Preliminary Evaluation of Simultaneous Data andPower Transmission in the Same Frequency Channel
Keita Yamazaki∗ , Yusuke Sugiyama∗ , Yoshihiro Kawahara† , Shunsuke Saruwatari∗ and Takashi Watanabe‡∗ Shizuoka University, † The University of Tokyo, ‡ Osaka University∗ Email: {yamazaki, sugiyama}@aurum.cs.inf.shizuoka.ac.jp, saru@inf.shizuoka.ac.jp† Email: kawahara@akg.t.u-tokyo.ac.jp ‡ Email: watanabe@ist.osaka-u.ac.jp

Abstract—Combining wireless transmission of data and powersignals enables us to use wireless devices without charging
batteries. To improve the utilization of wireless resources, a sender
could simultaneously transmit data and power signals in the same
frequency channel. A disadvantage of simultaneous transmissionis that it induces interference between data and power signals. To
minimize the effect of interference, we propose a new frequencysharing system. The proposed system makes two contributions.
The first contribution is interference cancellation of the powersignal to receive data from the collided signal using a combinationof digital and analog interference cancellation techniques. The
second contribution is a media access control protocol to receive
the transmitted power effectively by varying the sleep time. To
evaluate the performance of the proposed system, we built anexperimental apparatus using software-defined radio. Evaluations
show that it is feasible to transmit data and power simultaneously
using the proposed system.

I.

I NTRODUCTION

In our daily lives, we use various types of devices thatare connected to wireless networks and exchange information
with one another. The devices include mobile phones, carnavigation systems, heart-rate monitors, and tooth brushes [1].
Such wireless devices are driven by either charged batteries
or other external sources. Wireless power transmission [2]enables wireless devices to be powered permanently without
the need for changing and charging batteries; this will lead tothe invention of new types of wireless devices.
In this study, we use radio waves as the transmission
medium as they offer two advantages: (i) long transmission
distance and (ii) little calibration effort. In recent years, thedepletion of radio resources has become a significant problem
owing to the increase in the types of wireless devices. Therefore, wireless power transmission using radio waves needs tobe carried out without the depletion of radio resources.
The purpose of our study is to realize simultaneous dataand power transmission in the same frequency channel using
wireless power transmission and interference cancellation techniques [3], [4]. Figure 1 shows the final goal of our study. The
access points cooperatively transmit data and power to wirelesssensor nodes over a wireless network. The wireless sensor
nodes send back a data signal using the received and charged
power. Multiple access points and sensor nodes transmit databidirectionally, while the access points transmit power to thesensor nodes unidirectionally.
In this paper, we propose a frequency-sharing system
for simultaneous data and power transmission in the same
frequency channel. We assume that an access point and a

Power transmission

Access point

Access point

Data transmission

Wireless
sensor node

Wireless
sensor node
Access point

Fig. 1.

Central control unit

Final goal of the proposed system.

sensor node transmit data to each other when the access point
provides the power to the sensor node. This paper makes
two contributions: power-signal interference cancellation andmedium access control. Power-signal interference cancellation
enables the access point to receive data from a sensor nodeeffectively using digital and analog interference cancellation
while transmitting power. Medium access control enables thesensor node to receive the transmitted power effectively byvarying the sleep time.
We implemented the proposed system using softwaredefined radio to evaluate the performance of wireless powertransmission and power-signal interference cancellation. We
used a WARPv3 software-defined radio [5] to evaluate thefeasibility of power transmission. The evaluations show thata sensor node receives power to transmit a packet every 10
seconds.
We also used a universal software radio peripheral (USRP)
N200 software-defined radio [6] to evaluate power-signla
interference cancellation. Evaluation results show that thedigital and analog interference cancellation techniques cancel
the power signal by a maximum of 20 dBm and 40 dBm,
respectively.
The remainder of this paper is organized as follows. In
the next section, we present a brief review of related studies
and the position of this study. Section III describes the detailsof the proposed system that includes a wireless device anda protocol. Section IV evaluates the power transmission andinterference cancellation performance of the proposed system.
Finally, conclusions are summarized in Section V.
II.

