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This work presents an ultra-low power event driven wake-up receiver (WuRx) fabricated in a RF CMOS 130 nm process. The receiver consists of an off-chip lumped element matching network, an envelope detector, a decision circuit capable of detecting sub-mV baseband signal voltages and a clock source consuming 1.3 nW. This receiver has demonstrated a sensitivity of −72 dBm while consuming a total of 8...
A 507nW self-powered SoC is demonstrated for ultra-low power (ULP) internet-of-things (IoT) applications. The SoC includes ULP system-in-package (SiP) interfaces that enable its harmonious integration with a radio transmitter (TX) and a non-volatile memory (NVM). The energy harvesting platform power manager (EH-PPM) powers the SoC as well as off-chip components and is optimized for low quiescent power...
Standby-sparing systems where one processor is used as primary while another one is deployed as spare have been used to provide high reliability to real-time embedded systems. To reduce the energy consumption, the primary uses DVFS while the spare employs DPM to postpone the backup tasks. In this paper, we re-visit the problem for heterogeneous multicore systems that include both high-performance...
This paper presents an Ultra-Low Leakage (ULL) 55nm Deeply Depleted Channel (DDC) process technology for low power Internet of Things (IoT) applications. The DDC ULL devices provide 67% reduction in threshold (VT) variation due to Random Dopant Fluctuation (RDF). Circuit techniques such as subthreshold operation and reverse body biasing (RBB) are co-designed with the technology to maximize the energy/power...
This paper presents an Ultra-Low Leakage (ULL) 55nm Deeply Depleted Channel (DDC) process technology for low power Internet of Things (IoT) applications. The DDC ULL devices provide 67% reduction in threshold (VT) variation due to Random Dopant Fluctuation (RDF). Circuit techniques such as subthreshold operation and reverse body biasing (RBB) are co-designed with the technology to maximize the energy/power...
This paper compares the impact of power supply variation on the performance of register-based and latch-based digital circuits. A 32-tap, 16-bit FIR filter is fabricated using both flip-flops and latches in a 130nm CMOS process. Measurements show 25–37% improvement in energy-efficiency for the latch-based implementation operating below 0.6V subject to 44–120mV, 1 kHz peak-peak VDD ripple. This paper...
This paper presents an implementation of a 16-bit MSP430 processor for ultra-low-power (ULP) systems catering to battery-less wireless sensor nodes, biomedical, and other IoT applications. Implemented in a custom extremely low power (xLP) 90nm FDSOI process, the processor consumes 1.3µW operating at 0.4V while executing a peak detection algorithm at 250 kHz. It supports the standard MSP430 instruction...
The vision of smart grids lie in large scale, distributed electrical power systems, equipped with communication and information technologies for automated and sustainable electricity production and distribution. Smart grids require communication with individual energy consumers for enabling energy providers to create a control-feedback loop using time-dependent pricing. Emerging broadband wireless...
A 1 trillion node internet of things (IoT) will require sensing platforms that support numerous applications using power harvesting to avoid the cost and scalability challenge of battery replacement in such large numbers. Previous SoCs achieve good integration and even energy harvesting [1][2][3], but they limit supported applications, need higher end-to-end harvesting efficiency, and require duty-cycling...
We study a novel scheme to manage networks with heterogeneous traffic efficiently under resource crunch. We consider different types of revenue models for different service classes. We show that degradation of services and redistribution of resources while satisfying QoS under resource crunch can improve both availability and revenue.
Smart grids envision large scale, distributed electrical power systems, equipped with communication and information technologies for automated, efficient, reliable and sustainable electricity production and distribution. Advanced communication technologies have the potential to significantly enhance the overall efficiency of smart power grids. In this paper we propose and analyze the use of LTE multicast...
Smart Grids — intelligent electricity grids enable two way communication between utility and its customers. Smart Grid technologies are being deployed throughout the world, to make the traditional grids more reliable, secure and environmentally sustainable. Consumers are the important domain in a Smart Grid, participating in real-time demand response programs. To ensure the qualities of a Smart Grid...
Linear Sampling Method (LSM) is a reliable, simple and effective method for finding the shape and location of the unknown targets. It achieves the task by focusing the scattered fields from the objects to a monopole radiation. But, the resolution capabilities of LSM are ineffective when the scatterers are closely placed compare to the wavelength of microwave fields. In this paper we show that, this...
The 3rd Generation Partnership Project — Long Term Evolution (3GPP-LTE) is the best choice for multimedia data transmission in demanding situation. The 3GPP LTE provides high data transmission rate between the User Equipment (UE) and Evolved Node B (eNB) with lower latency and better throughput. However, with the advancement and increasing traffic of data load, it is necessary to have data scheduling...
Traffic lights, which may also be known as stoplights, traffic lamps, traffic signals, stop-and-go lights robots or semaphore are signaling devices positioned at road intersections, pedestrian crossings and other locations to control competing flows of traffic[1]. Traffic lights assign the right of way to road users by the use of lights in standard colors. Traffic light controller establishes a set...
Fault diagnosis in reciprocating air compressors is essential for continuous monitoring of their performance and thereby ensuring quality output. Support Vector Machines (SVMs) are machine learning tools based on structural risk minimization principle and have the advantageous characteristic of good generalization. For this reason, four well-known and widely used SVM based methods, one-against-one...
In this study, Support Vector Machine (SVM) based methods have been used to classify the electrocardiogram (ECG) arrhythmias. Among various existing SVM methods, three well-known and widely used algorithms one-against-one, one-against-all, and fuzzy decision function are used here to distinguish between the presence and absence of cardiac arrhythmia and classifying them into one of the arrhythmia...
This paper proposes Improved Mountain Clustering version-2 (IMC-2) based medical image segmentation. The proposed technique is a more powerful approach for medical image based diagnosing diseases like brain tumor, tooth decay, lung cancer, tuberculosis etc. The IMC-2 based medical image segmentation approach has been applied on various categories of images including MRI images, dental X-rays, chest...
We propose a new channel rate and queue state adaptive time resource allocation heuristic for the base stations in a multiuser wireless access scenario. Motivation of the scheme is derived through the effective capacity concept. Our proposed strategy accounts for fairness and quality-of-service (QoS) of the system on per frame basis. Our results show that the proposed scheme benefits the users with...
All wireless systems require the precise timing synchronization to satisfy the higher quality of service (QoS) requirements. Particularly, timing synchronization between base stations (BSs) during soft handover is required to increase the diversity gain of soft handover. Current timing synchronization protocol (e.g. IEEE1588, GPS) updates the synchronization at fixed time duration and it causes the...
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