Commit e143590a authored by Tran Huy Vu's avatar Tran Huy Vu

Update section 1 and 2

parent 257dd0e9
......@@ -464,3 +464,14 @@ month={Secondquarter},}
journal={American Society of Engineering Education},
year={2007},
}
@article{schmidt1986multiple,
title={Multiple emitter location and signal parameter estimation},
author={Schmidt, Ralph},
journal={IEEE transactions on antennas and propagation},
volume={34},
number={3},
pages={276--280},
year={1986},
publisher={IEEE}
}
......@@ -49,7 +49,7 @@ the harvested WiFi power (via directional WiFi transmissions) to much higher lev
device, at a much greater distance ($\sim$3-4meters from the transmitter)
than had been previously possible. This enables many more use cases, in
industrial IoT, smart homes, etc.; and (b) that, with novel triggered-sensing
techniques (that further extend the energy-driven intermittent sensing paradigm articulated in~\cite{hester20017b}), our solution can be used to collect useful gesture-related data from a batteryless, wearable sensing device, using an embedded accelerometer.
techniques (that further extend the energy-driven intermittent sensing paradigm articulated in~\cite{hester2017b}), our solution can be used to collect useful gesture-related data from a batteryless, wearable sensing device, using an embedded accelerometer.
Our solution, called \names, uses beam-formed transmissions, by a
multi-antenna AP, of WiFi ``power packets'' (transmissions performed
......@@ -105,7 +105,7 @@ drainage.
\item \emph{Demonstrate Feasibility of \name in a Real Office Environment:}
We utilize a series of quasi-controlled studies, in an office environment,
to demonstrate the overall effectiveness of the proposed \name approach.
\am{Need to add some details on the studies and the results}
Our microbenchmarks shows a huge potential use of the \name architecture for battery-less device. Though our user study shows that the application of \name to wearable devices is much more challenging, we do notice one case that the system provides sufficient energy for the wearable to work. In other cases, we do notice that our AP can transmit tens of \micro W to the device.
\end{itemize}
......
......@@ -47,7 +47,7 @@ With the adoption of MIMO technologies in the latest 802.11n and 802.11ac WiFi s
\end{figure}
\subsection{Locating the Client Device}
For beamformed energy transfer to be effective, the WiFi AP needs to know the location of the client device. More specifically, the AP does not really need to know the client's precise location; what it needs is the \emph{angular direction} of the client, \emph{relative to the AP's own location}. To compute this, the WiFi AP utilizes its antenna array to determine the AoA of any wireless transmissions from the client device. The key principle for such angle/direction estimation is that the same signal propagates different amounts of distances to reach different antennas located at the AP, and thus manifests itself in slight shifts in the signal phase changes across the different antenna elements at the AP. As the spacing between the antennas is fixed and known, by measuring the signal phase difference between adjacent antennas, we can estimate the angle of arrival of the signal (device). In practice, the presence of multipath (reflected signals) causes errors in such AoA estimation. Accordingly, we employ the state-of-the-art MUSIC signal processing algorithm~\cite{xx} to obtain the AoA information for both direct path and multipath signals. We defer implementation-specific details of such AoA estimation to Section~\ref{xxx}. However, Figure~\ref{fig:musicerror} shows the AoA estimation error observed in our office room setting, utilize a 4-element antenna array: we can see that the multi path effect in office environment is quite strong. At 1 location with 10 ping packets, the highest peak in a AoA spectrum is not always the correct angle of the device. However, if the system observes a sufficient number of continuous packets, it can still estimate the real angle of the device. This has been done in \cite{xiong2013arraytrack}. Note also that this functional step is needed only for mobile clients (e.g., wearable devices worn by an individual), and is unnecessary for more static settings where the location of the sensor devices are predetermined.
For beamformed energy transfer to be effective, the WiFi AP needs to know the location of the client device. More specifically, the AP does not really need to know the client's precise location; what it needs is the \emph{angular direction} of the client, \emph{relative to the AP's own location}. To compute this, the WiFi AP utilizes its antenna array to determine the AoA of any wireless transmissions from the client device. The key principle for such angle/direction estimation is that the same signal propagates different amounts of distances to reach different antennas located at the AP, and thus manifests itself in slight shifts in the signal phase changes across the different antenna elements at the AP. As the spacing between the antennas is fixed and known, by measuring the signal phase difference between adjacent antennas, we can estimate the angle of arrival of the signal (device). In practice, the presence of multipath (reflected signals) causes errors in such AoA estimation. Accordingly, we employ the state-of-the-art MUSIC signal processing algorithm~\cite{schmidt1986multiple} to obtain the AoA information for both direct path and multipath signals. Figure~\ref{fig:musicerror} shows the AoA estimation error observed in our office room setting, utilize a 4-element antenna array: we can see that the multi path effect in office environment is quite strong. At 1 location with 10 ping packets, the highest peak in a AoA spectrum is not always the correct angle of the device. However, if the system observes a sufficient number of continuous packets, it can still estimate the real angle of the device. This has been done in \cite{xiong2013arraytrack}. Note also that this functional step is needed only for mobile clients (e.g., wearable devices worn by an individual), and is unnecessary for more static settings where the location of the sensor devices are predetermined.
\begin{figure}[!htb]
\centering
......
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