IEICE TRANS. COMMUN., VOL.E96–B, NO.10 OCTOBER 2013

2491

PAPER

Special Section on Recent Progress in Antennas and Propagation in Conjunction with Main Topics of ISAP2012

Compact Antenna Arrangement for MIMO Sensor in Indoor
Environment
Naoki HONMA†a) , Member, Kentaro NISHIMORI†† , Senior Member, Hiroaki SATO† ,and Yoshitaka TSUNEKAWA† , Members

SUMMARY
This paper proposes the antenna arrangement for 2 × 2
MIMO (Multiple-Input Multiple-Output) sensor and evaluates the detection performance based on raytracing simulation. In this arrangement, thetransmitting and receiving antennas are placed closely. Two types of thearrangement are considered. In the first method, all of the transmitting andreceiving antennas are located closely. In the second method, two sets of
the antennas are placed separately, and each set has one transmitting and
one receiving antennas. The numerical analysis of the indoor propagation
based on the raytracing method is carried out. The path distribution andintrusion detection performance with the various antenna arrangements areevaluated for the human positions all over the room. The numerical analysis results show that the proposed antenna arrangements achieve the compact configuration of the sensor antenna system as well as high detection
performance.
key words: MIMO sensor, antenna, element spacing

1.

Introduction

Intrusion sensors using microwave for security application
has been studied [1]–[6], in these days. The microwave
sensors using existing signals, such as wireless LAN, TV
broadcast signals and so on, have been studied, and they
have proven that the microwave sensor are eﬀective in
break-in detection [1]–[4]. In [2] and [3], the intrusion isdetected by observing the amplitude of the received signal,
and it is shown that motion of the human body yields change
in the reception power of the broadcast signals. The work
[4] has proposed the detection algorithm where the eigenvector at the receiving array antennas is exploited to obtainhigh sensitivity. These microwave sensors can detect the
intrusion even when the intruder is at the NLOS (Non LineOf-Sight) locations, and this is the most attractive featurecompared to the other sensors [5].
The authors have studied MIMO (Multiple-Input
Multiple-Output) sensor that uses the MIMO channel variation to detect the intruders [5], [6] for indoor environment.
The MIMO sensor detects the intrusion by comparing thevarying channel with the person to the static one. In [5],the relationship between the antenna height and the detection rate has been studied, and it is found that the antenna
needs to be lower than the height of the intruder. In [6]Manuscript received January 17, 2013.
Manuscript revised May 20, 2013.
†
The authors are with Iwate University, Morioka-shi, 020-8551
Japan.
††
The author is with Niigata University, Niigata-shi, 950-2181
Japan.
a) E-mail: honma@iwate-u.ac.jp
DOI: 10.1587/transcom.E96.B.2491

and [7], the eﬀect of the antenna element spacing on thedetection rate has been investigated, and two types of theantenna configuration, i.e., SIMO (Single-Input MultipleOutput) and MIMO arrays, are compared. This work indicated that MIMO configuration outperforms SIMO configuration, but large antenna aperture is needed to achieve
high sensitivity. The work [8] experimentally explored theeﬀect of antenna diversity, frequency band, and size of theroom on the detection rate. In [9], the channel characteristics are evaluated and the eﬀect of the direct path existence
and location of the intruder on detection performance wasinvestigated. In these studies, the transmitting and receiving
arrays are placed separately at the ends of the rooms. It was
found that the arrays with wide antenna spacing are desirable for the high detection performances. In terms of the realistic hardware of the sensor, the excessively large antennaconfiguration and high hardware complexity are not desirable. Therefore, the eﬃcient antenna arrangement is needed
even when the size and number of the antennas are limited.
In this paper, we propose the antenna arrangement for
the MIMO sensor where the transmitting and receiving antennas are placed together [10]. The arrangement requires
the less antenna spaces than the conventional one. The
path distribution and the detection probabilities are evaluated based on the raytrace simulation. It is shown that the
proposed antenna arrangement can achieve the fairly highdetection performance.
2.

