Joint Early Stopping Criterions for Protograph LDPC Codes-Based JSCC System in Images Transmission

In this paper, a joint early stopping criterion based on cross entropy (CE), named joint CE criterion, is presented for double-protograph low-density parity-check (DP-LDPC) codes-based joint source-channel coding (JSCC) systems in images transmission to reduce the decoding complexity and decrease the decoding delay. The proposed early stopping criterion adopts the CE from the output likelihood ratios (LLRs) of the joint decoder. Moreover, a special phenomenon named asymmetry oscillation-like convergence (AOLC) in the changing process of CE is uncovered in the source decoder and channel decoder of this system meanwhile, and the proposed joint CE criterion can reduce the impact from the AOLC phenomenon. Comparing to the counterparts, the results show that the joint CE criterion can perform well in the decoding complexity and decoding latency in the low–moderate signal-to-noise ratio (SNR) region and achieve performance improvement in the high SNR region with appropriate parameters, which also demonstrates that this system with joint CE is a low-latency and low-power system.

Artificial Neural Networks Applied to Power Management in Low Power Microprocessors

Computer systems that operate in remote locations such as satellites, remote weather stations and autonomous robots are highly limited in the availability of energy for their operation. This work aims to employ artificial intelligence algorithms in energy management in order to obtain the maximum energy yield and the prediction of energy availability to the system. The work presents the main types of algorithms used in artificial intelligence and presents the creation of a prototype that will operate as a low power system powered by batteries and a small solar plate, the prototype will perform inferences on the LSTM neural network algorithm in order to predict the future availability of energy, consequently the management system will carry out the energy distribution in order to obtain the maximum operation of the prototype without total discharge of the batteries. So that the artificial intelligence system could be embedded in the prototype, the TensorFlow Lite framework was used, which allows the inference to be carried out in devices with low consumption and limited processing power.

TEI-DTA: Optimizing a Vehicular Sensor Network Operating with Ultra-Low Power System-on-Chips

In the era of the Internet of Things (IoT), the interest and demand for embedded systems have been explosively increasing. In particular, vehicular sensor networks are one of the fields where IoT-oriented embedded devices (also known as IoT devices) are being actively used. These IoT devices are widely deployed in and out of the vehicle to check vehicle conditions, prevent accidents, and support autonomous driving, forming a vehicular sensor network. In particular, such sensor networks mainly consist of third-party devices that operate independently of the vehicle and run on their own batteries. After all, like all battery-powered embedded devices, the IoT devices for the vehicular sensor network also suffer from limited power sources, and thus research on how to design/operate them energy-efficiently is drawing attention from both academia and industry. This paper notes that the vehicular sensor network may be the best application for ultra-low power system on-chips (ULP SoCs). The ULP SoCs are mainly designed based on ultra-low voltage operating (ULV) circuits, and this paper aims to realize the energy-optimized driving of the network by applying state of the art (SoA) low-power techniques exploiting the unique characteristics of ULV circuits to the IoT devices in the vehicular sensor network. To this end, this paper proposes an optimal task assignment algorithm that can achieve the best energy-efficient drive of the target network by fully utilizing the SoA low power techniques for ULV circuits. Along with a detailed description of the proposed algorithm, this paper demonstrates the effectiveness of the proposed method by providing an in-depth evaluation process and experimental results for the proposed algorithm.

DECODING TECHNIQUE FOR LOW POWER DESIGN IN XILINX

This research paper is a survey of the current status of research and practice in various disciplines of low power VLSI developments. The paper briefly discusses the rationale of the contemporary, and concentrates on low power design, it presents the metrics and techniques that are used to access the merits of the assorted proposed for the improved energy efficiency. Power dissipation [1], [5] has become an important consideration in terms of performance and scope for VLSI chip design. The research paper describes the decoding strategies, methodology, and techniques for low power system design. Here also we have proposed the decoding technique and compared with silent coding to scale back the transition state and conserved the power which is additionally described during this research. KEYWORDS—Power minimization, decoding technique, silent coding.

Design and Development of Non-Isolated Modified SEPIC DC-DC Converter Topology for High-Step-Up Applications: Investigation and Hardware Implementation

A new non-isolated modified SEPIC front-end dc-dc converter for the low power system is proposed in this paper, and this converter is the next level of the traditional SEPIC converter with additional devices, such as two diodes and splitting of the output capacitor into two equal parts. The circuit topology proposed in this paper is formulated by combining the boost structure with the traditional SEPIC converter. Therefore, the proposed converter has the benefit of the SEPIC converter, such as continuous input current. The proposed circuit structure also improves the features, such as high voltage gain and high conversion efficiency. The converter comprises one MOSFET switch, one coupled inductor, three diodes, and two capacitors, including the output capacitor. The converter effectively recovers the leakage energy of the coupled inductor through the passive clamp circuit. The operation of the proposed converter is explained in continuous conduction mode (CCM) and discontinuous conduction mode (DCM). The required voltage gain of the converter can be acquired by adjusting the coupled inductor turn’s ratio along with the additional devices at less duty cycle of the switch. The simulation of the proposed converter under CCM is carried out, and an experimental prototype of 100 W, 25 V/200 V is made, and the experimental outcomes are presented to validate the theoretical discussions of the proposed converter. The operating performance of the proposed converter is compared with the converters discussed in the literature. The proposed converter can be extended by connecting voltage multiplier (VM) cell circuits to get the ultra-high voltage gain.

Design and Development of IOT based Low Power Consumption in Employee Meeting Rooms

In this paper, We design and implement IOT based low power system that can be used in employee meeting rooms. The design is based on number of employees entering and leaving the room and automates room AC, lights and room freshners using relay device. The system designed counts number of employees entering the room using IR device and updates the number using counter and automates electrical appliances of the room and when leaving automatically switches off the devices. The power consumed is updated using ESP 8266 in the cloud called thing speak where the data can be evaluated and analyzed per day and per month. The system has 20*4 LCD which displays the complete details of the employees and electrical appliances. The working of the system starts with the entering of an employee in the room, the buzzer beeps and LED turns on. Arduino Mega is used as a central processor that controls all the appliances. The code is written in C and simulation is done using Proteus ISIS. Finally, the implemented system shows the energy consumption per day and per month and a detailed comparative analysis is done with and without connecting the system which shows a better saving of energy in the employee room. The methodology adapted for our work is V-methodology.