R ELATED WORKThis study aims to realize simultaneous wireless data andpower transmission in the same frequency channel. This simul-Power transmission
Data transmission
Access point

Wireless full duplex communication [14]–[16], which regards its own transmitted signal as self-interference to achievebidirectional communication, utilizes digital and analog interference cancellation. To cancel self-interference, Bharadia etal. [16] implemented digital and analog interference cancellation on a specific transceiver and achieved high interference
cancellation up to a maximum of 110 dB.
Conventional interference cancellation studies focus only

AntennaRX

Antenna
TX & RX

Sensor node

MAC 凚Section 3B, 3C凛

As regards interference cancellation, some studies have
improved communication performance by utilizing the characteristic of simultaneous transmission. A study on successiveinterference cancellation (SIC) [3], [4], [12], [13], which
extracts two data signals from a collided signal, utilizes thedifference between the received power of the two signals. In
SIC, a collided signal is first decoded to extract a strong data
signal while a weak data signal is regarded as interference. The
decoded strong signal is then reproduced and the strong signal
is subtracted from the collided signal to extract the weakersignal. Finally, the extracted weaker signal is decoded. SIC is
performed on the digital signal after auto-gain control (AGC)and analog-to-digital conversion (ADC). SIC is also referred
to as digital interference cancellation.

Rectenna
RX

PHY

Some studies on energy harvesting have showed thatpower can be obtained from radio waves in the environment.
Kawahara et al. [11] successfully turned on an LED by radio
waves from Tokyo Tower and operated a thermometer byutilizing power leakage from a microwave oven. Radio waves
are preferred as a medium for wireless power transmission
because of the long transmission distance achieved and thelittle adjustment of devices required.

Analog interference cancellation

A well-known example of wireless power transmission
using radio waves is the radio-frequency identifier (RFID)
used in various fields. Although the power transmitted byradio waves is less than that by magnetic methods, the radio
waves transmit power over longer distances. Yeager et al. [9]demonstrated that power can be received at a distance of 2 musing the UHF band by employing the wireless identificationand sensing platform (WISP) [10].

Digital interference cancellation

Fig. 2.

To increase the distance over which power can be transmitted, several studies have focused on the phenomenonof magnetic resonance. Kurs et al. [8] proposed magnetic
resonance-based wireless power transmission. This method
utilizes strongly coupled resonance of coils and capacitors
and transmits power to devices placed up to a one-meter
range. Achieving resonance needs fine-tuning of the coil andcapacitor.

PHY

MAC 凚Section 3B, 3C凛This study focuses on wireless power transmission andinterference cancellation. Wireless power transmission is classified into two types: magnetic and radio waves. One of
the magnetic products used for wireless power transmission
is Felica [7] developed by Sony. Felica transmits power byelectromagnetic induction to devices in a few millimeters
range.

Antenna
TX

Supercapacitor

taneous transmission enables us to create a wireless harness
or an access point providing data and power simultaneously invehicles. To achieve simultaneous transmission, the harness or
the access point need to cancel interference caused by powersignals.

Overview of the proposed system.

on data transmission. Our study, on the other hand, considers
simultaneous data and power transmission using interference
cancellation.
III.

F REQUENCY- SHARING SYSTEM

Based on the discussion in Section II, we propose afrequency-sharing system for simultaneous data and powertransmission. Section III-A describes the architecture of theaccess point and the sensor node in the proposed system.
Section III-B and III-C describe a MAC protocol for uplinkand downlink, respectively.
A. The Architecture of the Proposed System
Figure 2 shows the overview of the proposed system.
The access point involves digital and analog interference
cancellation, the PHY layer, and the MAC protocol describedin Section III-B and III-C. The access point has TX and RX
antennas. The TX antenna transmits data or power signals fromthe PHY and the MAC layer.
The TX antenna transmits the power signal continuously
unless the access point transmits a data signal. The RX antenna
receives the data signal, which is transmitted by a sensor node,and its own power signal. The digital and analog interference
cancellation stage extracts the data signal from the received
signal. The data signal is processed by the PHY and the MAC
layers.
The sensor node has a supercapacitor to store received
power. The sensor node also has a MAC protocol described in
Section III-B and III-C. The access point has an RX rectenna
for power transmission and the TX and RX antennas fordata transmission. The RX rectenna receives the power signal
and stores the received power in the supercapacitor. The TX
antenna transmits the data signal from the PHY layer and the
MAC protocol. The RX antenna receives a transmitted data
signal from the access point and transfer to the PHY and the
MAC layer.
B. Frequency-Sharing MAC Protocol: Uplink
Figure 3 shows the data transmission procedure for uplink.
The access point is in the listen state until it receives the data
signal. In the listen state, the TX antenna transmits a powersignal, and the digital and analog interference cancellation

