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High-Speed Parallel LFSR Architectures Based on
Improved State-Space Transformations
ABSTRACT:
Linear feedback shift register (LFSR) has been widely applied in BCH and CRC
encoding. In order to increase the system throughput, the parallelization of LFSR is
usually needed. Previously, a technique named state-space transformation was
presented to reduce the complexity of parallel LFSR architectures. Exhaustive
searches are performed to find good transformation matrix candidates. This brief
proposes a new technique for construction of the transformation matrix together
with a more efficient searching algorithm. The realization results indicate that the
proposed architecture outperforms the prior arts, improving the hardware
efficiency by around 35% and the corresponding searching algorithm finds the
desirable transformation matrix much faster. The proposed architecture of this
paper analysis the logic size, area and power consumption using Xilinx 14.2.
SOFTWARE IMPLEMENTATION:
 Modelsim
 Xilinx ISE

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High-Speed Parallel LFSR Architectures Based on Improved State-Space Transformations

  • 1. High-Speed Parallel LFSR Architectures Based on Improved State-Space Transformations ABSTRACT: Linear feedback shift register (LFSR) has been widely applied in BCH and CRC encoding. In order to increase the system throughput, the parallelization of LFSR is usually needed. Previously, a technique named state-space transformation was presented to reduce the complexity of parallel LFSR architectures. Exhaustive searches are performed to find good transformation matrix candidates. This brief proposes a new technique for construction of the transformation matrix together with a more efficient searching algorithm. The realization results indicate that the proposed architecture outperforms the prior arts, improving the hardware efficiency by around 35% and the corresponding searching algorithm finds the desirable transformation matrix much faster. The proposed architecture of this paper analysis the logic size, area and power consumption using Xilinx 14.2. SOFTWARE IMPLEMENTATION:  Modelsim  Xilinx ISE