IEICE TRANS. COMMUN., VOL.E99–B, NO.1 JANUARY 2016

69

PAPER

Special Section on Recent Progress in Antennas, Propagation and Wireless Systems Related to Topics in ISAP2014

Four-Stream Parallel Transmission for Short-Range MIMO Using
Only Passive Analog Components
Kentaro MURATA†a) , Student Member, Naoki HONMA†† , Member, Kentaro NISHIMORI††† , Senior Member,David M. KLYMYSHYN†††† , Nonmember, and Hisashi MORISHITA† , Fellow

SUMMARY An analog-beamforming-based eigenmode transmission
technique is proposed that employs a network of interconnected 180degree hybrid couplers at both transmitting and receiving sides of a planesymmetrically configured short-range MIMO system. This technique canorthogonalize MIMO channels regardless of array parameters such as antenna spacing and Tx-Rx distance, provided the MIMO array is symmetric.
For verifying the eﬀectiveness of the proposed technique in channel orthogonalization, an experiment is conducted using a 4×4 MIMO array consisting of microstrip antennas and cascade-connected rat-race hybrid couplers.
The results indicate a reduction in interference by approximately −28.3 dB
on average compared to desired signal power, and the ability to realize fourstream parallel MIMO transmission by using only analog passive networks.
The proposed technique can achieve channel capacity almost equivalent tothat of eigenbeam space division multiplexing with ideal digital beamforming.
key words: short-range MIMO, eigenmode transmission, 180-degree hybrid coupler

1. Introduction
Recently, contactless card services have become very popular in transportation and electronic payment systems. Moreover, radio frequency identification (RFID) technology is
finding increased application in manufacturing and logistics [1]. As typified by these applications, short-range communication technology is playing an indispensable role intoday’s ubiquitous society. With the rapid developmentof infrastructures for machine-to-machine communication,
cloud-computing-based content distribution services such asdata downloading from digital KIOSKs have been commercialized, and higher-speed short-range wireless communication capable of large-capacity data transfer such as music, movies and images will be highly demanded in the near
future. However, since conventional short-range communication schemes used for RFID are limited to lower-capacity
applications, communication speed is a critical bottleneck
hindering large-capacity communications. Currently, theManuscript received April 6, 2015.
Manuscript revised August 17, 2015.
†
The authors are with Graduate School of Science and Engineering, National Defense Academy, Yokosuka-shi, 239-8686
Japan.
††
The author is with Faculty of Engineering, Iwate University,
Morioka-shi, 020-8551 Japan.
†††
The author is with Faculty of Engineering, Niigata University,
Niigata-shi, 950-2181 Japan.
††††
The author is with Department of Electrical Engineering, University of Saskatchewan, Canada.
a) E-mail: ed14002@nda.ac.jp
DOI: 10.1587/transcom.2015ISP0028

utilization of ultra wide band and millimeter wave technologies are a focus for large-capacity short-range wireless communications with maximum data rates reaching up to multiple Gbits/s [2].
Another alternative is to employ multiple-input
multiple-output (MIMO) technology. Short-range MIMO
(SR-MIMO) is an emerging utility form of MIMO technology, expected to be applied, for example, to a through-thewall repeater [3], [4]. Conventionally, MIMO systems areoperated in rich spattering environments and improve wireless communication speed and quality by the use of diversity eﬀects and spatial multiplexing [5]. In contrast, Paulaj
pointed out that, even when the line-of-sight (LOS) component is dominant in a MIMO channel, a channel capacity higher than the ergodic capacity of a traditional MIMO
scheme operated in a rich-scattering environment can beachieved under the specific condition that the LOS channel
components are initially uncorrelated. This hints at the possible eﬀectiveness of LOS MIMO communication from thelinear algebraic viewpoint [6].
Considering this point, optimal array designs for LOS
MIMO that provide uncorrelated channels were investigatedbased on plane and spherical wave theories. For instance in[7]–[10], MIMO array antenna spacing is regarded as a key
factor to realize uncorrelated channels when Tx-Rx distanceis fixed. It was proven that a full-rank channel matrix canbe realized by arranging MIMO array antenna elements at
optimal spacing intervals. This research confirms the hypothesis presented in [6] and validates the eﬀectiveness of
LOS MIMO, in the other words, SR-MIMO from an electromagnetic perspective.
As the concept of SR-MIMO became popular, researchtackled challenges to enhance communication performance.
In [11] and [12], propagation characteristic improvement
techniques using scatterers such as reflectors and metal
wires were proposed. Although these approaches are somewhat straightforward, signal to noise ratio (SNR) can be substantially improved by controlling back and side lobes andbeam width, simply by optimizing the sizes and positionsof scatterers around an SR-MIMO array. From these earlier
studies including [6]–[12], a suitable design method of array
configuration for SR-MIMO systems has matured.
A current focus in practical use of SR-MIMO technology involves channel multiplexing with simpler hardwaresoftware configurations. Broadly, conventional channel
multiplexing techniques for SR-MIMO are classified intoc 2016 The Institute of Electronics, Information and Communication Engineers
Copyright IEICE TRANS. COMMUN., VOL.E99–B, NO.1 JANUARY 201670

