Architecture of an efficient dual band 1.8/2.5 GHz rectenna for RF energy harvesting

This paper presents a highly efficient rectenna of RF energy harvesting systems operating at 1.8 GHz and 2.5 GHz bands for battery-less sensor application. The antenna is designed by CST-MWS. The Schottky diode used for rectifying circuit is HSMS 286B in which designed by Agilent ADS. The key finding of the paper is that the simulated DC output voltage of the rectenna is 1.35 V for low input power of -25 dBm at a high resistance load of 1M Ω. Correspondingly, the RF-DC conversion efficiency of the rectification process is 59.51% and 45.75% at 1.8 GHz and 2.5 GHz, which are high efficiency and much better compared to literature respectively. The rectenna is capable to produce 1.8 V from an input power of -20 dBm. Thus, the proposed RF energy harvesting system offers a promising solution designed for efficient functionality at a low power level of RF energy in the dual band

Compact rectifier circuit design for harvesting gsm/900 ambient energy

In this paper, a compact rectifier, capable of harvesting ambient radio frequency (RF) power is proposed. The total size of the rectifier is 45.4 mm x 7.8 mm x 1.6 mm, designed on FR-4 substrate using a single-stage voltage multiplier at 900 MHz. GSM/900 is among the favorable RF Energy Harvesting (RFEH) energy sources that span over a wide range with minimal path loss and high input power. The proposed RFEH rectifier achieves measured and simulated RF-to-dc (RF to direct current) power conversion efficiency (PCE) of 43.6% and 44.3% for 0 dBm input power, respectively. Additionally, the rectifier attained 3.1 V DC output voltage across 2 k omega load terminal for 14 dBm and is capable of sensing low input power at -20 dBm. The work presents a compact rectifier to harvest RF energy at 900 MHz, making it a good candidate for low powered wireless communication systems as compares to the other state of the art rectifier

A Comprehensive Survey on RF Energy Harvesting: Applications and Performance Determinants

\ua9 2022 by the authors. Licensee MDPI, Basel, Switzerland.There has been an explosion in research focused on Internet of Things (IoT) devices in recent years, with a broad range of use cases in different domains ranging from industrial automation to business analytics. Being battery-powered, these small devices are expected to last for extended periods (i.e., in some instances up to tens of years) to ensure network longevity and data streams with the required temporal and spatial granularity. It becomes even more critical when IoT devices are installed within a harsh environment where battery replacement/charging is both costly and labour intensive. Recent developments in the energy harvesting paradigm have significantly contributed towards mitigating this critical energy issue by incorporating the renewable energy potentially available within any environment in which a sensor network is deployed. Radio Frequency (RF) energy harvesting is one of the promising approaches being investigated in the research community to address this challenge, conducted by harvesting energy from the incident radio waves from both ambient and dedicated radio sources. A limited number of studies are available covering the state of the art related to specific research topics in this space, but there is a gap in the consolidation of domain knowledge associated with the factors influencing the performance of RF power harvesting systems. Moreover, a number of topics and research challenges affecting the performance of RF harvesting systems are still unreported, which deserve special attention. To this end, this article starts by providing an overview of the different application domains of RF power harvesting outlining their performance requirements and summarizing the RF power harvesting techniques with their associated power densities. It then comprehensively surveys the available literature on the horizons that affect the performance of RF energy harvesting, taking into account the evaluation metrics, power propagation models, rectenna architectures, and MAC protocols for RF energy harvesting. Finally, it summarizes the available literature associated with RF powered networks and highlights the limitations, challenges, and future research directions by synthesizing the research efforts in the field of RF energy harvesting to progress research in this area

Recent Advances in Antenna Design for 5G Heterogeneous Networks

The aim of this book is to highlight up to date exploited technologies and approaches in terms of antenna designs and requirements. In this regard, this book targets a broad range of subjects, including the microstrip antenna and the dipole and printed monopole antenna. The varieties of antenna designs, along with several different approaches to improve their overall performance, have given this book a great value, in which makes this book is deemed as a good reference for practicing engineers and under/postgraduate students working in this field. The key technology trends in antenna design as part of the mobile communication evolution have mainly focused on multiband, wideband, and MIMO antennas, and all have been clearly presented, studied and implemented within this book. The forthcoming 5G systems consider a truly mobile multimedia platform that constitutes a converged networking arena that not only includes legacy heterogeneous mobile networks but advanced radio interfaces and the possibility to operate at mm wave frequencies to capitalize on the large swathes of available bandwidth. This provides the impetus for a new breed of antenna design that, in principle, should be multimode in nature, energy efficient, and, above all, able to operate at the mm wave band, placing new design drivers on the antenna design. Thus, this book proposes to investigate advanced 5G antennas for heterogeneous applications that can operate in the range of 5G spectrums and to meet the essential requirements of 5G systems such as low latency, large bandwidth, and high gains and efficiencies

The Machine that Lives Forever

Design an intelligent micromachine that can self-power and sustain from environmental energy scavenging to achieve an autonomous device that can communicate at will with peers indefinitely. Explore sleep/wake hibernation strategies coupled with food scavenging off-grid traits to identify the tightest work to sleep efficiency schedule, incorporating adaptive reconfiguration to manage significant environmental impacts. Capture, store and manage background radiations and stray RF signals to feed on in a continued effort to make intelligent survival decisions and oversee management protocols. Ensure that every micro Watt of usable energy gets extracted from every part of the harvest and then forward-scheduled it for productive use. Finally, employ natures tricks and experience to introduce essential personality traits, pursuing maximising survival numbers and increasing dispersal target area sizes of large self-sufficient wireless sensor deployments. This research intends to provide a closely coupled software-hardware foundation that aids implementers in intelligently harnessing and using tiny amounts of ambient energy in a highly autonomous way. This platform then continues on to explore ways of maximising the efficient usage of the harvested energy using various hibernation/wake strategies and then making objective comparisons with proposed intelligent energy management protocols. Finally, the protocol extends to enable the device to manage its personal survival possibilities so the devices can use an evolutional personality-based approach to deal with the unknown environmental situations they will encounter. This work examines a machine that can self-power and sustain from environmental energy scavenging with the aim to live forever. Living forever implies a brain (microcontroller) that can manage energy and budget for continuous faculty. With these objectives, sleep/wake/hibernation and scavenging strategies are examined to efficiently schedule resources within a transient environment. Example harvesting includes induced and background radiation. Intelligent, biologically-inspired strategies are adopted in forward-scheduling strategies given temporal energy relative to the machine’s function (the Walton)