Noise Analysis in VLC Optical Link based Discrette OP-AMP Trans-impedance Amplifier (TIA)

To design Visible Light Communication (VLC) system, there are several requirements that needs to be met. One of the requirements is an active component selection (e.g. Op Amp). As an ideal communication system, VLC system has to be able to provides wide bandwidth access with minimum noise. The Transimpedance amplifiers (TIAs) is one of main components in optical system which is placed in the first stage of receiver system. It is used to convert the current output from photodiode to voltage. We have designed a 1 MHz fGBW TIA with low noise (in μVrms range). This paper aims to explain the design and implementation of TIA circuit with photovoltaic topology which cover empirical calculations and simulation of TIA’s bandwidth and its noise sources, i.e. resistor feedback noise, current noise, voltage noise and total noise based on RSS. The OP-AMP is chosen from Texas Instruments product, OPA 380, and photodiode is chosen from OSRAM, SFH213, then simulated by TINA-TI SPICE® software. The noise in TIA circuit is analyzed clearly. The developed kit is ready to be implemented in VLC system

Noise and Bandwidth Consideration in Designing Op-Amp Based Transimpedance Amplifier for VLC

In a visible light communication (VLC) system, there are many modules involved. One of the important modules is Transimpedance Amplifier (TIA) that resides in the analog front-end receiver (Rx-AFE). TIA is responsible for performing signal conversion from current signal, which is provided from the photodiode (PD) to voltage signal. It is the reason why the TIA should be operating in low noise condition and wide bandwidth of frequency. These will enable a flexible coverage of the VLC system in performing its signal processing. Hence, in this research, we provide considerations of the noise and frequency bandwidth analysis in designing TIA to cope with the required design specification of a VLC system

Prominent edge detection with deep metric expression and multi-scale features

Abstract(#br)Edge detection is one of today’s hottest computer vision issues with widely applications. It is beneficial for improving the capability of many vision systems, such as semantic segmentation, salient object detection and object recognition. Deep convolution neural networks (CNNs) recently have been employed to extract robust features, and have achieved a definite improvement. However, there is still a long run to study this hotspot with the main reason that CNNs-based approaches may cause the edges thicker. To address this problem, a novel semantic edge detection algorithm using multi-scale features is proposed. Our model is deep symmetrical metric learning network, which includes 3 key parts. Firstly, the deep detail layer, as a preprocessing layer and a guide module, is..

On Minimal Second-order IIR Bandpass Filters with Constrained Poles and Zeros

In this paper, several forms of infinite impulse response (IIR) bandpass filters with constrained poles and zeros are presented and compared. The comparison includes the filter structure, the frequency ranges and a number of controlled parameters that affect computational efforts. Using the relationship between bandpass and notch filters, the two presented filters were originally developed for notch filters. This paper also proposes a second-order IIR bandpass filter structure that constrains poles and zeros and can be used as a  minimal parameter adaptive digital second-order filter. The proposed filter has a wider frequency range and more flexibility in the range values of the adaptation parameters

Variable learning rate EASI-based adaptive blind source separation in situation of nonstationary source and linear time-varying systems

In the case of multiple nonstationary independent source signals and linear instantaneous time-varying mixing systems, it is difficult to adaptively separate the multiple source signals. Therefore, the adaptive blind source separation (BSS) problem is firstly formally expressed and compared with tradition BSS problem. Then, we propose an adaptive blind identification and separation method based on the variable learning rate equivariant adaptive source separation via independence (EASI) algorithm. Furthermore, we analyze the scope and conditions of variable-learning rate EASI algorithm. The adaptive BSS simulation results also show that the variable learning rate EASI algorithm provides better separation effect than the fixed learning rate EASI and recursive least-squares algorithms

High-performance AES-128 algorithm implementation by FPGA-based SoC for 5G communications

none4siIn this research work, a fast and lightweight AES-128 cypher based on the Xilinx ZCU102 FPGA board is presented, suitable for 5G communications. In particular, both encryption and decryption algorithms have been developed using a pipelined approach, so enabling the simultaneous processing of the rounds on multiple data packets at each clock cycle. Both the encryption and decryption systems support an operative frequency up to 220 MHz, reaching 28.16 Gbit/s maximum data throughput; besides, the encryption and decryption phases last both only ten clock periods. To guarantee the interoperability of the developed encryption/decryption system with the other sections of the 5G communication apparatus, synchronization and control signals have been integrated. The encryption system uses only 1631 CLBs, whereas the decryption one only 3464 CLBs, ascribable, mainly, to the Inverse Mix Columns step. The developed cypher shows higher efficiency (8.63 Mbps/slice) than similar solutions present in literature.openP.Visconti, R. Velazquez, S. Capoccia, R. de FazioVisconti, P.; Velazquez, R.; Capoccia, S.; de Fazio, R