VLSI Architectures and Hardware Implementation of Ultra Low-Latency and Area-Efficient Pietra-Ricci Index Detector for Spectrum Sensing
VLSI Architectures and Hardware Implementation of Ultra Low-Latency and Area-Efficient Pietra-Ricci Index Detector for Spectrum Sensing
Abstract:
The Pietra-Ricci index detector (PRIDe) has been recently proposed as one of the simplest techniques for centralized, data-fusion cooperative spectrum sensing, attaining robustness against time-varying signal and noise levels, constant false alarm rate, and high detection power. In this paper, we propose the design and implementation of the PRIDe detector, targeting field programmable gate array (FPGA) and application-specific integrated circuit (ASIC) solutions. Novel approaches are proposed for computing the PRIDe’s test statistic, including the absolute value of complex quantities, the complex multiplier-accumulator, and the spectrum occupancy decision. The absolute value operation, which is critical to the PRIDe test statistic computational cost, applies the coordinate rotation digital computer (CORDIC) algorithm as a low latency and resource-efficient option. Register transfer level (RTL) and Monte Carlo simulations show that the resulting ultra-low latency PRIDe detector architectures attain no performance loss with respect to floating-point simulations. One of the two proposed ASIC design versions of the PRIDe sensor occupies 34.9% lower area compared to the most area-efficient sensor reported in literature, whereas the other one is 5.7× faster than the fastest state-of-the-art sensor. In a nutshell, the proposed detector architecture delivers the highest area and power efficiencies, considering the scaled values of area-time product (ATP) and power-delay product (PDP) metrics, in comparison to implementations reported to date.
” Thanks for Visit this project Pages – Register This Project and Buy soon with Novelty “
VLSI Architectures and Hardware Implementation of Ultra Low-Latency and Area-Efficient Pietra-Ricci Index Detector for Spectrum Sensing
