Commit 38daca25 authored by U-RAJESH-SIS\rajesh's avatar U-RAJESH-SIS\rajesh
parents 6875f813 4b448a8f
......@@ -457,3 +457,10 @@ number={2},
pages={32-39},
doi={10.1109/MCAS.2015.2419011},
month={Secondquarter},}
@article{yildiz2007,
author= {Yildiz, F and Zhu, J and Pecen, R and Guo, L},
title= {Energy scavenging for wireless sensor nodes with a focus on rotation to electricity conversion},
journal={American Society of Engineering Education},
year={2007},
}
......@@ -2,10 +2,9 @@
\label{sec:discussion}
Our research results, using an admittedly `proof-of-concept' wearable platform, show that the \name paradigm of beamformed WiFi energy harvesting can be used to monitor the gestural activities of individuals, at least in an office-like environment. There are, however, several open issues and considerations that need further exploration.
\textbf{Beamforming for Multiple Receivers:} The bulk of our studies have considered just a single wearable device. Limited studies (in Section~\ref{sec:multiuser}) show that, when multiple client devices are present, an AP can judiciously either time-multiplex its power packet transmissions to different devices, or adjust its beamwidth to simultaneously cover multiple devices, albeit with lower harvesting power/device. Such multi-device environments require the WiFI AP to optimize its operations y carefully considering coverage vs. energy density tradeoffs (as a function of beamwidth), similar to the prior exploration of rate
vs. coverage tradeoffs for multicast wireless traffic~\cite{XXX} or throughput maximization under directional transmissions~\cite{XXX}. In addition, different client devices may have different residual energy and/or different priorities in energy harvesting policies. In particular, clients can transmit `ping' packets that encode the criticality of their energy demand, thereby allowing an individual WiFi AP to dynamically adjust its optical choices of (beamwidth, direction, timeslice).
\textbf{Beamforming for Multiple Receivers:} The bulk of our studies have considered just a single wearable device. Limited studies (in Section~\ref{sec:multiuser}) show that, when multiple client devices are present, an AP can judiciously either time-multiplex its power packet transmissions to different devices, or adjust its beamwidth to simultaneously cover multiple devices, albeit with lower harvesting power/device. Such multi-device environments require the WiFI AP to optimize its operations carefully considering coverage vs. energy density tradeoffs (as a function of beamwidth), similar to the prior exploration of rate vs. coverage tradeoffs for multicast wireless traffic~\cite{chou2006} or throughput maximization under directional transmissions~\cite{sen2008}. In addition, different client devices may have different residual energy and/or different priorities in energy harvesting policies. In particular, clients can transmit `ping' packets that encode the criticality of their energy demand, thereby allowing an individual WiFi AP to dynamically adjust its optical choices of (beamwidth, direction, timeslice).
\textbf{Multi-AP Operation:} Our controlled user studies have been performed using a single WiFi AP. In a practical campus or factory environment, multple APs are likely to `cover' a specific location (from measurements, the typical number of APs overhead at a location in our campus buildings is 5-6). This opens up additional possibilities. First, the presence of multiple APs can lead to an additive increase in the harvested energy, as a single client device can receive RF energy from multiple transmitters. However, this will also require enhancements to the RF harvester module on the wearable--e.g., it will likely need multiple tunable inductors, to allow the harvester to simultaneously have multiple resonant frequencies (one corresponding to each AP's operating frequency). The benefits of such added harvested energy vs. additional receiver complexity are unclear and require further investigation. Second, our current WARP-based AP implementation focused only on power packet transmissions. In practice, each AP will have to perform CSMA-based channel access to avoid contentions with the data traffic transmissions. Moreover, if RF charging may be viewed as a secondary benefit of WiFi APs, it is important to adjust the schedule \& duty cycle of power packet transmissions (e.g., by using multiple virtual queues similar to NAPman~\cite{rozner2010}) to ensure that they do not cause unacceptable loss or latency of data packets.