Concept of MIMO Sensor and Detection Method

Before discussing the proposed antenna arrangement, thebasic concept of the MIMO sensor is explained briefly. Figure 1 is the conceptual sketch of MIMO sensor. This system
has Mt transmitting and Mr receiving antennas. At first, theMIMO channel without a person is measured in advance.
This channel is static and defined as,⎞⎛⎜⎜⎜ hno,11 . . . hno,1Mt ⎟⎟⎟⎜⎜⎜ .
.. ⎟⎟⎟⎟ .
..
Hno = ⎜⎜⎜ ..
(1)
.
. ⎟⎟⎟
⎠
⎝⎜
hno,Mr 1 . . . hno,Mr Mt
On the other hand, the channel with a person is defined as⎞⎛⎜⎜⎜ hob,11 . . . hob,1Mt ⎟⎟⎟⎜⎜.. ⎟⎟⎟⎟ .
..
Hob = ⎜⎜⎜⎜ ...
(2)
.
. ⎟⎟⎟
⎜⎝
⎠
hob,Mr 1 . . . hob,Mr Mt

c 2013 The Institute of Electronics, Information and Communication Engineers
Copyright IEICE TRANS. COMMUN., VOL.E96–B, NO.10 OCTOBER 2013

2492

Fig. 1Thus, the power of the error component is decreased in inverse proportion to the training times, NS .
In the simulation, the transmitting power is P = 1 W,
the number of the transmitting and receiving antennas are
Mt = Mr = 2, and the number of the training symbols
is set to NS = 8. The static channel, Hno , is assumed tobe obtained accurately by many training rounds, and does
not contain noise components. Hw is a Gaussian randommatrix, and its variance is determined so as to satisfy (6).
The estimation error, Hw , is used for considering sensitivity of MIMO sensor. In order to detect the intrusion, thecorrelation value needs to be observed and the detection ismade when the correlation is lower than the certain value.
We define a threshold value, ρt , and the intrusion is detected when ρ < ρt . When the estimated channel contains
a strong estimation error, the channel correlation is lowered
and this yields the false detection. Therefore, ρt needs to be
suﬃciently small so as to reduce the false detection. The
threshold value, ρt , can be determined by comparing Hno
and Hno + Hw , and is given so that the false detection probability becomes 1% in the static environment.

Concept of MIMO sensor.

The channels, Hno and Hob , are compared by the evaluation
function, Mr Mt∗
hno,i j hob,i j 
i=1 j=1.
(3)
ρ=Mr Mt Mr Mt h 2h 2
no,i job,i ji=1 j=1i=1 j=1

Now, (3) is defined as channel correlation in this study [6].
This value is lowered when these two channels diﬀer greatly,
and approaches to 1 when two channels are identical. Meanwhile, the estimated channel contains the random errors because of the existence of the noise, and the actually observed
channel correlation is lower than 1 even when the channel is
not varied. In this system, the training symbols known to
the receiver are sent from the transmitting antennas. A series of the training signals is defined as S = [s1 , · · · , sNS ],where NS is the number of training symbols, NS ≥ Mt andsi = [s1i , ..., s Mt i ]T . The received noise is also defined as
N = [n1 , · · · , nNS ], where ni = [n1i , ..., n Mr i ]T . They satisfy
the conditions,
NS P
I Mt ×Mt
M t
E NN H = NS σ2n I Mr ×Mr ,

SSH =

(4)
(5)

where P is the sum of the transmitted power. The noise is tobe zero-mean Gaussian white, and its mean power is σ2n . In
this case, the estimated channel without any persons at thecertain moment is expressed as H = Hno + Hw , where Hw
is the error component of the estimated channel. Based on
the LS (Least Square) estimation, its characteristics can be
expressed as, σ2 M 2
E Hw HwH = n t I Mr ×Mr .
NS P

(6)

3.

