NSF CAREER (4/15-3/20)

Project Description

IDEA: Integrated Data and Energy Access for Wireless Sensor Networks (April 2015 - March 2020)

  • Client:

    Project Sponsor- NSF
The proposed Integrated Data and Energy Access (IDEA) framework will help realize the promise of jointly powering and communicating with wireless sensors with the help of electromagnetic radio frequency (RF) waves. This research will result in a cross-layer protocol suite, modeling tools, and experimental systems that will be instrumental in building future RF energy harvesting networks for healthcare, wearable electronics, smart homes, and embedded implants with extended lifetimes. The controllable and predictable nature of RF energy and the lack of dependence on environmental conditions distinguish this form of energy harvesting over other renewable sources. IDEA will directly support national and institutional level energy-efficiency related program goals by reducing dependence on batteries and enhancing sustainability in networking. The project involves an integrated education plan involving demonstrations at public museums, pedagogical tools for K12 students, a summer school focused on RF energy harvesting, continuing education for industry personnel, along with dedicated outreach efforts to attract students from under-represented groups.

Current Personnel: 
Yousof Naderi
Ufuk Muncuk
Kubra Alemdar
Kunal Sankhe
Subhramoy Mohanti

Previous Personnel:
Raul Cid-Fuentes
Luiza Pelucio

Project Objectives:
  1. We will research methods for sharing the channel for the charging and data communication functions in the network, while addressing the challenges posed by phase variance and the constructive and destructive interference of energy signals in space.
  2. We will propose new routing metrics and protocols for creating energy paths, which will charge only selected sensors to ensure data delivery to the sink occurs timely over these pathways. It will yield concrete insights on the relationship between the number of ETs, their placement, the network lifetime, and the data communication capacity given the energy transfer requests within the network.
  3. We will answer fundamental questions on how much energy can be obtained through indoor ETs, as well as outdoors from the ambient RF environment in the TV band, leading to the creation of spatiol-temporal energy maps.
  4. We will transform the concept of RF harvesting sensors to a platform for network deployment through a testbed of software­-defined radio ETs and circuit designs for RF harvesting boards.

Key Outcomes and Research Results:

1. Software-Defined Wireless Energy Beamforming:
We developed and demonstrated a software-defined solution for wirelessly charging the sensors using RF energy. Here, the actions of more than one energy transmitter (ET) were synchronized in phase and frequency in realtime using periodic feedback from the target sensor, but without any common clock reference. The controller selected the optimal subset of ETs to satisfy the energy request from a given sensor, which cooperatively beamform RF energy towards that sensor.

Fig. 1. Prototyping distributed energy beamfomring with USRPs.

Our software-defined framework, implemented in Python, allowed the central controller to automatically discover the installed sensors, obtain energy needs, and schedule charging tasks in an asynchronous and non- blocking manner that allowed the network to scale. The demonstration included the design and fabrication of RF energy harvesting circuits that interface with the TIEZ430 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.

Fig. 2. Architecture of software-defined energy beamforming.

Furthermore, we developed a network architecture called HYDRA (from Harvesting energY from Direct RF and Ambient sources), a planning and network resource management framework for powering small form factor sensor nodes. HYDRA uses distributed ad hoc beamforming-capable energy transmitters (ETs) and also leverages ambient energy from cellular and TV spectrum bands (Fig. 3(a)).

Fig. 3(a) Network architecture of HYDRA where sensors are powered by joint ad­hoc beamforming from multiple energy transmitters (ETs) and ambient energy sources.

Fig. 3(b) Average received power density at various locations in the Boston area, from ambient sources as well as when the maximum energy harvesting yield source is intelligently chosen through the so called 'cognitive EH' approach.

Through modeling optimal radiating power levels and phases of the ETs, HYDRA determines the spatial scheduling of the energy beams mapping ET operations to changing network requirements and available ambient energy, while minimizing the energy expenditures of ETs. Through actual in-field experimentation, we showed that ambient RF energy harvesting is best performed by adaptively choosing the available spectrum bands, which in turn alters the energy contribution required from the ETs (Fig. 3(b)).

U. Muncuk, S. Mohanti, K. Alemdar, M Y. Naderi, K. R Chowdhury, “Software-defined Wireless Charging of Internet of Things using Distributed Beamforming," ACM SenSys 2016 - The ACM Conference on Embedded Networked Sensor Systems, Stanford, CA, USA, November 2016. PDF

K. Chowdhury, and M.Y. Naderi, “Distributed Wireless Charging System and Method,” U.S. Application No.: 62/308298.

2. Simultaneous Wireless Energy Transfer and Communication:
 When data communication and RF energy recharging occur in-band, sharing the RF medium and devoting separate access times for both operations raises architectural and protocol level challenges. We developed a method of concurrent transmission of data and energy to solve this problem, allowing ETs to transmit energy and sensors to transmit data in the sameband synchronously. Our key idea concerned devising a physical layer modulation scheme that allows the data transmitting node to introduce variations in the envelope of the energy signal at the intended recipient. We implemented a proof-of-concept receiver, modeled and validated through extensive experimentation. We also designed a new physical layer mechanism for guaranteed successful delivery of information in a point-to-point link.