Using interference cancellation

Access point

Access point/

Data
transmission

Fig. 3.

' $

/

3
/

/

Sensor node B

' $ /
3

/

Sensor node A

Receive

/

3

Power
transmission

Sensor node C' $Tlisten

Tsleep

BoX-MAC

/

Sleep

/

Power
transmission

3

Sensor node C/: Listen䚸'': Data䚸$$: ACK䚸3
3: Power

Data transmission procedure in uplink

Tsleep is small
when a battery is high.

Tsleep is longwhen a battery is low.

Receive

Fig. 4. Comparison of the listen state between Box- Fig. 5.
MAC and our proposed system

/

'

'

/

/
Transmit

/

$

/
3

Tsleep/Sensor node B

' $

'

/

Sensor node A

Proposed
MAC protocol
Transmit

Datatransmission

Tsleep is static.

//

Receive

/
Sleep

'

$

/
/

/

/: Listen䚸'': Data䚸$$: ACK䚸3
3: Power

Data transmission procedure in downlink

stage extracts the data signal from the signal received by the
RX antenna.
Each sensor node transmits a data signal without carrier
sense when data is generated. After receiving a data signal
from a sensor node, the access point stops power transmission
and transmits an ACK frame. After transmitting the ACK
frame, the access point resumes power transmission. When thesensor node cannot receive the ACK frame, the sensor node
retransmits the data signal.

Access point

Sensor node

C. Frequency-Sharing MAC Protocol: Downlink
To receive power from an access point efficiently, eachsensor node changes its sleep time. To ensure this, we extend
the listen state of BoX-MAC [17], which has already been
implemented on a CC2420 IEEE 802.15.4 radio transceiver.
Figure 4 shows the comparison of the listen state of thesensor node with that of BoX-MAC. Tsleep is the sleep interval.
Tsleep in BoX-MAC is constant.
On the other hand, our protocol assigns a short Tsleep forthe sensor node with high battery and a long Tsleep for thesensor node with low battery. The protocol calculates Tsleep
as follows:(1)
Tsleep = αEmax /Estored
where α is a weighting factor depending on the application,
Estored is the stored power in a sensor node, and Emax is the
maximum power capacity of the sensor node. When α is large,
the average sleep time becomes longer.
Figure 5 shows the data transmission procedure for downlink. The data reception process of each sensor node is thesame as that of BoX-MAC. First, each sensor node goes tothe listen state during Tlisten at fixed intervals.
When data is generated at an access point, the accesspoint starts data transmission. The access point repeats datatransmission until the access point receives an ACK frame.
We assume that sensor node A successfully receives data fromthe access point for the third time and sends back an ACK
frame. Once a sensor node receives data during the listen state,
the sensor node stays at the receiving state. After the data isreceived, the sensor node sends back an ACK frame.
IV.

E VALUATION

We evaluated the performance of the system with respect
to power transmission and interference cancellation using

Fig. 6.

