Ufuk Muncuk

Design Optimization and Implementation for RF Energy Harvesting Circuits

A new design for an energy harvesting device is proposed in this paper, which enables scavenging energy from radiofrequency (RF) electromagnetic waves. Compared to common alternative energy sources like solar and wind, RF harvesting has the least energy density. The existing state-of-the-art solutions are effective only over narrow frequency ranges, are limited in efficiency response, and require higher levels of input power. This paper has a twofold contribution. First, we propose a dual-stage energy harvesting circuit composed of a seven-stage and ten-stage design, the former being more receptive in the low input power regions, while the latter is more suitable for higher power range. Each stage here is a modified voltage multiplier, arranged in series and our design provides guidelines on component choice and precise selection of the crossover operational point for these two stages between the high (20 dBm) and low power (-20 dBm) extremities. Second, we fabricate our design on a printed circuit board to demonstrate how such a circuit can run a commercial Mica2 sensor mote, with accompanying simulations on both ideal and non-ideal conditions for identifying the upper bound on achievable efficiency. With a simple yet optimal dual-stage design, experiments and characterization plots reveal approximately 100% improvement over other existing designs in the power range of -20 to 7 dBm.

Range extension of passive wake-up radio systems through energy harvesting

Use of a passive wake-up radio can drastically increase the network lifetime in a sensor network by reducing or even completely eliminating unnecessary idle listening. A sensor node with a wake-up radio receiver (WuRx) can operate in an extremely low power sleep mode until it receives a trigger signal sent by a wake-up radio transmitter (WuTx). After receiving the trigger signal, the attached WuRx wakes up the sensor node to start the data communication. In this paper, we implement and compare the performance of three passive wake-up radio-based sensor nodes: 1) WISP-Mote, which is a sensor mote that employs an Intel WISP passive RFID tag as the WuRx; 2) EH-WISP-Mote, which combines a novel energy harvester with the WISP-Mote; and 3) REACH-Mote, which uses the energy harvester circuit combined with an ultra-low-power pulse generator to trigger the wake-up of the mote. Experimental results show that the wake-up range and wake-up delay for the EH-WISP-Mote are improved compared with the WISP-Mote, while providing the ability to perform both broadcast-based and ID-based wake-ups. On the other hand, the REACH-Mote, which can only provide broadcast-based wake-up, can achieve a much longer wake-up range than any known passive wake-up radio to date, achieving feasible wake-up at a range of up to 37 ft.

Multi-Path Model and Sensitivity Analysis for Galvanic Coupled Intra-Body Communication Through Layered Tissue

New medical procedures promise continuous patient monitoring and drug delivery through implanted sensors and actuators. When over the air wireless radio frequency (OTA-RF) links are used for intra-body implant communication, the network incurs heavy energy costs owing to absorption within the human tissue. With this motivation, we explore an alternate form of intra-body communication that relies on weak electrical signals, instead of OTA-RF. To demonstrate the feasibility of this new paradigm for enabling communication between sensors and actuators embedded within the tissue, or placed on the surface of the skin, we develop a rigorous analytical model based on galvanic coupling of low energy signals. The main contributions in this paper are: (i) developing a suite of analytical expressions for modeling the resulting communication channel for weak electrical signals in a three dimensional multi-layered tissue structure, (ii) validating and verifying the model through extensive finite element simulations, published measurements in existing literature, and experiments conducted with porcine tissue, (iii) designing the communication framework with safety considerations, and analyzing the influence of different network and hardware parameters such as transmission frequency and electrode placements. Our results reveal a close agreement between theory, simulation, literature and experimental findings, pointing to the suitability of the model for quick and accurate channel characterization and parameter estimation for networked and implanted sensors.

Battery-Free Identification Token for Touch Sensing Devices

This paper proposes the design and implementation of low-- energy tokens for smart interaction with capacitive touch-- enabled devices by associating the tokens identity with its contact, or touch. The proposed tokens design features two key novel technical components: (1) a through--touch--sensor low--energy communication method for token identification and (2) a touch--sensor energy harvesting technique. The communication mechanism involves the token transmitting its identity (ID) directly through the touch--sensor by artificially modifying the effective capacitance between the touch-- sensor and token surfaces. This approach consumes significantly lower energy compared to traditional electrical signal modulation approaches. By enabling the token to harvest energy from touch--screen sensors or touch--surfaces the token is rendered battery--free. Through experimental evaluations using a prototype implementation, the proposed design is shown to achieve at least 95% identification accuracy. It is also shown to consume less energy than competitive techniques (NFC P2P and Bluetooth Low--Energy) for communicating a short ID sequence. The adoption of this technology among users is evaluated through a user study on 12 subjects.