three categories.
The first category proposes a multiplexing techniqueutilizing orthogonal polarizations. In MIMO communications, it is widely accepted that polarization waves allow spatially uncorrelated MIMO channels in a far region. For example, when triple polarizations are employed,
an ideal three-fold channel capacity is expected comparedwith a single polarization [13]. In [14] and [15], dualpolarization multiplexing techniques for SR-MIMO werereported. These studies clarified that lower order eigenvalues of the channel matrix were significantly improved by applying dual-polarization that contributed to the channel capacity improvement. The use of a dual-polarized microstrip
antenna (MSA) also helped to miniaturize a MIMO arraysystem. As these findings suggested, it was verified thatpolarization multiplexing was also eﬀective in SR-MIMO
communication.
In the second category, a channel multiplexing methodthat used electric and magnetic modes in a near-field region as distinct information carriers was proposed [16], [17].
This method exploits the characteristic of a reactive nearfield where attenuation rates of electric and magnetic fields
radiated from small electric and magnetic dipoles are diﬀerent. This multiplexing mechanism is completely diﬀerent
from polarization.
The greatest benefit of the first two categories is that,since only polarized or electric/magnetic antennas are used,
multiplexed channels can be easily constructed by an extremely simple system configuration without specialized RF
front-ends for signal separation. However, the maximum
level of multiplexing possible is electromagnetically limited
to three (by tri-polarization) and two (by electric and magnetic fields). Therefore, a diﬀerent approach must be taken
for multiplexing channels of the same polarizations or fields.
The third category involves analog-beamformingbased decoding techniques. Usually, short-range communication links are static since Tx and Rx antennas exist in
the LOS environment. Therefore, propagation channels are
uniquely determined, that enables a fixed-weight decoding.
In the previous studies, analog decoding techniques using
passive circuit elements (such as dividers, phase shifters
and attenuators) [18], [19], sub-arrays [20] and orthogonaldirectivity antennas [21] were proposed. The merits of theuse of analog-beam forming are: 1) high frequency utilization eﬃciency; and 2) low power consumption due tobroadband characteristics and passive analog circuits. However, a problem with analog-beamforming is that the array
displacement causes a capacity degradation since a fixedweight analog beamformer cannot form an optimal beamadaptively in response to the array displacement unlike withconventional digital beamforming.
To solve this problem, the authors proposed a novel
eigenmode transmission technique using only 180-degreehybrid couplers [22]. In this technique, as long as the symmetry of the MIMO array configuration is retained, it is possible to orthogonalize MIMO channels regardless of arrayparameters such as the type of antenna, antenna spacing andTx-Rx distance. Therefore, this technique is robust to specific direction displacements and specific rotation angles ofthe MIMO array.
In related work, the authors also proposed a simultaneous matching technique for SR-MIMO considering the influence of the proximally-positioned Tx and Rx arrays [23],and this novel matching theory is founded upon the conceptof the proposed channel orthogonalization technique. After the channel orthogonalization, the SR-MIMO system canbe regarded as multi independent single-input single-output(SISO) systems. Then corresponding pairs of Tx and Rx
ports can be simultaneously matched by applying conjugateimage-impedance theory to each orthogonalized SISO system individually, that extracts the maximum channel capacity that an arbitrary SR-MIMO potentially possesses. Furthermore, it was reported that although the application limitation of the channel orthogonalization technique was up
to 4×4 MIMO when Tx and Rx arrays faced each other(usual for short-range communication), this approach could
be extended to a massive SR-MIMO system consisting ofmany more antennas. Combining this technique with digital
beamforming results in a considerable reduction of calculations required for eigenbeam space division multiplexing(E-SDM) [24].
In our previous work, it was demonstrated experimentally that this base channel orthogonalization techniqueachieved a channel capacity almost equivalent to that ofdigital-beamforming-based E-SDM in a 2×2 SR-MIMO
system [25], [26]. However, although the extension method
to more than a 2×2 SR-MIMO was theoretically established,
the eﬀectiveness of it was not experimentally demonstrated.
The purpose of the paper is to validate the eﬀectiveness of the proposed technique in a 4×4 SR-MIMO system operating in an actual environment. In the experiment,
MSA arrays and cascade-connected networks consisting offour rat-race couplers were used for setting up the proposed
SR-MIMO system. In this paper, some experimental results
are presented, and the channel orthogonalization eﬀect andchannel capacity improvement are quantitatively evaluated.
These results confirm that the four-stream parallel MIMO
transmission can be successfully achieved using fairly simple analog passive networks. Finally, this paper proves thatthe proposed technique of analog-based E-SDM (AE-SDM)
can achieve a channel capacity almost equivalent to that ofdigital-based E-SDM (DE-SDM) by ideal beamforming in a
4×4 SR-MIMO system.
2. Theory of Proposed TechniqueIn this section, the extension method of AE-SDM to a 4×4
SR-MIMO system is explained. Details on the fundamental
theory of the proposed technique can be found in [22].
A 4×4 SR-MIMO system with a cuboidal configuration, symmetrical with respect to the vertical and horizontal
reference planes is shown in Fig. 1. In the system, transmitting antennas Tx 1∼4 are connected to Tx ports #1∼#4,
and receiving antennas Rx 1∼4 are connected to Rx portsMURATA et al.: FOUR-STREAM PARALLEL TRANSMISSION FOR SHORT-RANGE MIMO USING ONLY PASSIVE ANALOG COMPONENTS

71

equally split to output ports OUT 1 and OUT 2 in phase,
while a signal input to IN 2 is output in reversed phase [27].
Taking this matter into consideration, the transmission matrix between inputs and outputs of an ideal CCC, SCCC , isexpressed as
⎡
⎤
1
1 ⎥⎥
⎢⎢⎢ 1 1⎥⎢
1 ⎢⎢ 1 1 −1 −1 ⎥⎥⎥⎥⎥⎥ .
SCCC = − ⎢⎢⎢⎢
(3)
2 ⎢⎢⎣ 1 −1 1 −1 ⎥⎥⎥⎦
1 −1 −1 1
Fig. 1

Plane-symmetrically configured 4×4 SR-MIMO system.

Fig. 2

Symbol of an 180-degree hybrid coupler.

An ideal hybrid coupler has neither reflection nor mutual
coupling in both inputs and outputs, and this is also true for
CCC.
Two CCCs are connected to both Tx and Rx sides of theplane-symmetrically configured 4×4 SR-MIMO system. Inputs IN 1∼4 and outputs OUT 1∼4 of Tx CCC are connected
to Tx ports #1∼#4 and transmitting antennas Tx 1∼4, respectively. Inputs IN 1∼4 and outputs OUT 1∼4 of Rx CCC
are connected to receiving antenna Rx 1∼4 and Rx ports#5∼#8, respectively. Since the networks have no reflection
or mutual coupling, the complete cascade-connected transmission matrix can be expressed as the product of the transmission matrices of the individual networks [28]. Thus, theideal channel matrix of the whole SR-MIMO system including the cascade-connected Tx and Rx CCCs, Schl , is givenasSchl = SCCC Schl SCCC .

Fig. 3

Network configuration of a cascaded-connected couplers.