Proposed Antenna Arrangement and Numerical
Analysis Model

3.1 Antenna Arrangement
The MIMO sensor dealt with in this paper comprises 2 × 2
vertical dipoles. Figure 2(a) indicates the proposed antennaarrangement. The transmitting and receiving antennas arearranged vertically each other, and this yields small mutual
coupling between the transmitting and receiving antennas.
Two sets of such antennas are arranged horizontally. The
advantage of this arrangement is that the configuration of
the sensor system becomes very compact since all of the antennas are placed closely if the horizontal distance between
two sets is within some wavelengths.
The arrangement in Fig. 2(b) is another proposal. One
set of the transmitting and receiving antennas is placed at
one side of the room, and another identical set is placed atanother side of the room. As it can be seen in Fig. 2(b),this configuration can cover all over the room even aroundthe corner of the room, which have been dead zone of the
MIMO sensor in the previous work [6] if the 4 antennas areplaced to 4 corners.
Figure 2(c) shows the antenna arrangement C, which isthe conventional one. The transmitting and receiving arrays
are located at both ends of the room. This arrangement isnormally used in MIMO systems, and this has been wellstudied in our previous works [5]–[8].
3.2 Numerical Analysis ModelIn this study, the detection performance is evaluated using
the raytracing simulation based on the imaging method. Figure 3 shows the numerical analysis model for indoor environment. Two diﬀerent environments are tested in this study.

HONMA et al.: COMPACT ANTENNA ARRANGEMENT FOR MIMO SENSOR IN INDOOR ENVIRONMENT

2493

One is a small room, whose dimension is W x × Wy × Wz =7.8 × 6.8 × 2.5 m3 . The other is a large room, whose dimension is 15.6 × 13.6 × 2.5 m3 . The materials of wall, ceiling,
and floor are assumed to be concrete (the relative permittivity: 6.0). The human body is approximated as the rectangular dielectrics whose dimension is 0.2 × 0.34 × 1.7 m3 (therelative permittivity: 37.5), and it is placed at the position(x, y). The height of the antenna, h, the antenna spacing,d, and positions are mentioned in the following section. In
the raytracing simulation, the number of the maximum reflection times is set to 5. The number of the human body is
1, and the human body is moved with 0.5 m step and 1.0 m

step in xy directions for the small and large rooms, respectively, i.e., 180 positions are evaluated for each environment.
The frequency is 2.4 GHz or 5.2 GHz, and the bandwidth is
10 MHz. The dipole radiation pattern is used, but the mutual
coupling is neglected for simplicity.
4.

Results

Figure 4 shows the path distribution calculated by imaging
method. Figures 4(a), (b) and (c) corresponds to the arrangements A, B, and C, respectively. Here, the distributions are projected onto xy-plane. The position of humanbody is set to (x, y) = (3.9, 3.4) m, and the antenna heightis set to h = 1.0 m. In the arrangement A, the antennas
are located on the plane, X = 3.9 m. In the arrangements
B and C, the antennas are located on the planes, X = 0.6 m,
X = 7.6 m. The antenna spacing, d, is set to 0.5λ0 (λ0 : wavelength in vacuum). For simplicity, only the major paths areshown in these figures. It can be seen that the arrangement
A yields radial path distributions. However, the relatively

Fig. 2 Antenna arrangement: (a) Arrangement A (Proposed), (b)Arrangement B (Proposed), (c) Arrangement C (Conventional).

Fig. 3

Analysis model.

Fig. 4 Path distribution based on imaging method (W x × Wy × Wz =7.8 × 6.8 × 2.5 m3 ): (a) arrangement A, (b) arrangement B, (c) arrangement
C.

IEICE TRANS. COMMUN., VOL.E96–B, NO.10 OCTOBER 2013

2494

Fig. 6 Detection rate versus antenna position, X (arrangement A, W x ×
Wy × Wz = 7.8 × 6.8 × 2.5 m3 , 2.4 GHz).

