FPGA Based Scalable Fixed Point QRD Core Using Dynamic Partial Reconfiguration

G. Prabhu, Bibin Johnson, J. S. Rani
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引用次数: 10

Abstract

This work presents an FPGA based scalable fixed point QRD architecture based on Givens Rotation algorithm.The proposed QRD core utilizes an efficient pipelined and unfolded 2D MAC based systolic array architecture with dynamic partial reconfiguration(DPR) capability. An improved LUT based Newton-Raphson method is proposed for finding square root and inverse square root which helps in reducing the area by 71% and latency by 50%, while operating at a frequency 49% higher than the existing boundary cell architectures. The scalability of the QRD core is achieved using DPR which results in reduction in dynamic power and area utilization as compared to a static implementation. The proposed architecture is implemented on Xilinx Virtex-6 FPGA for any real matrices of size m × n where, 4 ≤ n ≤ 8 and m ≥ n by dynamically inserting or removing the partial modules. The evaluation results shows reduction in latency, area and power as compared to CORDIC based architectures. The proposed scalable QRD core is used for implementing a high performance adaptive equalizer(QRD-RLS Algorithm) used in mobile receiver's and the evaluation is done by transmitting BPSK symbols in the training mode.
基于FPGA的动态局部重构可扩展定点QRD核心
本文提出了一种基于Givens旋转算法的FPGA可扩展定点QRD架构。所提出的QRD核心采用了一种高效的流水线和展开的基于二维MAC的收缩阵列架构,具有动态部分重构(DPR)能力。提出了一种改进的基于LUT的求平方根和反平方根的Newton-Raphson方法,该方法有助于减少71%的面积和50%的延迟,同时工作频率比现有的边界单元结构高49%。QRD核心的可扩展性是使用DPR实现的,与静态实现相比,DPR降低了动态功率和面积利用率。该架构在Xilinx Virtex-6 FPGA上通过动态插入或移除部分模块,实现了任意大小为m × n且4≤n≤8且m≥n的实矩阵。评估结果显示,与基于CORDIC的架构相比,延迟、面积和功耗都有所降低。提出的可扩展QRD核用于实现移动接收机的高性能自适应均衡器(QRD- rls算法),并在训练模式下通过发送BPSK符号来进行评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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