#5∼#8. The channel matrix of the system, Schl , is expressedwith port numbers as⎡⎤⎢⎢⎢ S 51 S 52 S 53 S 54 ⎥⎥⎥⎢⎢⎢ S
S 62 S 63 S 64 ⎥⎥⎥⎥⎥
Schl = ⎢⎢⎢⎢ 61(1)⎢⎢⎣ S 71 S 72 S 73 S 74 ⎥⎥⎥⎥⎦
S 81 S 82 S 83 S 84
where, for example, S 51 is a channel between Tx port #1 andRx port #5.
Due to the symmetry of the array configuration, channels between 1) ports facing each other, 2) ports existing
across the vertical plane, 3) ports existing across the twoplanes and 4) ports across the horizontal plane are equal andreplaced with α, β, γ and δ, respectively. This makes⎡⎤⎢⎢⎢ α β γ δ ⎥⎥⎥⎢⎢⎢ β α δ γ ⎥⎥⎥⎥⎥
Schl = ⎢⎢⎢⎢
(2)⎢⎢⎣ γ δ α β ⎥⎥⎥⎥⎦
δ γ β αa regular symmetrical matrix.
Cascade-connected couplers (CCC) used in the propose technique are constructed by cascade-connecting four
hybrid couplers as shown in Fig. 3. Note that input ports IN
1 and IN 2 of a single hybrid coupler shown in Fig. 2 correspond to even and odd modes. A signal input to IN 1 is(4)

By substituting (2) and (3) into (4), we obtain
⎡ 


 ⎤
S 53
S 54
⎢⎢⎢ S 51 S 52
⎥⎥



 ⎥
⎢⎢⎢⎢ S 61
⎥⎥⎥⎥
S 62
S 63
S 64

Schl = ⎢⎢⎢ 
⎥⎥


 ⎥
S
S
S
S
⎢⎢⎣ 71
⎥
72
73
74 ⎥



 ⎦
S 81 S 82 S 83 S 84⎡00⎢⎢⎢α + β + γ + δ⎢⎢⎢
0α+β−γ−δ0= ⎢⎢⎢00
α−β+γ−δ
⎣
0

0

0

⎤

0
⎥⎥⎥
⎥⎥⎥
0
⎥⎥⎥
0
⎦
α−β−γ+δ(5)

and the channel matrix is diagonalized. That means that four
orthogonalized streams are formed between corresponding
pairs of Tx and Rx ports, and E-SDM is realized.
As discussed above, orthogonalized channels can beformed between corresponding Tx and Rx ports using
CCCs, and the proposed technique allows E-SDM using
only analog passive networks without digital beamforming.
For reference, this technique is valid regardless of antenna
spacing and Tx-Rx distance as long as the symmetry of thearray configuration is retained.
3. Experimental Results
In this section, evaluation results on the eﬀect of channel
orthogonalization and the channel capacity improvement by
the proposed technique are shown.

IEICE TRANS. COMMUN., VOL.E99–B, NO.1 JANUARY 201672

Fig. 4

Configuration of a 4×4 MSA SR-MIMO array.
Fig. 6

Fig. 5Four-element MSA array.

3.1 Experimental Setup
3.1.1 Array Configuration
In Fig. 4, the configuration of the experimental 4×4 SRMIMO array is illustrated. Both Tx and Rx arrays consistof four identical MSAs. Figure 5 is a picture of a fabricated
MSA array on a polytetrafluoroethylene (PTFE) substratewith thickness of 1.56 mm and relative permittivity of 2.2.
The size of the substrate is as shown in the figure. Sucha large ground plane has two potential eﬀects 1) to reduce
scattering waves by screening the objects behind the arraysuch as CCC and cables, and 2) to assure a highly accurate symmetry by employing the co-planar array configuration. However in principle, the size of the ground plane
does not aﬀect the proposed channel orthogonalization on
the condition that the plane symmetry of the SR-MIMO array configuration is kept. Actually, a suﬃcient channel orthogonality was experimentally confirmed even by using arrays consisting of separated MSAs with small ground plane[25], [26]. The size of each MSA and its feeding point are
optimized so that a single MSA assumed on the infinite dielectric substrate is fully matched at the center frequency ofFrequency responses of S-parameter.

2.5 GHz. The array has eight screw holes for fixture mounting (see Fig. 10). In terms of array parameters, antenna spacing, d, is defined as the distance between the centers of theMSAs, and Tx-Rx distance, D, is defined as the distance
between the grounds of Tx and Rx arrays. In order to evaluate antenna spacing characteristics, three types of the arrays
whose d is 0.8, 1.0 and 1.2 λ were fabricated, where λ is thefree-space wavelength at the center frequency.
For reference, the S-parameter frequency responses of
the array with d = 1.0 λ are shown in Fig. 6. In the figure, characteristics for only MSA 1 are shown because of
the structural symmetry, and S 11 , S 21 , S 31 and S 41 represent the reflection of MSA1, and the couplings with MSA
2∼4, respectively. Bold and thin lines are measurement andsimulation results, respectively, and in the simulation, an infinite dielectric plane was assumed as a dielectric layer of
the array substrate for the convenience of calculation. For
electromagnetic analysis, IE3D was used [34]. From the figure, although it is observed that the measurement resonant
point is shifted to lower frequency compared with that ofsimulation because of the diﬀerence in dielectric layer, thereflection is −22.7 dB, suppressed to a satisfactory extent at
the center frequency. Also, couplings with the other element
are reduced to under −26.5 dB at the center frequency. Likewise, for the arrays with d = 0.8 and 1.2 λ, it is confirmedthat reflections and couplings are held under the suﬃciently
low levels of −13.5 and −23.4 dB, respectively, therefore,
these characteristics are omitted from the paper.
Additionally, Figs. 7(a) and (b) show E- and H-plane(zx- and xy-plane) radiation patterns of MSA1 of the arraywith d = 1.0 λ; those of MSA2∼4 should be symmetrical tothat of MSA1 so they are omitted. The array exists right on
the yz-plane and its center is located at the origin of the coordinate. θ and φ are defined as the right-handed angle fromz-axis and the left-handed angle from x-axis, respectively. In
the figures, measured Eθ and Eφ components are normalizedby maximum Eθ on each plane, and plotted with circle andsquare markers, respectively. Also, simulated Eθ is normalized by its maximum and shown in bold line while simulated
Eφ is omitted since it is negligibly small. From the experimental results, the peak gains of E- and H-plane patterns

MURATA et al.: FOUR-STREAM PARALLEL TRANSMISSION FOR SHORT-RANGE MIMO USING ONLY PASSIVE ANALOG COMPONENTS

73

Fig. 7

Fig. 8Fabricated rat-race.

Fig. 9Fabricated CCC.