Fig. 5 Detection characteristics (arrangement A, 2.4 GHz): (a) Detection
rate versus d, (b) Distribution of channel correlation.

sparse path distribution around the walls is observed. On
the other hand, the arrangement B yields two kinds of paths,
i.e., one is between two separated antenna sets, and anotheris between two closely placed transmitting and receiving
antennas. Since two of them distribute totally in diﬀerent
ways, the sensor is expected to detect the target all over theroom. Meanwhile, the path distribution in the arrangement
C is relatively sparse, especially around the corners.
Figure 5(a) shows the detection rate versus the antenna
spacing, d. Here, all of the antennas are located in the plane,
X = 3.9 m, their height is 1.0 m, and d corresponds to thespacing between two sets of the transmitting and receiving antennas. The antenna location in y-axis is Y = 3.6 m.
The transmitting power is 1 W, and the noise power is set toσn 2 = −78, −68, −58 dBm. From this result, it is found thatthe detection rate improves by increasing d. On the other
hand, the detection rate cannot be improved even with large
d when the noise power is high (σn 2 = −58 dBm). This isbecause of the failure in the channel estimation. On the other

hand, more than 90% detection ratio is obtained even withsmall d when the noise power is suﬃciently small. This indicates the proposed arrangement is eﬀective in downsizing
the antenna system.
Figure 5(b) shows the channel correlation distribution
for arrangement A. Here, d = 0.5λ0 , h = 1.0 m, X = 3.9 m,
σ2n = −78 dBm. The antenna location in y-axis is Y = 3.6 m.
The axes indicates the position of the human body in theroom, and the intensity of ρ is shown in gray scale. The
bright color means the place where the correlation is lowered by the human, and the intrusion can be easily detected
at this place. On the other hand, the undetectable place isindicated by the mark, ‘’. It can be found that the correlation at the location around the antenna is lowered compared to that at others. Besides, the overall value of ρ isquite high since the transmitting and receiving antennas areplaced together and the strong direct paths from the transmitting antennas to receiving antennas governs the reception power. This can be understood from (3) since the varying component in the channel matrix, Hob becomes smalland Hob approaches Hno . In this situation, the thresholdvalue, ρt , also approaches 1. The important thing is the detection is made when the power of the varying component
in the channel matrix suﬃciently exceeds the noise component, Hw . Hence, the high correlation value does not always
mean poor detection performance. Here, the threshold valueof the detection was ρt = 0.9999649.
Figure 6 shows the detection rate versus the antenna location, X. Here, the spacing, d, is set to 0.5λ0 , the height,d, is 1.0 m, and the antenna location in y-axis is Y = 3.6 m.
This result shows that the detection rate is almost independent of the antenna location, X. This is because many paths
exist in this environment and some of them always illuminate the human body even when the antenna is placed at thevarious positions. More than 90% of the detection rate isachieved when σ2n = −78 dBm.
Figure 7 shows the analysis results for arrangement B.
In this model, the locations of the antennas are at X = 0.6 m
and 7.6 m, and height is h = 1.0 m. A set of the transmitting and receiving antennas is placed at the one side of theroom and another set of the antennas is placed at anotherside. Here, D (D = 7 m) represents the distance between
two sets of the antennas, and d represents the distance between the transmitting and receiving antennas in each set.

HONMA et al.: COMPACT ANTENNA ARRANGEMENT FOR MIMO SENSOR IN INDOOR ENVIRONMENT

2495

Fig. 7 Detection characteristics (arrangement B, 2.4 GHz): (a) Detection
rate versus d, (b) Distribution of channel correlation.

Fig. 8 Detection characteristics (conventional arrangement C, 2.4 GHz):(a) Detection rate versus d, (b) Distribution of channel correlation.

