Software Defined Radio (SDR) is the ubiquitous technology employed in Electronic Communication Systems. Widespread availability of multi-processor SoC technologies lead the way to replace the analog hardware blocks with software driven flexible heterogeneous computing blocks. One of the potential requirement of Software defined Radio/Receiver is assessment of spectrum occupancy over the specified frequency spectrum. The SDR has fast analog-to-digital converter (ADC) that digitizes the band limited RF or IF signals followed by Digital Down Converter (DDC) that optimizes the bandwidth (BW) and output data rate. In many applications, the signal of interest represents a small proportion of the input BW. Spectrum occupancy is estimated by converting time domain signals at the output of DDC to frequency domain and applying detection threshold on the spectrum. This is achieved through Fast Fourier Transform (FFT) technique. Active signals within the pass band are detected based on the estimated Noise riding threshold of the spectral data. In this paper, DDC and FFT blocks are designed for implementation on FPGA. Vivado 2018.1 version tool is used in the design and development of the firmware. Broad specifications are RF = 100 to 1000 MHz, Second IF = 75 MHz, instantaneous BW = 40 MHz, ADC sampling rate, f s = 100 MHz.
The objective of the conference is to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results on all aspects of Energy Conversion and Storage. It also provides a premier interdisciplinary platform for researchers, practitioners, and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of Energy Conversion and Storage.
Energy harvesting is a powerful technique to produce clean and renewable energy with better infrastructure improvement. The exhaustive review of recent progress and development in bio-mechanical energy harvesting (BMEH) techniques from human body is discussed in this manuscript. The BMEH from the human body is categorized into three parts, namely, piezoelectric energy harvesting (PEEH), triboelectric energy harvesting (TEEH), and Electro-magnetic Energy harvesting (EMEH). Each energy harvesting system is discussed with working principles with mathematical equations; each energy harvesting progress is discussed with a few work demonstrations. The applications of each energy harvesting from the recent research work are addressed in detail. The summary of each energy harvester from the human body or motion with advantages, limitations, performance metrics, current methods, and implemented human body parts are highlighted with Tabulation. The critical challenges/issues with possible solutions are also discussed.
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