Radiation pattern.

are 7.87 dBi at θ = 95.4 degree and 8.18 dBi at φ = 358.4
degree, respectively. And, their half-value angles are 91.2
and 79.2 degrees, respectively. The figures show that theexperimental patterns are in good agreement with those of
the simulation. Note, however, that these far-field characteristics are not necessarily directly-reflected in the following
analysis results for such short-range cases.
3.1.2 Cascade-Connected Couplers
Rat-race hybrid couplers with details shown in Figs. 8 and 9
are used for implementation. λeﬀ (87.8 mm) is the eﬀective
wavelength at the center frequency calculated considering
the thickness and the relative permittivity of the dielectric
substrate [29]. The width of the line of the rat-race,√ wr , wasdetermined for a characteristic impedance of 2Z0 basedon [29], where Z0 is 50 Ω. The fabricated hybrid coupler
has connectors on its back side, and is connectable to MSA
arrays and measuring instruments via flexible cables. A fabricated CCC configured with four concatenated rat-races isshown in Fig. 9. In Table 1, the input-output characteristicsof the fabricated CCC at the analysis frequency are shown.
Table 1(a) shows amplitude characteristics in dB. Althougha slight loss occurs in each component, the input signal isequally split to four outputs. Table 1(b) shows phase characteristics. The absolute value of the relative phase of each
output signal to OUT 1 is displayed in degrees. From the table, it is found that phase characteristics with low error are

Table 1

Input-output characteristics.

Unit: dB
OUT 1
OUT 2
OUT 3
OUT 4

(a) Amplitude
IN 1
IN 2
IN 3
−6.25 −6.24 −6.27−6.21 −6.22 −6.23−6.27 −6.22 −6.33−6.26 −6.24 −6.25

IN 4
−6.24
−6.24
−6.26
−6.23

Unit: deg
OUT 1
OUT 2
OUT 3
OUT 4

(b) Relative phase
IN 1
IN 2
IN 3
0
0
0
0.27
0.10
179.760.82 179.20
0.53
1.09 179.02 179.13

IN 4
0179.88179.520.74

obtained, compared to the ideal CCC shown in (3).
Although such a bulky circuit structure was used in theexperiment for fundamental performance validation of the
proposed technique, further miniaturization of CCC is necessary from a practical application standpoint. In [30] and[31], distributed circuits similar to CCC used in the proposed technique are presented, using 3-dB quadrature hybrids and delay lines as a substitute for 180-degree hybrid

IEICE TRANS. COMMUN., VOL.E99–B, NO.1 JANUARY 201674

Fig. 10

Picture of an experimental setup.

couplers. In [32], a lumped-element quadrature coupler fabricated using deep X-ray lithography process is presented,
enabling approximately 85% area reduction compared to aconventional quadrature hybrid. Thus, drastic miniaturization of the proposed system configuration can be expected
through the use of novel circuit structures and fabrication
techniques.
3.1.3 SR-MIMO System Configuration
Figure 10 shows the 4×4 SR-MIMO system configuration
used in the experiment. The experiment was conducted in areverberation room. Tx and Rx arrays were fixed on acrylic
fixtures and faced each other. The Tx and Rx fixtures were
designed so either could be slid along the Tx-Rx distancedirection to obtain the MIMO channel characteristics versus
distance. In the experiment, two patterns of MIMO channels were measured; first, the channel matrix was obtained
when a measuring instrument was directly connected to the
SR-MIMO array without CCCs. Second, the channel matrix was obtained with CCCs connected as shown in Fig. 10.
The observed frequency range is ±50 MHz from the center
frequency, and the noise level is approximately −90 dBm,
which is almost equal to that at room temperature (300 K)
calculated by the Johnson-Nyquist formula [33].
3.2 The Eﬀect of a Channel Orthogonalization
In order to exhibit the eﬀect of the channel orthogonalization, the amplitudes of MIMO channel components measured by a vector network analyzer (VNA) are visualized ingray scale in Fig. 11. In the experiment, the Tx and Rx arrays whose d is 1.0 λ were used and D was set to 1.0 λ. In
the figure, the amplitude is shown in dB, and the upper andlower limits are set to 0 and −30 dB, respectively.
Figure 11(a) is an amplitude characteristic without
CCCs, and this figure indicates a regular symmetry expressed as (2) due to the plane-symmetry of the SR-MIMO
system configuration. In the figure, diagonal components
represent desired signal channels between corresponding Tx
and Rx ports, while non-diagonal components in each row
represent interference channels from non-corresponding Tx
ports to a certain Rx port. Hence, in the case that CCCs are

Fig. 11

Visualization of channel components.

not connected, interferences noticeably exist at the similarlevel to signal channels, and because of this, signal to interference and noise power ratio (SINR) in each stream ispoor.
On the other hand, Fig. 11(b) shows a channel characteristic with CCCs. From the figure, it is confirmed that
only diagonal components, or signal channels, remain while
non-diagonal components, or interference channels, are reduced below −30 dB. On the basis of these results, it is confirmed that the proposed technique can reduce interference
from non-corresponding Tx to a suﬃcient extent.
3.3 Signal and Interference Characteristics
In this subsection, signal and interference powers in eachstream are evaluated more quantitatively. In the measurement, the same arrays as described in 3.2 were used, and D
was varied from 0.5 to 2.0 λ at 0.25-λ intervals. For comparison, simulation results are also shown. In the simulation,
the array parameters were set to same values as those in theexperiment, and D was varied over the same range but more
finely at 0.05-λ intervals.
In Fig. 12, three types of signal powers are displayed;