Figure 7(a) shows the detection rate versus the antenna spacing, d, where all of the simulation condition except the antenna arrangement is given identically to that in Fig. 5. Interestingly, it can be seen that the detection rate is almost
independent of d. This means the antenna spacings between
the transmitting antennas as well as between the receiving
antennas are always around 7 m and it is suﬃciently large
for MIMO sensor. For σn 2 = −78 dBm, 100% of the detection rate is obtained independently of d. Even though
two locations for antennas are required for arrangement B, a
compact antenna configuration can be provided by making
d small.
Figure 7(b) shows the channel correlation distribution
for arrangement B. Here, d = 0.5λ0 , and σ2n = −78 dBm.
The other conditions are identical to that in Fig. 5(b). It canbe seen that the correlation is greatly lowered along the lines
between the Tx.1 and Rx.2. This is because the human bodyobstructs the direct paths. Similarly, the correlation is lowered along the once-reflected path by way of either side of
the wall. As seen here, the detection is easily made when thetarget obstructs these strong paths. Furthermore, a large reduction in the channel correlation is observed even aroundthe walls, like x = 0.5, 7.5 m. This is because of the existence of the round-trip wave between walls. Therefore,
this arrangement well covers even at the corners, and thedetection rate is 100% in this case. Besides, the overall correlation value is high similarly to arrangement A, since thereceiving antennas have strong wave from the neighboringtransmitting antennas. Here, the threshold value is set toρt = 0.9999745.
Figure 8 represents the results of the arrangement C,
i.e., the conventional one. In this case, the transmitting
and receiving antennas are placed on the planes at X =0.6, 7.6 m, respectively, and their height is h = 1.0 m. Here,the spacing between the transmitting antennas and that between receiving antennas are set to be identical, and it is represented by d. D represents the distance between two arrays,
and it is set to 7 m. Figure 8(a) shows the detection rate versus the antenna spacing, d. The other parameter excluding
the antenna arrangement is set to identical to the simulation

IEICE TRANS. COMMUN., VOL.E96–B, NO.10 OCTOBER 2013

2496

Fig. 9 Detection rate versus antenna height (d = 0.5λ0 , σ2n = −78 dBm,
W x × Wy × Wz = 7.8 × 6.8 × 2.5 m3 , 2.4 GHz).

Fig. 11 Detection rate versus noise power for large room (W x ×Wy ×Wz =15.6 × 13.6 × 2.5 m3 , 2.4 GHz).

Fig. 10 Detection rate versus noise power for small room (W x × Wy ×
Wz = 7.8 × 6.8 × 2.5 m3 , 2.4 GHz).

for the proposed arrangements A and B. From this result, it
can be seen that small d yields low detection rate. Whend = 0.5λ0 and σn 2 = −78 dBm, the detection rate was 92%.
Figure 8(b) shows the distribution of the correlation coeﬃcient of the arrangement B when d = 0.5λ0 and σ2n =−78 dBm. It is found that the bright spots appear on the direct and once-reflected paths similarly to the arrangement
B. However, the undetected spots appear at the both sides of
the room. This is because not so many paths distribute at thecorners of the room and these areas become the dead zone.
In the arrangement C, the distance between transmitting andreceiving antennas is large compared with the other arrangements and this yields low SNR. The observed SNR is 25 dB
and the channel correlation is ρt = 0.9993874. The correlation value tends to become lower than that in arrangements
A and B, yet the threshold value also becomes low becauseof the low SNR. Hence, this causes the detection failures insome cases.
Figure 9 depicts the detection rate versus the antennaheight. Here, the antenna spacing, d, is set to 0.5λ0 , andaverage noise power is −78 dBm. It is clearly seen that thedetection rate deteriorates when the antenna is higher thanhuman body, whose height is 1.7 m. This tendency is observed in all three arrangements, and it is found that the antenna needs to be located lower than the height of the humanbody.
The detection rates versus the noise power with various
antenna spacings are evaluated for two sizes of the room.
Figures 10 and 11 indicate the detection rate for small andlarge rooms, respectively. Also, the results (a), (b), and (c)correspond to the antenna spacings, 6.25, 200, and 400 cm,
respectively. From these results, it can be seen that the arrangement B yields the highest detection rate in most cases.
The detection rate of the arrangement B with d = 6.25 cm
is comparable to that of the arrangement C with d = 400 cm