Topology optimization for galvanic coupled wireless intra-body communication

Implanted sensors and actuators in the human body promise in-situ health monitoring and rapid advancements in personalized medicine. We propose a new paradigm where such implants may communicate wirelessly through a technique called as galvanic coupling, which uses weak electrical signals and the conduction properties of body tissues. While galvanic coupling overcomes the problem of massive absorption of RF waves in the body, the unique intra-body channel raises several questions on the topology of the implants and the external (i.e., on skin) data collection nodes. This paper makes the first contributions towards (i) building an energy-efficient topology through optimal placement of data collection points/relays using measurement-driven tissue channel models, and (ii) balancing the energy consumption over the entire implant network so that the application needs are met. We achieve this via a two-phase iterative clustering algorithm for the implants and formulate an optimization problem that decides the position of external data-gathering points. Our theoretical results are validated via simulations and experimental studies on real tissues, with demonstrated increase in the network lifetime.

REACH 2 -Mote: A Range-Extending Passive Wake-Up Wireless Sensor Node

A wireless sensor network that employs passive radio wake-up of the sensor nodes can reduce the energy cost for unnecessary idle listening and communication overhead, extending the network lifetime. A passive wake-up radio is powered by the electromagnetic waves transmitted by a wake-up transmitter rather than a battery on the sensor node. However, this method of powering the wake-up radio results in a short wake-up range, which limits the performance of a passive wake-up radio sensor network. In this article, we describe our design of a passive wake-up radio sensor node—REACH2-Mote—using a high-efficiency, energy-harvesting module and a very low power wake-up circuit to achieve an extended wake-up range. We implemented REACH2-Mote in hardware and performed field tests to characterize its performance. The experimental results show that REACH2-Mote can achieve a wake-up range of 44 feet. We also modeled REACH2-Mote and evaluated its performance through simulations, comparing its performance to that of another passive wake-up radio approach, an active wake-up radio approach, and a conventional duty cycling approach. The simulation results show that REACH2-Mote can significantly extend the network lifetime while achieving high packet delivery rate and low latency.

Tissue safety analysis and duty cycle planning for galvanic coupled intra-body communication

Galvanic coupling is the enabler of closed-loop communication between implanted sensors and embedded actuating devices (such as drug injectors) by providing energy-efficient and reliable non-RF transmission through links formed within tissue. For safe deployment, it is critical to verify that the amount of heat generated within tissues during signal propagation stays within permissible bound. In this paper, we analyze the thermal distribution within tissues, for galvanic coupling-based communication for varying transmission power levels, number of collocated transmitters, and blood perfusion conditions using finite element based numerical simulation and skin-phantom based experiments. Our results confirm that tissue heating remains well below safe limit of 1 °C. Using the temperature dissipation profile, we derive the suitable transmission duty cycles, separation distances and number of concurrent sources that may co-exist without raising the tissue temperature. The proposed strategies provide upto four fold increase in bandwidth efficiency through concurrent transmissions, ensuring sufficient bandwidth for implant communications.

Software-defined Wireless Charging of Internet of Things using Distributed Beamforming: Demo Abstract

Smart homes will compose of multiple sensors that will sense, compute and transmit information to a central cloud, all of which are energy consuming tasks. We propose to demonstrate a software-defined solution for wirelessly charging these sensors using RF energy, thereby extending their lifetimes. In our demo, the actions of more than one energy transmitter (ET) are synchronized in phase and frequency in real time using periodic feedback from the target sensor, but without any common clock reference. The controller selects the optimal subset of ETs to satisfy the energy request from a given sensor, which cooperatively beamform RF energy towards that sensor. Our software-defined framework, implemented in Python, allows the central controller to automatically discover the installed sensors, obtain energy needs, and schedule charging tasks in an asynchronous and non-blocking manner that allows the network to scale. The demonstration includes advancements in design and fabrication of RF energy harvesting circuits that interface with the TI EZ430 sensors, implementation of a software-defined control and data plane, as well as a real-time distributed beamforming algorithm on USRP radios that results in a battery-free network of sensors.

CapBand: Battery-free Successive Capacitance Sensing Wristband for Hand Gesture Recognition

We present CapBand, a battery-free hand gesture recognition wearable in the form of a wristband. The key challenges in creating such a system are (1) to sense useful hand gestures at ultra-low power so that the device can be powered by the limited energy harvestable from the surrounding environment and (2) to make the system work reliably without requiring training every time a user puts on the wristband. We present successive capacitance sensing, an ultra-low power sensing technique, to capture small skin deformations due to muscle and tendon movements on the users wrist, which corresponds to specific groups of wrist muscles representing the gestures being performed. We build a wrist muscles-to-gesture model, based on which we develop a hand gesture classification method using both motion and static features. To eliminate the need for per-usage training, we propose a kernel-based on-wrist localization technique to detect the CapBands position on the users wrist. We prototype CapBand with a custom-designed capacitance sensor array on two flexible circuits driven by a custom-built electronic board, a heterogeneous material-made, deformable silicone band, and a custom-built energy harvesting and management module. Evaluations on 20 subjects show 95.0% accuracy of gesture recognition when recognizing 15 different hand gestures and 95.3% accuracy of on-wrist localization.