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Home All Updates (3681) VLSI PROJECTS ABSTRA
VLSI PROJECTS ABSTRA
VLSI PROJECTS ABSTRACT 2016-2017: HARDWARE AND ENERGY-EFFICIENT STOCHASTIC LU DECOMPOSITION SCHEME FOR MIMO RECEIVERS ABSTRACT: In this paper, we design a hardware and energy-efficient stochastic lower–upper decomposition (LUD) scheme for multiple-input multiple-output receivers. By employing stochastic computation, the complex arithmetic operations in LUD can be performed with simple logic gates. With proposed dual partition computation method, the stochastic multiplier and divider exhibit high computation accuracy with relative short length stochastic stream. The proposed architecture of this paper analysis the logic size, area and power consumption using Xilinx 14.2. EXISTING SYSTEM: Generally, there are two main approaches for the matrix decomposition method in MIMO systems: 1) QR decomposition and 2) lower–upper decomposition (LUD). QR decomposition algorithm, which transfers a matrix into an orthogonal matrix and an upper triangular matrix, is widely employed in the path-search-based MIMO-detection algorithm. In the other aspect, LUD algorithm factorizes a matrix into a lower triangular matrix and an upper triangular matrix. LUD has the same function as QR decomposition, which serves for a path search-based MIMO detection. Moreover, LUD is an indispensable processing in the zero-force (ZF) and the minimum mean square error (MMSE)-based MIMO system. In this paper, we focus on the implementation of LUD algorithm. PROPOSED SYSTEM: Stochastic computation is a powerful tool for signal processing systems. Information is represented by the statistical mean of a random bit stream. In this paper, we apply a signed stochastic stream to represent the FP signal in two’s complement system (TCS). As shown in Fig. 1(a), the absolute value of x is compared with a positive random number with uniform distributions. A binary bit stream X is obtained at the output of the comparator with the value bit a(X), while the signed bit of the TCS signals x is outputted directly as a stream s(X). For example, in order to represent a value of −0.6, six out of ten bits are 1 in a(X), and the bits in the signed stream s(X) are 1. ADVANTAGES: • high hardware efficiency • high power efficiency DISADVANTAGES • Low hardware efficiency • Low power efficiency SOFTWARE IMPLEMENTATION • Modelsim • Xilinx ISE
  • 2016-07-15T08:21:21

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