HONMA et al.: COMPACT ANTENNA ARRANGEMENT FOR MIMO SENSOR IN INDOOR ENVIRONMENT

2497

Fig. 12 Detection rate versus noise power for small room (W x × Wy ×
Wz = 7.8 × 6.8 × 2.5 m3 , 5.2 GHz).

for both room sizes. Even though the detection rate of thearrangement A is lower than that of B, the arrangement A
achieves the detection rate as high as the arrangement C,
and oﬀers the smallest size of the antenna. It is also foundthat the MIMO sensor at the large room requires small noise
power and this comes from the low reception power causedby the large path loss. The required noise level at the large
room is lower by approximately 6 dB than that at the small
room in this case.
The eﬀect of the frequency on the detection performance is evaluated to consider the feasibility of the proposed antenna arrangements. Figures 12 and 13 show thedetection rates for two types of the rooms when the frequency is set to 5.2 GHz. Here, the results (a), (b), and (c)correspond to the antenna spacings, 6.25, 200, and 400 cm,
respectively. Even though the frequency is much higher thanthat in Figs. 10 and 11, very similar tendency in the detection characteristics is observed. However, the required noiselevel is about 7–10 dB lower than that for 2.4 GHz. This isbecause of the large path loss at 5.2 GHz. Nevertheless, thearrangement B yields almost equal or higher detection ratio
than arrangement C does for both room sizes. Though thedetection ratio of the arrangement A is lower than the others when the antenna spacing, d, is large, the detection ratio

Fig. 13 Detection rate versus noise power for large room (W x ×Wy ×Wz =15.6 × 13.6 × 2.5 m3 , 5.2 GHz).

comparable to the others can be attained when d = 6.25 cm.
It is considered that the distributed antenna arrangement, i.e.
method B, is suitable for the situation where the path loss islarge.
5.

Conclusion

In this paper, the antenna arrangements for the MIMO sensor have been proposed. In these arrangements, the transmitting and receiving antennas are placed together. The numerical analysis of the indoor propagation based on the raytracing method is carried out. The intrusion detection performance with the various antenna arrangements are evaluated for the human positions all over the room. The numerical analysis results showed that the proposed arrangements can achieve comparable or higher detection rate thanthe conventional arrangement when the antenna spacing islimited. Especially, the detection rate of the proposed arrangement B is equal or superior to that of the conventionalarrangement with large antenna spacing, such as 400 cm,
even when the antenna spacing is 6.25 cm. This tendency isobserved even for the situation, where the frequency is highor the room size is large. From these results, it is found thattwo proposed antenna arrangements are eﬀective in down-

