper, presentation of the worthy implementation of FFT/IFFT processor for OFDM applications is described. We obtain the single-path delay feedback architecture, to get a ROM of smaller size and this proposed architecture applies a reconfigurable complex multiplier. To minimize the error of truncation we apply a fixed width modified booth multiplier. As a result, the proposed radix-2k feed forward architectures even offer an attractive solution for current applications, and also open up a new research line on feed forward structures

The Telecommunications and Data Acquisition Report

This publication, one of a series formerly titled The Deep Space Network (DSN) Progress Report, documents DSN progress in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations. In addition, developments in Earth-based radio technology as applied to geodynamics, astrophysics, and the radio search for extraterrestrial intelligence are reported

Accelerating Polynomial Multiplication for RLWE using Pipelined FFT

The evolution of quantum algorithms threatens to break public key cryptography in polynomial time. The development of quantum-resistant algorithms for the post-quantum era has seen a significant growth in the field of post quantum cryptography (PQC). Polynomial multiplication is the core of Ring Learning with Error (RLWE) lattice based cryptography (LBC) which is one of the most promising PQC candidates. In this work, we present the design of fast and energy-efficient pipelined Number Theoretic Transform (NTT) based polynomial multipliers and present synthesis results on a Field Programmable Gate Array (FPGA) to evaluate their efficacy. NTT is performed using the pipelined R2SDF and R22SDF Fast Fourier Transform (FFT) architectures. In addition, we propose an energy efficient modified architecture (Modr2). The NTT-based designed polynomial multipliers employs the Modr2 architecture that achieve on average 2× better performance over the R2SDF FFT and 2.4× over the R22SDF FFT with similar levels of energy consumption. The proposed polynomial multiplier with Modr2 architecture reaches 12.5× energy efficiency over the state-ofthe-art convolution-based polynomial multiplier and 4× speedup over the systolic array NTT based polynomial multiplier for polynomial degrees of 1024, demonstrating its potential for practical deployment in future designs