\textbf{Multi-AP Operation:} Our controlled user studies have been performed using a single WiFi AP. In a practical campus or factory environment, multple APs are likely to `cover' a specific location (from measurements, the typical number of APs overhead at a location in our campus buildings is 5-6). This opens up additional possibilities. First, the presence of multiple APs can lead to an additive increase in the harvested energy, as a single client device can receive RF energy from multiple transmitters. On the other hand, as suggested by Figure~\ref{fig:edev2beam}, beams on the same channel may also interfere destructively. However, this will also require enhancements to the RF harvester module on the wearable (similar to the design innovations in~\cite{talla2015powering}), to allow the harvester to simultaneously have multiple resonant frequencies, each corresponding to a different AP's operating frequency. The benefits of such added harvested energy vs. additional receiver complexity are unclear and require further investigation. Second, our current WARP-based AP implementation focused only on power packet transmissions. In practice, each AP will have to perform CSMA-based channel access to avoid contentions with the data traffic transmissions. Moreover, if RF charging may be viewed as a secondary benefit of WiFi APs, it is important to adjust the schedule \& duty cycle of power packet transmissions (e.g., by using multiple virtual queues similar to NAPman~\cite{rozner2010}) to ensure that they do not cause unacceptable loss or latency of data packets.
\textbf{Additional \& Improved Energy Harvesting:} One of our key contributions is to demonstrate that, with appropriate beamforming, standards-compliant WiFi transmissions can provide harvestable power levels of O(100$\mu$W) at reasonable distances (2-3m). In contrast, as an exemplary alternative,
mbient light energy (indoors) is projected to provide~\cite{yildiz2007} a harvestable power density of 100$\mu$W/cm$^2$, implying a harvesting capability of roughly around 1200$\mu$W for a typical $12cm^2$ smartwatch surface. It is entirely possible that, depending on the use case, wearables may combine WiFi/RF harvesting with other other ``traditional'' harvestable energy alternatives, such as ambient light and vibrations. The attractiveness of the \name prototype comes from our belief that WiFi is more pervasive and that WiFi-based harvesting can occur continuously (e.g., at night, in a dark room). In addition, our wearable prototype uses a straightforward XXX\am{Vu:say a couple of words about the antenna} antenna for energy harvesting. It is very likely that alternative antenna form factors (e.g., a metallic strip-based ``patch antenna, illustrated in Figure~\ref{fig:patchantenna}) can increase the harvested energy significantly (see~\cite{chen2013})--the development of suitable design forms for such RF-powered wearables remains an open question.
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......@@ -82,6 +82,7 @@ Figure~\ref{fig:dutycycle} plots the residual energy (computed, as before, from
We next varied the number of transmitting antennas in the WARP transmitter and studied the impact on the residual power. In this experiment, we explicitly plot the \emph{harvested RF power} *using a 10K$\omega$ resistive load) at the supercapacitor--i.e., we disable the wearable system components (microprocessor, sensor and RF frontend). Figure~\ref{fig:numberantenna} plots the resulting values, computed over the 15 minute experimental window. IMatching our intuition, a larger number of antennas allows the transmission beamwidth to be smaller, thereby effectively increasing the density of the delivered RF power. However, in practice, an overly thin beam may be counterproductive if the AoA estimation is not sufficiently accurate: the RF beam may be misdirected and too narrow, resulting in a sharp drop in the power harvested by the wearable. pointed at a direction deviated from the device's true location and thus the device may not be charged at all.
\subsection{Beam Adaptation for More than One Devices}
\label{sec:multiuser}
In the final set of studies, we studied the behavior of \name in the presence of multiple (2) client devices. In this case, the AP has to make some interesting choices between charging both devices simultaneously or in round-robin fashion. We placed the two devices on the table with two different spacing values: 30cm and 1.7m. We then run the beamforming algorithm with two operational modes:
\begin{itemize}
\item \emph{Time-multiplexed:} In this mode, the AP attempts to primarily charge only 1 client device at any instant. Given this objective, the AP uses an 8 antenna array (narrow beam) directed towards the current primary client device, before periodically switching the beam to the other client. We experimented with 3 switching periods: 10 secs, 30 secs and 90 secs.
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