IEICE TRANS. COMMUN., VOL.E96–B, NO.10 OCTOBER 20132498

sizing the antenna configurations of MIMO sensor without
paying any cost of the detection rate.
Acknowledgments
This work is supported in part by the Center for Revitalization Promotion of the Japan Science and Technology
Agency (JST), and JSPS KAKENHI (23500549).
References[1] A. Hatami and K. Pahlavan, “In-building intruder detection for
WLAN access,” IEEE Pos., Loc. and Nav. Symp., pp.592–595, April
2004.
[2] M. Nishi, S. Takahashi, and T. Yoshida, “Indoor human detection
systems using VHF-FM and UHF-TV Broadcasting waves,” Proc.
2006 IEEE Int. Symp. Personal Indoor Mobile Radio Commun.
(PIMRC’06), Sept. 2006.
[3] Y. Okugawa, Y. Akiyama, H. Yamane, and K Tajima, “Study on an
intrusion detecting method using TV broadcasting waves,” Proc. of2007 Int. Symp. Antenna Propagat. (ISAP 2007), Nov. 2007.
[4] S. Ikeda, H. Tsuji, and T. Ohtsuki, “Indoor event detection with signal subspace spanned by eigenvector for home or oﬃce security,”
IEICE Trans. Commun., vol.E92-B, no.7, pp.2406–2412, July 2009.
[5] N. Honma, T. Sugiura, K. Nishimori, H. Sato, and Y. Tsunekawa,“MIMO sensor — Experimental channel characterization in indoor
environment,” Proc. 2010 Int. Symp. Antenna Propagat. (ISAP2010), Nov. 2010.
[6] K. Nishimori, Y. Koide, N. Honma D. Kuwahara, H. Yamada, and
H. Makino, “MIMO Sensor — Eﬀectiveness of distributed MIMO
antenna configuration,” Proc. 2010 Int. Symp. Antenna Propagat.
(ISAP 2010), Nov. 2010.
[7] K. Nishimori, Y. Koide, D. Kuwahara, N. Honma, H. Yamada, and
H. Makino, “MIMO sensor — Evaluation on antenna arrangement,”
5th European Conf. Antennas and Propagat. (EuCAP 2011), Electric
Proc. EuCAP 2011, April 2011.
[8] K. Nishimori, K. Ushiki, and N. Honma, “Experimental evaluation
toward transmit and receive diversity eﬀect in SIMO/MIMO sensors,” 6th European Conf. Antennas and Propagat. (EuCAP 2012),
Electric Proc. EuCAP 2012, Post2-30, March 2012.
[9] A. Kumakura, H. Yamada, K. Nishimori, and Y. Yamaguchi, “Fundamental study on channel model of MIMO sensor for event detection,” Proc. 2011 Int. Symp. Antenna Propagat. (ISAP 2011), Oct.
2011.
[10] N. Honma, K. Nishimori, H. Sato, and Y. Tsunekawa, “Compact antenna arrangement for MIMO sensor in indoor environment,” Proc.
2012 Int. Symp. Antenna Propagat. (ISAP 2012), Nov. 2012.

Naoki Honma
received the B.E., M.E., andPh.D. degrees in electrical engineering from Tohoku University, Sendai, Japan in 1996, 1998,
and 2005, respectively. In 1998, he joined the
NTT Radio Communication Systems Laboratories, Nippon Telegraph and Telephone Corporation (NTT), in Japan. He is now working for
Iwate University. He received the Young Engineers Award from the IEICE of Japan in 2003,
the APMC Best Paper Award in 2003, and theBest Paper Award of IEICE Communication Society in 2006, respectively. His current research interest is planar antennas
for high-speed wireless communication systems. He is a member of IEEE.

Kentaro Nishimori
received the B.E., M.E.,
and Dr.Eng. degrees in electrical and computerengineering from Nagoya Institute of Technology, Aichi, in 1994, 1996, and 2002, respectively. He joined NTT Wireless Systems Laboratories in 1996. He was a visiting researcher at
the Center for TeleInFrastruktur, Aalborg University, Denmark in 2006. He received theYoung Engineers Award from the Institute ofElectronics, Information and Communication
Engineers (IEICE) of Japan in 2001 and Young
Engineer Award from IEEE AP-S Japan Chapter in 2001. His current research interests are multi-user MIMO systems and cognitive radio systems.
He is a member of IEEE.

Hiroaki Sato
received the B.E. degree inelectronic engineering from Utsunomiya University, Utsunomiya, Japan, in 1990 and the
M.E. and Ph.D. degrees in electrical and communication engineering from Tohoku University, Sendai, Japan, in 1992 and 1995, respectively. In 1995, he joined ONO SOKKI CO.,LTD., Yokohama, Japan. Since 2002, he has
been with the Faculty of Engineering, Iwate
University. His current research interests include digital signal processing and digital system control. He is a member of the Institute of Electronics, Information
and Communication Engineers of Japan.

Yoshitaka Tsunekawa
received the B.E.
degree from Iwate University, Morioka, Japan,
in 1980 and the M.E. and the Doctor of Engineering degrees from Tohoku University, Sendai, Japan, in 1983 and 1993, respectively. Since
1983, he has been with the Faculty of Engineering, Iwate University, where he is now a professor at the Department of Electrical Engineeringand Computer Science. His current research interests include digital signal processing and digital control. He is a member of the Instituteof Electronics, Information and Communication Engineers of Japan, andIEEE.