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A Reconfigurable Systolic Array Architecture for Multicarrier Wireless and Multirate Applications
Author(s) -
H. Ho,
V. Szwarc,
T. Kwaśniewski
Publication year - 2009
Publication title -
international journal of reconfigurable computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.236
H-Index - 16
eISSN - 1687-7209
pISSN - 1687-7195
DOI - 10.1155/2009/529512
Subject(s) - polyphase system , computer science , digital signal processing , fast fourier transform , electronic circuit , modular design , circuit complexity , throughput , systolic array , parallel computing , wireless , embedded system , computer architecture , computer hardware , very large scale integration , electronic engineering , algorithm , engineering , electrical engineering , telecommunications , operating system
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

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