MURATA et al.: FOUR-STREAM PARALLEL TRANSMISSION FOR SHORT-RANGE MIMO USING ONLY PASSIVE ANALOG COMPONENTS

75

the first is a signal power when DE-SDM is applied to anumerically-simulated channel matrix, and defined eigenvalue of a correlation matrix of the channel matrix. The
second is a signal power when DE-SDM is applied toan experimentally-measured channel matrix without CCCs,
and defined in a same manner as the first. The third is asignal power when the proposed AE-SDM is applied, anddefined as the square of the absolute value of a diagonalcomponent in an experimentally-measured channel matrix
with CCCs. These three types of signals are shown withlines, open and filled markers, respectively. Additionally,
the interference when AE-SDM is applied is also shownwith double-lined markers, and defined as the square sumof the absolute value of non-diagonal components in a certain row of the channel matrix. Figures 12(a)∼(d) present
the characteristics of the first to fourth streams, where theorder is determined by the signal level of each stream.
First, in comparison between experimental and simulated signal powers, it is confirmed that experimental values
are somewhat higher than simulated ones as a whole. As
possible causes of that, the following points are cited; 1)
an infinite dielectric plane is assumed in the numerical simulation so that the dielectric loss in the dielectric layer increased, and 2) more multi-paths are expected in the experiment due to the scatterers around the arrays such as fixturesand radiowave absorbers so that signal power is enhanced.
However, both experimental and simulation results show thesimilar increase and decrease tendencies in each stream.
When comparing AE-SDM and DE-SDM, almost thesame characteristics are obtained. The average signal power
deteriorations from the first to fourth streams are extremely
slight over the analysis range and retained −0.69, −0.60,−0.70 and −0.49 dB, respectively. The cause of the deterioration is discussed in detail in Appendix in the end of thepaper.
Focusing on the interference characteristics, it is confirmed that interference power is suppressed under approximately −30 dB over the analysis range for each stream. As aresult, the average signal to interference power ratio (SINR)
is 28.3 dB overall, therefore, favorable channel orthogonalization eﬀect is demonstrated.
3.4 Channel Capacity Characteristics
In this subsection, channel capacity characteristics are evaluated. In the experiment, D was varied over the same range
as 3.3, and the arrays whose d is d = 0.8 and 1.2 λ werealso used aside from d = 1.0 λ. As an evaluation formula,channel capacity is expressed as
C=

NRx


log2 1 + S INR (i)

(6)

i=1

where S INR (i) for ith stream is given as
Fig. 122

Experimental results on signal and interference powers.

S INR (i) =hi,i Pt /NTx2NTxji, j=1 hi, j Pt /NTx + Pn.

(7)

IEICE TRANS. COMMUN., VOL.E99–B, NO.1 JANUARY 201676

In the above equation, hi,i is the ith diagonal component ofa channel matrix and corresponds to a desired signal channel. On the other hand, hi, j is a non-diagonal component ofa channel matrix in the ith row and jth column and corresponds to an interference channel. As for DE-SDM, eigenvalues of a correlation matrix of a channel matrix are substituted into a signal-power term, while an interference-powerterm is zero. NTx and NRx represent the numbers of Tx andRx antennas, respectively, and equal 4 in the experiment.
Pt and Pn represent total transmission power and receiving
noise level, and the ratio of Pt to Pn is 30 dB.
In Fig. 13, channel capacity characteristics are shown.
In the figure, experimental results of DE-SDM, AE-SDM,
and w/o BF are shown with diﬀerent types of markers where
w/o BF is a characteristic when no beamforming is done.
For reference, simulation results are also shown with different types of lines, and as for AE-SDM of simulation, its
capacity is calculated from a numerically-simulated channel matrix multiplied by the transmission matrix of an ideal
CCC given in (3).
First, in terms of the simulation results of DE-SDM
and AE-SDM, the capacity of AE-SDM should theoreticallyagree with that of DE-SDM. However, it is confirmed that
the AE-SDM characteristics unnaturally deteriorate over therange from 0.75 to 1.0 λ. This is caused since the symmetryof the array configuration cannot be perfectly realized due tothe specification of the electromagnetic simulator. As for thereason why the experimental results are slightly higher thanthose of simulation, it is already discussed in the previous
subsection.
Comparisons between AE-SDM and w/o BF over the
analysis range of D when d = 0.8, 1.0 and 1.2 λ are 4.30,
3.78 and 2.75 times on average, respectively, shows thatchannel capacity is drastically improved by the proposed
technique. This also indicates that when antenna spacing issmaller, more capacity improvement is expected since larger
antenna spacing allows channel separation without beamforming, i.e. when antenna spacing is infinite, completelyindependent streams can be formed between corresponding
pair of Tx and Rx antennas.
Finally, experimental results of AE-SDM and DESDM are compared. As well as signal characteristics shownin the previous section, the characteristic deterioration is observed. However, the average capacity deterioration over the
analysis range of D when d = 1.0 λ is only 6.0%, therefore, it is confirmed that E-SDM can be suﬃciently realized by the proposed technique independently of Tx-Rx
distance. Furthermore, although channel orthogonalization
performance is inferior compared to when d = 1.0 λ, capacity deteriorations when d = 0.8 and 1.2 λ are suﬃciently
small, at 12.0% and 11.7%, respectively. From these results,
it is verified that the proposed technique is valid regardlessof not only Tx-Rx distance but also antenna spacing.
Despite the array parameter independence of the proposed channel orthogonalization, channel capacity is highly
dependent upon SR-MIMO array configuration. For example, a smaller antenna spacing compared to Tx-Rx distanceFig. 13

Experimental results on channel capacity.

leads to highly correlated channels, which are not suitable
for space multiplexing. In addition, a strong mutual coupling between the elements causes SNR deterioration. On
the other hand, an infinitely large spacing yields two independent streams but does not always provide the best MIMO
performance in an SR-MIMO system in terms of SNR. SRMIMO has an optimal antenna spacing realizing maximum
channel capacity, and optimal Tx-Rx array configurations
were theoretically discussed in previous studies [7]–[10].
For practical purposes, the antenna spacing of an SR-MIMO
array should be chosen considering a balance between desired communication properties and design size limitation.