Power transmission setup

software-defined radio in a preliminary evaluation of thesystem.
We first implemented power transmission on a WARPv3
software defined radio. The transmission power is 20 dBm,
which is the standard transmission power of wireless LANs
in Japan. We next implemented interference cancellation on a
USRP N200 software-defined radio and a XCVR 2450 witha USRP hardware driver (UHD) [18] using C++. This isbecause the software-defined radio easily implements digitalinterference cancellation and adjusts the parameters of analog
interference cancellation.
A. Power Transmission
We measured the power received by a sensor node from anaccess point at the anechoic chamber in Shizuoka University,
Japan. Figure 6 shows the power transmission set up. We used
a WARPv3 software-defined radio as the access point. The
antenna of the access point is VERT2450 for the 2.4–2.48-GHz
band with a 3-dBi gain. We connected the WARPv3 softwaredefined radio to a spectrum analyzer and observed that thetransmission power is 17.3 dBm. Thus, the transmission powerof the access point with VERT2450 is about 20.3 dBm.
The access point sends three types the power signal:
continuous-wave (CW), binary phase-shift keying (BPSK), andorthogonal frequency-division multiplexing (OFDM). We useda rectenna for the 2.4-GHz band as a sensor node and evaluatedreceived power. The received band is 2.45 GHz± 50 MHz, andthe maximum output voltage is 2.7 V±0.1 V. We connected
the rectenna to a 100-kΩ resistor.

Fig. 7. Received power as a function of the distance Fig. 8. Received power as a function of the speed Fig. 9. Received power as a function of the carrierof the baseband signal
frequency

Figure 7 shows the received power as a function of distance
between the access point and the sensor node. The speed of
the baseband signal is 10 Msps. The carrier frequency is 2.412
GHz. Figure 7 shows the following:
1)
2)

3)

The sensor node receives about 75 µW from transmission signals when the distance is shorter than 30
cm.
The received power of the OFDM signal is lower thanthat of the CW and the BPSK signals when the accesspoint sends the CW or the BPSK signal when the
distance is 30–90 cm. The result shows that a single
frequency is more suitable for power transmission
than multiple frequencies.
The received power gradually decreases as the distance increases. The received power is zero when the
distance is 120 cm. In order to increase the coverage
distance, transmission power has to be increased.

Figure 8 shows the received power as a function of the
distance. The carrier frequency is 2.412 GHz. The distance
between the access point and the sensor node is 50 cm. Figure
8 shows that the power transmission is almost independentof the speed of the baseband signal. Specifically, the valuesof received power of the CW, BPSK, and OFDM signals
are 57 µW–65 µW, 51 µW–52 µW, and 34 µW–46 µW,
respectively.
Figure 9 shows the received power as a function of thecarrier frequency. The distance between the access point andthe sensor node is 50 cm. The speed of baseband signal is 10
Msps. Figure 9 shows the following:
1)

2)

Power transmission is almost independent of thecarrier frequency. Specifically, the values of received
power of the CW, BPSK, and OFDM signals are 61µW–70 µW, 60 µW–68 µW, and 45 µW–51 µW,
respectively.
The received power of the OFDM signal is 20 %–40 % lower than that of the CW and BPSK signals.
There is room for improvement with respect to themodulation scheme of the data transmission; forexample, the modulation schemes on the downlink
and uplink can be changed.

The above results show that the sensor node transmits apacket every 10 seconds when the carrier frequency is 2.412
GHz when the distance between the access point and the sensor
node is 50 cm, and the speed of the baseband signal is 10 Msps.

TX1

RX

TX2

Fury
DesktopPC

Fig. 10.

PC

PC

Experimental setup for digital interference cancellation

This is because the sensor node transmits a packet at 500 µJ.
The results demonstrate that the proposed system can be used
for short-range wireless applications such as a sensor network
in a vehicle.
B. Digital Interference Cancellation
In order to cancel the power signal from the received signal
after ADC and AGC, we implemented the digital interference
cancellation stage. Figure 10 shows the experimental setup
for digital interference cancellation. The experimental setup
consists of two senders TX1 and TX2 , one receiver RX, threecontrol computers, and a Fury desktop used as an external
clock. The senders and the receiver were implemented by
USRP N200s and connected to each control PC (Panasonic
Let’s note CF-B11). To reduce frequency offsets among the
USRPs, a 10-MHz signal was input from the Fury desktop to
all USRPs. TX1 periodically sends an OFDM signal as a data
signal. TX2 continuously sends a sine wave as a power signal.
The OFDM signal collides with the power signal at RX. RX
extracts the OFDM signal by subtracting the power signal fromthe collided signal. RX decodes the extracted OFDM signal.
We evaluated the experimental setup operating in the 5.11GHz band at the anechoic chamber in Shizuoka University,
Japan. The sampling rate is 195.3125 ksps, and the payload
size of the OFDM signal is 1500 bytes. The number of powersignal samples was fixed at 500.
First, we evaluated the bit-error rate (BER) as a functionof the signal-to noise ratio (SNR). The theoretical values in an

