Table of Contents Author Guidelines Submit a Manuscript
International Journal of Reconfigurable Computing
Volume 2009 (2009), Article ID 529512, 14 pages
Research Article

A Reconfigurable Systolic Array Architecture for Multicarrier Wireless and Multirate Applications

1Terrestrial Wireless Systems, Communications Research Centre, 3701 Carling Avenue, BOX 11490, Station H, Ottawa, ON, Canada K2H 8S2
2Department of Electronics, Carleton University, 1125 Colonel By Drive, Ottawa, ON, Canada K1S 5B6

Received 26 November 2008; Accepted 23 June 2009

Academic Editor: Neil Bergmann

Copyright © 2009 H. Ho et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A reconfigurable systolic array (RSA) architecture that supports the realization of DSP functions for multicarrier wireless and multirate applications is presented. The RSA consists of coarse-grained processing elements that can be configured as complex DSP functions that are the basic building blocks of Polyphase-FIR filters, phase shifters, DFTs, and Polyphase-DFT circuits. The homogeneous characteristic of the RSA architecture, where each reconfigurable processing element (PE) cell is connected to its nearest neighbors via configurable switch (SW) elements, enables array expansion for parallel processing and facilitates time sharing computation of high-throughput data by individual PEs. For DFT circuit configurations, an algorithmic optimization technique has been employed to reduce the overall number of vector-matrix products to be mapped on the RSA. The hardware complexity and throughput of the RSA-based DFT structures have been evaluated and compared against several conventional modular FFT realizations. Designs and circuit implementations of the PE cell and several RSAs configured as DFT and Polyphase filter circuits are also presented. The RSA architecture offers significant flexibility and computational capacity for applications that require real time reconfiguration and high-density computing.