MURATA et al.: FOUR-STREAM PARALLEL TRANSMISSION FOR SHORT-RANGE MIMO USING ONLY PASSIVE ANALOG COMPONENTS

77

4. Conclusion
For the purpose of verifying the eﬀectiveness of the proposed technique in a 4×4 SR-MIMO system, an experiment
was conducted using fabricated four-element MSA arrays
and CCCs. This paper details the channel orthogonalizationeﬀectiveness of the proposed technique as determined from
evaluation results.
The results showed that an average interference power
can be reduced to −28.3 dB at the average desired powerover the analysis range. From the channel capacity characteristics versus Tx-Rx distance when antenna spacing is
1.0 λ, it has been confirmed that the average capacity deterioration by the proposed AE-SDM is only 6.0% compared to
DE-SDM, an ideal transmission method for MIMO. Also,
the capacity deteriorations for the other antenna spacings
are approximately 10%, therefore, the proposed techniqueallows E-SDM with satisfactory performance independentlyof antenna spacing and Tx-Rx distance. This has experimentally proven that the proposed technique is also eﬀective ina 4×4 SR-MIMO system.
References[1] R. Want, “An introduction to RFID technology,” IEEE Pervasive
Comput., vol.5, no.1, pp.25–33, Jan. 2006.
[2] C. Park and T.S. Rappaport, “Short-range wireless communications for next-generation networks: UWB, 60 GHz millimeter-wave
WPAN, And ZigBee,” IEEE Wireless Commun., vol.14, no.4,
pp.70–78, Aug. 2007.
[3] N. Honma, K. Nishimori, T. Seki, and M. Mizoguchi, “Short range
MIMO communication,” Proc. 3rd EuCAP, pp.1763–1767, March
2009.
[4] K. Nishimori, N. Honma, T. Seki, and K. Hiraga, “On the transmission method for short-range MIMO communication,” IEEE Trans.
Veh. Technol., vol.60, no.3, pp.1247–1251, March 2011.
[5] G.J. Foschini and M.J. Gans, “On limits of wireless communications
in a fading environment when using multiple antennas,” Wireless.
Pers. Commun., vol.6, no.3, pp.311–335, 1998.
[6] A. Paulaj, R. Nabar, and D. Gore, Introduction to space-time wireless communications, Cambridge University Press 2003.
[7] J.-S. Jiang and M.A. Ingram, “Spherical-wave model for short-range
MIMO,” IEEE Trans. Commun., vol.53, no.9, pp.1534–1541, Sept.
2005.
[8] L. Liu, W. Hong, H. Wang, G. Yang, N. Zhang, H. Zhao, J. Chang,
C. Yu, X. Yu, H. Tang, H. Zhu, and L. Tian, “Characterization ofline-of-sight MIMO channel for fixed wireless communications,”
Antennas Wirel. Propag. Lett., vol.6, no.11, pp.36–39, March 2007.
[9] F. Bøhagen, P. Orten, and G.E. Øien, “Design of optimal highrank line-of-sight MIMO channels,” IEEE Trans. Wireless Commun., vol.6, no.4, pp.1420–1425, April 2007.
[10] I. Sarris and A.R. Nix, “Design and performance assessment of highcapacity MIMO architectures in the presence of a line-of-sight component,” IEEE Trans. Veh. Technol., vol.56, no.4, pp.2194–2202,
July 2007.
[11] H. Hirayama, G. Matsui, N. Kikuma, and K. Sakakibara, “Channel
capacity improvement in short-range MIMO using side and back reflectors,” IEICE Trans. Commun., vol.E94-B, no.5, pp.1280–1283,
May 2011.
[12] D. Zhang, T. Hori, and M. Fujimoto, “Channel capacity improvement in near-field MIMO system using metal wires,” IEICE Trans.
Commun., vol.E96-B, no.5, pp.1141–1148, May 2013.

[13] M.R. Andrews, P.P. Mitra, and R. deCarvalho, “Tripling the capacity of wireless communications using electromagnetic polarization,”
Nature, vol.409, no.6818, pp.316–318, Jan. 2001.
[14] K. Hiraga, T. Seki, K. Nishimori, and K. Uehara, “Eﬀectivenessof short-range MIMO using dual-polarized antenna,” IEICE Trans.
Commun., vol.E95-B, no.1, pp.87–96, Jan. 2012.
[15] K. Hiraga, K. Sakamoto, K. Nishimori, T. Seki, T. Nakagawa, andK. Uehara, “A study of short-range MIMO transmission utilizing
polarization multiplexing for the simplification of decoding,” IEICE
Trans. Commun., vol.E97-B, no.2, pp.459–468, Feb. 2014.
[16] Y. Tak and S. Nam, “Mode-based computation method of channel characteristics for a near-field MIMO,” Antennas Wirel. Propag.
Lett., vol.10, pp.1170–1173, Oct. 2011.
[17] M.A. Nikravan, H.G. Schantz, A.H. Unden, and D.-H. Kwon,“Channel multiplexing technique utilizing electric and magnetic
components of a radio wave,” IEEE Commun. Lett., vol.18, no.2,
pp.317–320, Feb. 2014.
[18] R. Kataoka, K. Nishimori, T. Hiraguri, N. Honma, T. Seki, K.
Hiraga, and H. Makino, “Analog decoding method for simplified short-range MIMO transmission,” IEICE Trans. Commun.,vol.E97-B, no.3, pp.620–630, March 2014.
[19] K. Sakamoto, K. Hiraga, T. Seki, T. Nakagawa, and K. Uehara, “Performance evaluation of short-range MIMO using a method for controlling phase diﬀerence between each propagation channel,” IEICE
Trans. Commun., vol.E96-B, no.10, pp.2513–2520, Oct. 2013.
[20] M. Arai, K. Hiraga, T. Nakagawa, T. Seki, and K. Uehara, “Theoretical and experimental analysis of spatial division using antenna directivities in short-range MIMO transmission,” Electron. Lett., vol.50,
no.2, pp.65–67, Jan. 2014.
[21] K. Hiraga, T. Nakagawa, M. Arai, K. Sakamoto, T. Seki, K. Uehara,and H. Toshinaga, “Study on MIMO transmission using orthogonal
directivities obtained from higher order microstrip antenna modes,”Electron. Lett., vol.50, no.7, pp.562–564, April 2014.
[22] K. Murata, N. Honma, K. Nishimori, and H. Morishita, “Analog
eigenmode transmission for short-range MIMO,” IEEE Trans. Veh.
Technol., 2015 (in press).
[23] K. Murata, N. Honma, K. Nishimori, and H. Morishita, “Bidirectional matching technique for Tx and Rx ports in shortrange MIMO,” Asia-Pacific Microwave Conference (APMC 2014),
pp.498–500, Nov. 2014.
[24] K. Murata, H. Morishita, N. Honma, K. Nishimori, and D.M.
Klymyshyn, “Analog-digital hybrid eigenmode transmission for
massive short-range MIMO,” 2014 IEEE International Workshop on
Electromagnetics (iWEM), pp.223–224, 2014.
[25] K. Murata, N. Honma, K. Nishimori, and H. Morishita, “Analog
eigenmode transmission for 2×2 short-range MIMO,” 2014 IEEE
Antennas and Propagation Society International Symposium (APSURSI), pp.476–477, 2014.
[26] K. Murata, N. Honma, M. Tsunezawa, K. Nishimori, and H.
Morishita, “Experimental evaluation of analog eigenmode transmission for short-range MIMO: Array parameter independency andwideband characteristics,” IEICE Communications Express, vol.4,
no.6, pp.198–204, April 2015.
[27] D.M. Pozar, Microwave Engineering, 4th ed., Wiley, New York,
2012.
[28] G.R. Simpson, “A generalized n-port cascade connection,” MTT-S
International Microwave Symposium Digest, pp.507–509, 1981.
[29] E. Hammerstad and Ø. Jensen, “Accurate models for microstrip
computer-aided design,” MTT-S International Microwave Symposium Digest, pp.407–409, 1980.
[30] J.C. Coetzee and Y. Yu, “Port decoupling for small arrays by meansof an eigenmode feed network,” IEEE Trans. Antennas Propag.,vol.56, no.6, pp.1587–1593, June 2008.
[31] J.H. Kim and W.S. Park, “A Hadamard matrix feed network for adual-beam forming array antenna,” IEEE Trans. Antennas Propag.,vol.57, no.1, pp.283–286, Jan. 2009.
[32] D.M. Klymyshyn, M. Börner, D.T. Haluzan, E.G. Santosa, M.