0

10

100

Data signal
Theoretical80
Decode rate [%]

BER

10-1
10-2
10-3

-10

Fig. 11.

Analog interference cancellation circuit

40
RxIN

0
-40

-5

0

10
SNR [dB]

BER as a function of SNR

20

30

SamplerIn+

Data and energy
Data and data
-30

-20
-10
10 log10(Pa / Pb) [dB]

Figure 12 shows the decoding rate as a function of thepower ratio between the two signals. Data and power areproposed for power signal interference cancellation, whereas
only data signals are used in conventional SIC. We calculated
the power ratio with the received-signal strength indicator(RSSI) of the two signals, Pa and Pb as 10 log (Pa /Pb ). In
the data and power signal scenario, Pa and Pb are the RSSIof OFDM and power signals, respectively. In the data only
scenario, Pa and Pb are the RSSI of weak and strong OFDM
signals, respectively. Figure 12 shows the following:

3)

Balun

USB

RxOUT

EXT

In

10
Transmitting
circuit

Receiving
circuit

SPI

Fury
Desktop

USRP1

The decoding rate is small when the power ratio issmall. The dynamic range of the data signal becomes
smaller because AGC controls the gain based on the
power signal. When the power ratio is small, the RSSIof the power signal is larger than that of the data
signal. For example, when the power ratio is −30
dB, the RSSI of the power signal is 1000 times larger
than that of the data signal.
The decoding rate of data and power achieved islarger than that achieved with data and data. Unlike
the waveform of a power signal, the waveform ofa data signal is unknown. When the decoding of astrong data signal fails, the decoding of a weak signal
also fails automatically.
The decoding rate of data and power achieved is
100% when the power ratio is higher than approximately −20 dB. This means that digital interference
cancellation is successful when the RSSI of the powersignal is about 100 times larger than that of the data
signal. When the power ratio is smaller than −20
dB, the receiver needs to combine analog interference
cancellation to receive the data signal.

USRP2
balun
QHx220

Next, we evaluated the decoding rate as a function of thepower ratio. To analyze the difference in performance between
cancellation of a known power signal and an unknown data
signal, the decoding rates of conventional and our implemented
interference cancellation of the power signal were compared.

2)

0

QHx220-Fig. 12. Decoding rate as a function of power ratio Fig. 13. Schematic of the analog interference canbetween the two signals
cellation circuit

additive white gaussian noise (AWGN) channel were comparedwith experimental results. Figure 11 shows the BER as afunction of the SNR. The power ratio between the OFDM
signal and the power signal ranged from −31.23 to −5.57
dB. If the BER was zero, we plotted for a value of 10−5 forconvenience sake. Figure 11 shows that digital cancellation
is successful because the experimental results approach thetheoretical results.

1)

Antenna
RX

60

20

10-4
10

Antenna
TX

PC1

PC2
TX

Fig. 14.