Fig. 4. Energy management functions at the sensor, with the harvested energy budget feeding both the sensing as well as future transmission needs.

R. G. Cid-Fuentes, M. Y. Naderi, S. Basagni, K. Chowdhury, A. Cabellos-Aparicio, E. Alarcon, "On Signaling Power: Communications over Wireless Energy", IEEE INFOCOM 2016, San Francisco, CA, USA. PDF

R. G. Cid-Fuentes, M.Y. Naderi, S. Basagni, K. R. Chowdhury, A. Cabellos-Aparicio and E. Alarcón, "An All-Digital Receiver for Low Power, Low Bit-Rate Applications Using Simultaneous Wireless Information and Power Transmission", IEEE ISCAS 2016, Montreal, Canada, May 2016. PDF

3. Wake-Up Receiver & Token Identification using Energy Harvesting:
The existing passive wake-up receivers (WuRxs) are radio frequency identification (RFID) tag based, which incur high cost and complexity. In this activity, we studied cost-effective and long-range WuRx solutions for range-based wake-up (RW) as well as directed wake-up (DW). In particular, we considered the case of an RF energy harvesting wireless sensor node and investigate how a low-cost WuRx can be built using an RF energy harvester available at the node.

Fig. 5. Prototype of EH-based passive wake-up receiver.

In addition, we developed a touch energy harvester for smart interaction with capacitive touch–enabled devices by associating the token’s identity with its contact, or touch. The proposed token’s 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 harvester design. 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. By enabling the token to harvest energy from touch–screen sensors or touch–surfaces the token is rendered battery–free.

Fig. 6. (a) Touch energy harvester's schematic, (b) PCB design and token’s schematic.

K. Kaushik, D. Mishra, S. De, K. R. Chowdhury, and W. Heinzelman, “Low-Cost Wake-Up Receiver for RF Energy Harvesting Wireless Sensor Networks,” IEEE Sensors Journal, vol. 16, no. 16, Aug. 2016. PDF

P. Nguyen, U. Muncuk, A. Ashok, K. R. Chowdhury, M. Gruteser, and T. Vu, “Battery-Free Identification Token for Touch Sensing Devices, ACM Conference on Embedded Networked Sensor Systems (SenSys), Stanford, CA, Nov. 2016. PDF

4. Medium Access for Energy Transmitters:
 We researched, what we call a 'Duty­ cycled random-phase Multiple Access (DRAMA)' scheme, for wireless RF power transmission. Our approach is based not only in handling the interferences of multiple ETs, but also to benefits from them to broaden the input power range of existing energy harvesters at the sensor nodes. For this, DRAMA relies on the fundamental assumption that efficiency is maximized when the input power varies in time as much as possible, since the energy harvesters operate with increasing efficiency as a function of the input power.

R.G. Cid-Fuentes, M.Y. Naderi, R. Doost, K.R. Chowdhury, A. Cabellos-Aparicio, E. Alarcon, "Leveraging Deliberately Generated Interferences for Multi-sensor Wireless RF Power Transmission", in Proc. IEEE GLOBECOM 2015, San Diego, CA, USA, Dec. 2015. PDF

5. Multi-band Ambient RF Energy Harvesting for Self-powered Sensors:
We developed a multi-band adjustable circuit for harvesting from LTE 700MHZ, GSM 850MHZ, and ISM 900MHZ bands with one single circuit. To this end, we designed a tunable impedance matching network composed of off-the-shelf components, such as adjustable capacitors (i.e. trimmers) to adapt the impedance matching network configuration with the selected RF band using a single fabricated ambient RF energy harvesting circuit. Our circuit design is fabricated on the printed circuit board with comprehensive evaluations at each associated frequency to test the power conversion efficiency.

Fig. 7. (a) Overview of our adjustable ambient RF energy harvesting system, (b) Prototype of the circuit.

Additionally, we designed and implemented an RF-EH prototype can constantly operate TI eZ430-RF2500 sensor at multiple city locations, with efficiencies of up to 45% in LTE 700, GSM 850, and ISM 900 bands. We conducted comprehensive RF ambient survey study in Boston, and demonstrated that more than 65% of the locations have enough RF power density to perpetually operate low-power sensor mote in battery-less operation mode.

Fig. 8. (a) Battery-free communications setup with TI eZ430-RF2500 sensors that are powered with LTE signals, (b) Levels of average ambient harvested power at different Boston locations.

U. Muncuk, K. Alemdar, J. D. Sarode, and K. R. Chowdhury, "Multi-band Ambient RF Energy Harvesting Circuit Design for Enabling Battery-less Sensors", IEEE Transaction on Circuits and Systems, May 2017 (submitted)