IEICE TRANS. COMMUN., VOL.E99–B, NO.1 JANUARY 201678

Schaﬀer, S. Achenbach, and J. Mohr, “Vertical high-Q RF-MEMS
devices for reactive lumped-element circuits,” IEEE Trans. Microw.
Theory Techn., vol.58, no.11, pp.2976–2986, Nov. 2010.
[33] M. Vargas and R. Pallàs-Areny, “Thermal noise in a finite bandwidth,” IEEE Instrum. Meas. Mag., vol.4, no.4, pp.23–25, Dec.
2001.
[34] Mentor Graphics. The IE3DTM electromagnetic design. [Online].
http://www.mentor.com/electromagnetic-simulation/[35] K. Hiraga, T. Seki, K. Nishimori, K. Nishikawa, I. Toyoda,
and K. Uehara, “Analyses of antenna displacement in short-range
MIMO transmission over millimeter-wave,” IEICE Trans. Commun., vol.E94-B, no.10, pp.2891–2895, Oct. 2011.

Fig. A· 1

Measurement of through characteristics of Tx-Rx CCCs.

Fig. A· 2

Norm characteristics with insertion loss compensation.

Fig. A· 3

Capacity characteristics with insertion loss compensation.

Appendix:
In this appendix, the causes of the capacity deterioration by
AE-SDM compared to DE-SDM are discussed. The possible main causes are considered as the following two factors;
1) receiving power decrease by insertion loss of CCCs and2) interference increase due to the impurity of the channel
orthogonality. In the following consideration, experimental
and simulation results when d is 1.0 λ are used for the evaluation of each characteristic.
A.1 Receiving Power Decrease by Insertion Loss of CCCs
For the purpose of evaluating the performance deterioration
caused by the insertion loss of CCCs, transmission characteristics when Tx and Rx CCCs directly connected were
measured as shown in Fig. A· 1. In the result, it is found thatthe average transmission power is −0.77 dB per each stream,that should be ideally 0 dB. This deterioration is attributed tocopper and reflection losses of Tx and Rx CCCs and cables
used for connecting CCCs. Thus, characteristics when assuming that insertion loss can be compensated are evaluatedin following parts, and the channel matrix when insertion
loss of CCCs is compensated, Schl, comp , is expressed as
Schl, comp =Schl, meas2

(A· 1)

Schl, thr F /NTx
where Schl, meas is a experimentally-measured channel matrix
when CCCs are connected to Tx and Rx sides and Schl, thr F
is the Frobenius norm of a transmission matrix measured
when Tx and Rx CCCs are directly connected.
Figure A· 2 shows the norm of the channel matrix, ortransmission power. In the figure, open and filled markers
represent without CCCs and with CCCs, respectively. Andstars represent characteristics of the compensated channel
matrix. From the figure, although the norm characteristic
is deteriorated when CCCs are connected, the transmission
power with CCCs is raised to the same level as that without
CCCs by compensating for the insertion loss. Figure A· 3shows channel capacity characteristics, and it is confirmedthat channel capacity is also improved by compensating forthe insertion loss. However, unlike the norm characteristics
shown in Fig. A· 2, even though the insertion loss is compensated, capacity characteristics with compensation does

not match those without CCCs and are still slightly lower.
A.2 Impurity of Channel Orthogonality
Next, capacity degradation caused by impurity of channel
orthogonality is considered. As mentioned in 2, if ideal
CCCs are connected to a perfectly plane-symmetrically configured MIMO system, interference channels from noncorresponding Tx ports to a certain Rx port theoretically
become zero. However, because of manufacturing error of
CCCs and MSA arrays and array displacement, it is practically diﬃcult to perfectly realize the regular symmetricalchannel matrix expressed as (2). Thus, these factors deteriorate purity of channel orthogonality resulting in an increaseof interference power. According to the Table 1, the prototype of CCCs were manufactured with high dimensional
accuracy, therefore, it is regarded that impurity of channel
orthogonality is mainly due to the influences of the Tx andMURATA et al.: FOUR-STREAM PARALLEL TRANSMISSION FOR SHORT-RANGE MIMO USING ONLY PASSIVE ANALOG COMPONENTS

79

A.3 Some Countermeasures and Future Work

Fig. A· 4Interference characteristics with ideal CCCs.

Fig. A· 5 Capacity characteristics with insertion loss compensation andideal interference cancellation.

Rx MSA arrays configuration such as fabrication and displacement errors.
First, interference power characteristics are evaluatedin case that ideal CCCs are connected to the SR-MIMO
system by post-processing. If the SR-MIMO system including Tx and Rx arrays is perfectly configured planesymmetrically, ideal CCCs enable complete interference
suppression. The analysis result is shown in Fig. A· 4, andstars represent characteristics when ideal CCCs applied toa measured channel matrix without CCCs. Also, interference characteristics calculated from the measured channel
matrix with actual CCCs are shown with filled circles forcomparison. From the result, it is confirmed, even though
ideal CCCs are used, interferences still remain at the samelevel as that with the actual CCCs. This indicates that channel orthogonality is spoiled by not so much manufacturing
error of CCCs but the asymmetry of SR-MIMO array configuration.
Then, it is assumed that it is possible to cancel theremaining interference completely which cannot be suppressed by manufactured CCCs. In analysis, the interference is canceled by applying DE-SDM by post-processing
to a measured channel matrix with CCCs. In Fig. A· 5, capacities with both loss compensation and interference cancellation are plotted with stars and almost agree with that ofideal DE-SDM plotted with open circles as can be seen fromthe figure.