RX

Experimental setup for analog interference cancellation

C. Analog Interference Cancellation
In order to cancel the power signal from the received
signal before AGC and ADC, we implemented the analog
interference cancellation circuit using the QHx220 circuit [19].
The QHx220 circuit controls the amplitude and the phaseof analog signals. In terms of the number of antennas, theimplemented circuit exploits the balun (balanced-unbalanced)
circuit to cancel self-interference. Antenna cancellation [15]needs three antennas, whereas the balun circuit needs only
two antennas.
Figure 13 shows the schematic of the analog interference
cancellation circuit. The transmission signal from a USRP
N200 is input to the balun circuit. The balun circuit outputs
the phase-inverted transmission signal and the original transmission signal. Next, the phase-inverted transmission signal is
input to the QHx220 circuit and the original transmission signal to antenna TX. The QHx220 circuit adjusts the amplitude
and the phase of the phase-inverted transmission signal, and theadjusted signal combines with the received signal from antenna
RX to achieve self-interference cancellation. The combined
signal is fed to another USRP N200, and the amplitude andthe phase are adjusted with a serial peripheral interface (SPI)
to enhance the performance of interference cancellation. For
the adjustment, the SPI uses the result of signal processing
and transmits the amplitude and the phase with 24 bits at 10
Mbps.
Figure 14 shows the experimental setup for analog interference cancellation. The experimental setup consists of

1024

-10

-20

-30

RSSI [dBm]

Q-DAC Value

512

-40

channel. To evaluate the performance of power transmission
and interference cancellation, we used the software-definedradio. Evaluations showed that the power transmission and theinterference cancellation of the wireless device are feasible.
Currently, we are working on adapting the system for use inpractical applications such as a wireless harness in a vehicle.
For future work, we verify our study with theoretical aspects[20], [21].
ACKNOWLEDGEMENT
This work was supported by SCOPE (Strategic Information
and Communications R&D Promotion Programme) of Ministry of Internal Affairs and Communications, Japan.
R EFERENCES

-50
512

0

1024

[1]
[2]

I-DAC Value

Fig. 15.

RSSI of the signal after self-interference cancellation[3]

two USRP N200s, two control PCs (Panasonic Let’s note
CF-B11), one analog interference cancellation circuit consistsof the balun circuit and the QHx220 circuit, and the Fury
desktop used as an external clock. To reduce frequency offsets
among the USRPs, a 10-MHz signal was input from the Fury
desktop to all USRPs. The USRP1 with the control PC1
sends the power signal from the antenna TX. After antenna
RX received the signal, the analog interference cancellation
circuit cancels self-interference. The USRP2 with the control
PC2 receives the signal. The control PC2 sends the value ofthe amplitude and the phase as 78 bytes of data via the USB,
whose transmission rate is 921.6 kbps. We used FT245RL tocontrol the QHx220 circuit through the USB. We evaluatedthe experimental setup operating in the 5.11-GHz band at theanechoic chamber in Shizuoka University, Japan. We observed
the RSSI of the signal after self-interference cancellation.

[4]

Figure 15 shows the RSSI of the signal after selfinterference cancellation. Here, we assign the I-DAC value ofthe QHx220 circuit parameter to the horizontal axis and the
Q-DAC value of the QHx220 circuit parameter to the verticalaxis. Figure 15 shows the following:
1)
2)

3)

The analog interference cancellation circuit cancels
self-interference by 40 dB. The circuit achieves better
cancellation than digital interference cancellation.
From the experiment, the optimal I-DAC and Q-DAC
values are 377 and 420, respectively. When QHx220
chooses the optimal values, the analog interference
cancellation circuits cancels self-interference by 62.4
dB.
As the I-DAC and Q-DAC values differ from optimal values, the performance of analog interference cancellation gradually decreases. Specifically,
the analog interference cancellation circuit cancels
self-interference by 40 dB until the I-DAC and QDAC values differ from the optimal values by up to50.
V.

C ONCLUSIONSThe present paper proposed a frequency-sharing system
to transmit data and power wirelessly in the same frequency

[5]
[6]
[7]
[8]
[9]
[10]

[11]

[12]

[13]

[14]

[15]

[16]

[17]
[18]
[19]
[20]
[21]

