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A parallel complex divider architecture based on DCD iterations for computing complex division in MVDR beamformer

机译:基于DCD迭代的并行复数除法器架构,用于计算MVDR波束形成器中的复数除法

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This paper presents a hardware architecture using mixed pipeline and parallel processing for complex division based on dichotomous coordinate descent (DCD) iterations. The objective of the proposed work is to achieve low-latency and resource optimized complex divider architecture in adaptive weight computation stage of minimum variance distortionless response (MVDR) algorithm. In this work, computation of complex division is modeled as a 2x2 linear equation solution problem and the DCD algorithm allows linear systems of equations to be solved with high degree of computational efficiency. The operations in the existing DCD algorithm are suitably parallel pipelined and the performance is optimized to 2 clock cycles per iteration. To improve the degree of parallelism, a parallel column vector read architecture is devised. The proposed work is implemented on the field programmable gate array (FPGA) platform and the results are compared with state-of-art literature. It concludes that the proposed architecture is suitable for complex division in adaptive weight computation stage of MVDR beamformer. We demonstrate the performance of the proposed architecture for MVDR beamformer employed in medical ultrasound imaging applications.
机译:本文提出了一种基于二分坐标下降(DCD)迭代的,使用混合流水线和并行处理进行复杂划分的硬件体系结构。拟议工作的目标是在最小方差无失真响应(MVDR)算法的自适应权重计算阶段实现低延迟和资源优化的复杂除法器架构。在这项工作中,将复数除法的计算建模为2x2线性方程解问题,并且DCD算法允许以较高的计算效率来求解线性方程组。现有DCD算法中的操作适当地并行流水线化,并且性能被优化为每次迭代2个时钟周期。为了提高并行度,设计了并行列向量读取体系结构。拟议的工作在现场可编程门阵列(FPGA)平台上实现,并将结果与​​最新文献进行了比较。结论表明,所提出的架构适用于MVDR波束形成器的自适应权重计算阶段的复杂划分。我们演示了用于医疗超声成像应用中的MVDR波束形成器的建议架构的性能。

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