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In this work, we demonstrate that it is possible to read UHF RFID tags without a carrier. Specifically, we introduce an alternative reader design that does not emit a carrier and allows reading RFID tags intended for conventional carrier-based systems. While traditional RFID tags modulate a carrier, it is important to note that a modulation circuit used for backscatter also modulates the inherent noise of the tag circuitry, including the Johnson noise, irrespective of whether a carrier is present or not. Our Modulated Noise Communication (MNC) approach leverages recent work on Modulated Johnson Noise (MJN) and can be read by an alternative RFID reader design that enables simpler, more accessible RFID readings than a conventional backscatter reader by eliminating self-jamming obstructions. MNC is shown to support wireless transmission of data packets between 2 cm to 10 cm of separation between a standard UHF RFID tag and the proposed alternative reader for data rates of 1 bps and 2 bps. 

New methods of passive wireless communication are presented where no RF carrier is needed. Instead, data is wirelessly transmitted by modulating noise sources, from those found in electronic components to extraterrestrial noise sources. Any pair of noise sources with a difference in noise temperature can be used to enable communication. We discuss using the Earth, the Moon, the Sun, the coldness of space, and Active Cold Load circuits as sources of thermal contrast. We present Cosmic Backscatter and demonstrate that wireless connectivity can be enabled by switching an antenna connection between the "cold" Sky and a "hot" 50Ω resistor. Furthermore, we present Noise Suppression Communication, where data is transmitted by controlling an Active Cold Load to selectively reduce emitted noise below ambient temperature levels. 

This paper presents a step-up DC-DC converter that uses a stepwise gate-drive technique to reduce the power FET gate-drive energy by 82%, allowing positive efficiency down to an input voltage of ±0.5 mV—the lowest input voltage ever achieved for a DC-DC converter as far as we know. Below ±0.5 mV the converter automatically hibernates, reducing quiescent power consumption to just 255 pW. The converter has an efficiency of 63% at ±1 mV and 84% at ±6 mV. The input impedance is programmable from 1 Ω to 600 Ω to achieve maximum power extraction. A novel delay line circuit controls the stepwise gatedrive timing, programmable input impedance, and hibernation behavior. Bipolar input voltage is supported by using a flyback converter topology with two secondary windings. A generated power good signal enables the load when the output voltage has charged above 2.7 V and disables when the output voltage has discharged below 2.5 V. The DC-DC converter was used in a thermoelectric energy harvesting system that effectively harvests energy from small indoor temperature fluctuations of less than 1°C. Also, an analytical model with unprecedented accuracy of the stepwise gate-drive energy is presented. 

We present the design of a passive wireless communication method that does not rely on ambient or generated RF sources. Instead, the method modulates the Johnson (thermal) noise of a resistor to transmit information bits wirelessly. By selectively connecting or disconnecting a matched resistor to an antenna, the system can achieve data rates of up to 26 bps and distances of up to 7.3 m. This communication method operates at very low power, similar to that of an RFID tag, with the advantage of not requiring a preexisting RF signal to reflect. 

Connected devices are becoming more ubiquitous, but powering them remains a challenge. The Wireless Identification and Sensing Platform (WISP) is a fully programmable device capable of energy harvesting and backscatter communication. It can accommodate a variety of sensing modalities and operate without batteries or a wired power supply, making it a suitable device for ubiquitous computing. A new version of WISP is presented. WISP-6.0 is designed to be lowpower, modular, and enable dual energy harvesting from sources like a solar panel. Additionally, an upgraded cross-platform host application is built using the latest web technologies. Compared to its predecessor, WISP-5.1, WISP-6.0 consumes 13.62% and 6.29% less power in active accelerometer and active acknowledgment modes respectively. Furthermore, WISP-6.0 is better able to harvest RF energy collected from its antenna, with the greatest improvements at higher input powers. 

Brain–computer interfaces (BCIs) are neural prosthetics that enable closed-loop electrophysiology procedures. These devices are currently used in fundamental neurophysiology research, and they are moving toward clinical viability for neural rehabilitation. State-of-the-art BCI experiments have often been performed using tethered (wired) setups in controlled laboratory settings. Wired tethers simplify power and data interfaces but restrict the duration and types of experiments that are possible, particularly for the study of sensorimotor pathways in freely behaving animals. To eliminate tethers, there is significant ongoing research to develop fully wireless BCIs having wireless uplink of broadband neural recordings and wireless recharging for long-duration deployment, but significant challenges persist. BCIs must deliver complex functionality while complying with tightly coupled constraints in size, weight, power, noise, and biocompatibility. In this article, we provide an overview of recent progress in wireless BCIs and a detailed presentation of two emerging technologies that are advancing the state of the art: ultralow-power wireless backscatter communication and adaptive inductive resonant (AIR) wireless power transfer (WPT). 

Realizing the vision of ubiquitous battery-free sensing has proven to be challenging, mainly due to the practical energy and range limitations of current wireless communication systems. To address this, we design the first wide-area and scalable backscatter network with multiple receivers (RX) and transmitters (TX) base units to communicate with battery-free sensor nodes. Our system circumvents the inherent limitations of backscatter systems--including the limited coverage area, frequency-dependent operability, and sensor node limitations in handling network tasks--by introducing several coordination techniques between the base units starting from a single RX-TX pair to networks with many RX and TX units. We build low-cost RX and TX base units and battery-free sensor nodes with multiple sensing modalities and evaluate the performance of the MultiScatter system in various deployments. Our evaluation shows that we can successfully communicate with battery-free sensor nodes across 23400 square feet of a two-floor educational complex using 5 RX and 20 TX units, costing $569. Also, we show that the aggregated throughput of the backscatter network increases linearly as the number of RX units and the network coverage grows. 

Occupancy detection systems are commonly equipped with high quality cameras and a processor with high computational power to run detection algorithms. This paper presents a human occupancy detection system that uses battery-free cameras and a deep learning model implemented on a low-cost hub to detect human presence. Our low-resolution camera harvests energy from ambient light and transmits data to the hub using backscatter communication. We implement the state-of-the-art YOLOv5 network detection algorithm that offers high detection accuracy and fast inferencing speed on a Raspberry Pi 4 Model B. We achieve an inferencing speed of ∼100ms per image and an overall detection accuracy of >90% with only 2GB CPU RAM on the Raspberry Pi. In the experimental results, we also demonstrate that the detection is robust to noise, illuminance, occlusion, and angle of depression. 

Despite significant research in backscatter communication over the past decade, key technical open problems remain underexplored. Here, we first systematically lay out the design space for backscatter networking and identify applications that make backscatter an attractive communication primitive. We then identify 10 research problems that remain to be solved in backscatter networking. These open problems span across the network stack to include circuits, embedded systems, physical layer, MAC and network protocols as well as applications. We believe that addressing these problems can help deliver on backscatter's promise of low-power ubiquitous connectivity.