In summary, if 1) the CCCs are fabricated with moreaccuracy and less losses, and 2) the arrays are planesymmetrically positioned more precisely, the channel capacity closer to that of ideal DE-SDM can be achieved by
AE-SDM. Largely, the asymmetry of the channel matrix due
to array displacement, inclination and the presence of environmental scatterers is critical for the proposed technique.
In particular, an SR-MIMO at millimeter wave frequency
is sensitive to such factors since, for example, severalcentimeter displacement could be several wavelengths [35].
To address such factors causing the asymmetrical channel, several approaches were suggested and their robustnesses against asymmetrical channel condition were evaluated. In the technique suggested in [19], power and phase
diﬀerences between channels are controlled by using subarrays with variable attenuators to regenerate a quasi-ideal
channel condition. Reference [21] proposed a channel orthogonalization technique by using multiple MSAs operating at diﬀerent higher-order modes and reported that it was
robust to a certain level of fading; this technique is similar
to our proposed technique in that the orthogonal directivities are employed for multiplexing [22]. In our future work,
we also need to evaluate the robustness of the proposed
technique and consider some countermeasures for non-ideal
cases.

Kentaro Murata
received the B.E. and M.E.
degrees in electrical and electronics engineeringfrom Iwate University, Morioka, Japan in 2011
and 2014, respectively. He is currently working
toward the Ph.D. degree with Graduate Schoolof Science and Engineering, National Defense
Academy of Japan, Yokosuka, Japan. His current research interests include feeding methods
for multiple-input-multiple-output antenna systems.

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, the Best
Paper Award of IEICE Communication Society
in 2006, and the APMC Best Paper Award in 2014, respectively. His current research interest is MIMO antennas for high-speed wireless communication systems.

IEICE TRANS. COMMUN., VOL.E99–B, NO.1 JANUARY 2016

80

Kentaro Nishimori
received the B.E., M.E.
and Ph.D. degrees in electrical and computer engineering form Nagoya Institute of Technology,
Nagoya, Japan in 1994, 1996 and 2003, respectively. In 1996, he joined the NTT Wireless Systems Laboratories, Nippon Telegraph and Telephone Corporation (NTT), in Japan. He was senior research engineer on NTT Network Innovation Laboratories. He is now associate professor in Niigata University. He was a visiting
researcher at the Center for Teleinfrastructure(CTIF), Aalborg University, Aalborg, Denmark from Feb. 2006 to Jan.
2007. He was an Associate Editor for the Transactions on Communications for the IEICE Communications Society from May 2007 to May 2010
and Assistant Secretary of Technical Committee on Antennas and Propagation of IEICE from June 2008 to May 2010. He received the Young
Engineers Award from the IEICE of Japan in 2001, Young Engineer Award
from IEEE AP-S Japan Chapter in 2001, Best Paper Award of SoftwareRadio Society in 2007 and Distinguished Service Award from the IEICE
Communications Society in 2005, 2008 and 2010. His main interests are
spatial signal processing including MIMO systems and interference management techniques in heterogeneous networks. He is a member of IEEEand IEICE. He received IEICE Best Paper Award in 2010.

David M. Klymyshyn
was born in Yorkton, Canada in 1968. He received his B.E.,
M.Sc., and Ph.D. degrees in Electrical Engineering from the University of Saskatchewan,
Canada in 1990, 1995, and 1998, respectively.
From 1990 to 1994, Dr. Klymyshyn was withSED Systems (Canada), and in 1995 was with
WaveCom Electronics (now Vecima NetworksCanada), where he was involved in the designof various commercial microwave satellite andcommunication systems. From 1998–2013 he
was a Research Scientist with Telecommunication Research Labs (Canada)
where he received 7 “Professor Performance Awards” for graduate supervision in microwave/wireless research. He also has ongoing research collaboration with the Institute of Microstructure Technology, Karlsruhe Instituteof Technology (KIT-Germany), where he was a Visiting Scientist in 2004
and 2008. Since 1998, he has been a Professor of Electrical and Computer
Engineering at the University of Saskatchewan (UofS), teaching undergraduate and graduate microwave courses. Dr. Klymyshyn has supervised morethan 50 students and researchers, and has received 11 “Merit Awards” forresearch and scholarly work at the UofS. He was selected as a “Rising Star”
by the VP Research at UofS, and was nominated for the “Ivany Internationalization Award”. In 2012, Dr. Klymyshyn was awarded a Discovery Accelerator Supplement grant from the Natural Sciences and Engineering Research Council of Canada (NSERC) to recognize “a superior research program”, one “highly rated for originality and innovation”. He has 4 patents
and 5 pending patents in the microwave/antenna area. Dr. Klymyshyn’s
current research interests focus on microwave/antenna devices and circuits
fabricated in thick materials. His group was first in Canada to demonstratefabrication of high-aspect-ratio RF MEMS reactive devices and circuits,polymer-based dielectric resonator antenna structures, and artificial dielectric structures and antennas fabricated using deep X-ray lithography. He is
co-Principal Investigator at Canada’s deep XRL facility, SyLMAND (Synchrotron Laboratory for Micro/Nano Devices). Dr. Klymyshyn has published over 110 papers, including a Journal of Micromechanics and Microengineering paper in the “Year’s Best Papers from 2010”, and an IEEE
Antennas and Propagation Magazine paper awarded the “2012 IEEE Edward E. Altshuler Year’s Best Paper Award”.

Hisashi Morishita
received the B.S. degree in Electrical Engineering from National
Defense Academy of Japan in 1980, the M.S.
and Ph.D. degrees from University of Tsukuba
in 1987 and 1990, respectively. From 1990 to
1992, he worked as a research and developmentoﬃcer at Air Research and Development Command of Japan Air Self-Defense Force (JASDF).
Since 1992, he has been with National Defense
Academy and is currently a Professor in the Department of Electrical and Electronic Engineering. From 1996 to 1997, he was a Visiting Researcher at the Communications Research Laboratory, McMaster University, Canada. His research isconcerned with mobile communication and small antennas. He is a fellowof IEICE and a senior member of IEEE.