Beam, “Beam Toothbrush,”
http://www.beamtoothbrush.com/toothbrush/.
T. Bieler, M. Perrottet, V. Nguyen, and Y. Perriard, “Contactless power
and information transmission,” IEEE Transactions on Industry Applications,vol. 38, no. 5, pp. 1266–1272, 2002.
D. Tse and P. Viswanath, Fundamentals of Wireless Communication. Cambridge University Press, May 2005.
D. Halperin, T. Anderson, and D. Wetherall, “Taking the sting out of carrier sense: Interference cancellation for wireless LANs,” in Proceedings ofthe 14th ACM Annual International Conference on Mobile Computing and
Networking (MobiCom’08), San Francisco, California, September 2008, pp.
339–350.
Rice University, “WARP, Rice University open-access research platform,”
http://warp.rice.edu/trac/.
Ettus Research, “USRP N200/N210 Networked Series,” September 2012.
Sony Global, “FeliCa Web Site,”
http://www.sony.net/Products/felica/.
A. Kurs, A. Karalis, R. Moffatt, J. D. Joannopoulos, P. Fisher, and M. Soljacic,“Magnetic resonances wireless power transfer via strongly coupled,” Science,
vol. 317, no. 82, pp. 83–86, July 2007.
D. J. Yeager, A. P. Sample, and J. R. Smith, “Wisp: A passively powered
uhf rfid tag with sensing and computation,” RFID Handbook: Applications,Technology, Security, and Privacy, pp. 261–278, 2008.
J. R. Smith, A. P. Sample, P. S. Powledge, S. Roy, and A. Mamishev, “Awirelessly-powered platform for sensing and computation,” in Proceedings of
the 8th International Conference on Ubiquitous Computing (UbiComp’06).
Springer, 2006, pp. 495–506.
Y. Kawahara, X. Bian, R. Shigeta, R. Vyas, M. M. Tentzeris, and T. Asami,“Power harvesting from microwave oven electromagnetic leakage,” in Proceedings of the 15th International Conference on Ubiquitous Computing(UbiComp’13), Zurich, Switzerland, september 2013, pp. 373–382.
S. Gollakota and D. Katabi, “ZigZag decoding: Combating hidden terminals
in wireless networks,” in Proceedings of the Annual Conference of the ACM
Special Interest Group on Data Communication (SIGCOMM’08), Seattle,
Washington, August 2008, pp. 159–170.
A. Gudipati and S. Katti, “AutoMAC: Rateless wireless concurrent medium
access,” in Proceedings of the 18th ACM Annual International Conference on
Mobile Computing and Networking (MobiCom’12), Istanbul, Turkey, August
2012, pp. 257–268.
J. I. Choi, M. Jain, K. Srinivasan, P. Levis, and S. Katti, “Achieving single
channel, full duplex wireless communication,” in Proceedings of the 16th
ACM Annual International Conference on Mobile Computing and Networking(MobiCom’10), Chicago, Illinois, September 2010, pp. 1–14.
M. Jain, J. I. Choi, T. M. Kim, D. Bharadia, S. Seth, K. Srinivasan, P. Levis,
S. Katti, and P. Sinha, “Practical, real-time, full duplex wireless,” in Proceedings of the 17th ACM Annual International Conference on Mobile Computing
and Networking (MobiCom’11), Las Vegas, NV, September 2011, pp. 301–
312.
D. Bharadia, E. McMilin, and S. Katti, “Full duplex radios,” in Proceedingsof the Annual Conference of the ACM Special Interest Group on Data
Communication (SIGCOMM’13), HongKong, China, August 2013, pp. 375–
386.
D. Moss and P. Levis, “BoX-MACs: Exploiting physical and link layerboundaries in low-power networking,” Stanford University, Tech. Rep. SING08-00, 2008.
J. Blum, “UHD driver for USRPs,” in In GNU Radio Conference (GRC’11),
September 2011.
Q. Inc., “QHX220 Active Isolation Enhancer and Interference Canceller,”
http://www.intersil.com/products/deviceinfo.asp?pn=QHX220.
H. Ju and R. Zhang, “Throughput maximization in wireless powered communication networks,” in IEEE Transactions on Wireless Communications,vol. 13, no. 1. IEEE, January 2014, pp. 418–428.
K. Ishibashi, “Dynamic Harvest-and-Forward: New Cooperative Diversity
with RF Energy Harvesting,” in Proceedings of the 6th International Conference on Wireless Communications and Signal Processing (WCSP’14),
October 2014, pp. 1–5.