Selected Papers

Experimental Evaluation of 8 × 4 Eigenmode SDM
Transmission in Broadband MIMO-OFDM Systems
Kentaro Nishimori†, Riichi Kudo, Yasushi Takatori,
and Koichi Tsunekawa
Abstract

We describe the features and basic characteristics of an 8 × 4 MIMO-OFDM (multiple-input multipleoutput orthogonal frequency division multiplexing) testbed that can evaluate eigenmode space divisionmultiplexing (E-SDM) in broadband MIMO-OFDM systems. The testbed achieved a maximum frequency utilization of 13.7 bits/s/Hz, the highest value for transmission reported in a formal publication.

1. Introduction
Due to the recent popularity of mobile phones andbroadband wireless local area networks (LANs),broadband wireless systems using orthogonal frequency division multiplexing (OFDM) were introduced to combat the effects of multi-path fading inindoor wireless LAN systems. Moreover, the multiple-input multiple-output (MIMO) technique isincorporated into these broadband wireless systems
using OFDM to achieve higher transmission speeds
without expanding the frequency band [1], [2].
MIMO technologies are categorized into 1) highquality transmission of a single data stream as spacetime codes using transmit and receive diversity or 2)
high-data-rate transmission of multiple data substreams [3], [4]. The latter, which is called space division multiplexing (SDM), is attractive because it
improves the transmission rate in a limited frequency
bandwidth. Moreover, various algorithms such as
Zero Forcing (ZF), Minimum Mean Square Error(MMSE), Ordered Successive Cancellation (OSUC),
and Maximum Likelihood Detection (MLD) havebeen proposed to discriminate the inter-substream
interference if the transmitters cannot know the channel state information (CSI) [3].
On the other hand, if the transmitter can know the
CSI, then Eigenmode-SDM (E-SDM) [5]-[7] is very
effective because optimal MIMO transmission can be† NTT Network Innovation Laboratories
Yokosuka-shi, 239-0847 Japan
E-mail: nishimori.kentaro@lab.ntt.co.jp

50

achieved with simple spatial filtering using the ZF
algorithm at the receiver, for example [7]. The channel capacity in MIMO channels can be improved
without increasing the number of receive antennas if
the number of transmit antennas is increased by using
E-SDM. Thus, E-SDM is suitable for downlink systems, which need to provide high-data-rate transmission because the number of antennas is generally
greater at the access point than at the mobile terminal.
To incorporate MIMO technologies into commercial wireless systems, several chip vendors, manufacturers, and research institutes around the world havedeveloped prototypes with MIMO transmission ranging from 2 × 2 to 4 × 4 [8]-[11]. However, only a few
studies have evaluated the frequency utilization for
MIMO transmission in an actual environment. For
example, a maximum frequency utilization of 2.7
bits/s/Hz can be obtained in commercial wireless
LAN systems based on the IEEE.802.11a standard[12]. In the case of MIMO systems, it was reported
that maximum frequency utilization of 10 bits/s/Hz
was obtained with 4 × 4 MIMO transmission using
simple MLD without transmit beamforming [10].
To further improve the frequency utilization, it iseffective to increase the number of antennas. However, it is very difficult to use more than four antennas
at the mobile terminal because many terminal stations
are small, such as PCMCIA (Personal Computer
Memory Card International Association) cards or
personal digital assistants (PDAs). Since E-SDM canachieve a high transmission rate without increasing
the number of antennas at the mobile terminal, it isvery effective to use E-SDM when the number of
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Transmitter

4.85 GHz
ReceiverUp conv. #1
D/A converter
for IQ signal
TCP-IP

Up conv. #2
Up conv. #3

S1

Down conv. #1

LNA

Down conv. #2

LNA

Down conv. #3

LNA

Down conv. #4

A/D converter
for IQ signal
TCP-IP

S2
S3

GP-IB

LNA

S4
Up conv. #8
LO1 (3.15 GHz)

LO2 (8 GHz)
Feedback of CSI (by using TCP-IP)

IQ: in-phase and quadrature-phase
LO: local oscillator
LNA: low-noise amplifier
GP-IB: general purpose interface bus
TCP-IP: transmission control protocol Internet protocol

Fig. 1. Configuration of MIMO-OFDM transceiver.

Tx1
Tx2

Tx5

LO1

Tx6
Tx7

Rx4

LNA

Rx3

Rx2

Rx1

Tx3
Tx8
Tx4
LO2
(b) Receiver(a) Transmitter

Fig. 2. Photograph MIMO-OFDM transceiver.

antennas at the access point is greater than four andthe number of mobile terminals is less than four,
especially from the viewpoint of the hardware implementation in near-future commercial systems.
In this paper, we describe the features and basic
characteristics of a broadband MIMO-OFDM testbed
that can evaluate transmit beamforming such as ESDM. We set the numbers of transmit and receive
antennas to eight and four, respectively, to clarify theeffectiveness of our testbed using E-SDM for the proVol. 3 No. 9 Sep. 2005

totypes developed by outside research institutes. This
testbed can also handle 100-MHz bandwidth signals.
It can obtain not only spatial/frequency correlationand eigenvalue distributions, which are key parameters in MIMO channels, but also evaluate the transmission quality including error correction for MIMOOFDM transmission. Finally, we report that a maximum frequency utilization of 13.7 bits/s/Hz, thehighest value for a transmission yet reported in a formal publication related to MIMO technology, was51

Selected Papers

achieved with 8 × 4 E-SDM transmission on the
MIMO-OFDM testbed. Section 2 outlines the 8 × 4
MIMO-OFDM testbed and communication flow.
Section 3 presents experimental results for the bit
error rate (BER) and frequency utilization when
SDM and E-SDM with ZF were used for MIMO
transmission.

conversion is applied and the RF (radio frequency)
signals at 4.85 GHz are transmitted. In the receivers,
these signals are down-converted, and A/D conversion is applied. These signals are finally transferred toa PC. All the signal processing is performed off-line
to evaluate the various SDM algorithms in our testbed. Moreover, as shown in Fig. 1, the CSI is transferred over a wired connection to determine the transmit weight in our MIMO-OFDM testbed.
As shown in Fig. 1, signal generators (LO1 andLO2) are used for the local oscillators to enhance thestability of the frequency converter among the transmitters or receivers. Each D/A converter has 128
Mbytes of memory, and signals with various formats
can be evaluated. Each A/D converter has 128 Mbytes
of memory, and we can handle data acquisition for six
seconds at a maximum of 20 MHz, for example.

2. Configuration of 8 × 4 MIMO-OFDM testbed
2.1 Hardware configuration
The configuration of the experimental testbed forbroadband MIMO-OFDM transmission is shown in
Fig. 1 and a photograph of it is shown in Fig. 2. Its main
parameters are given in Table 1. The center frequency of this testbed is 4.85 GHz. To maximize the effectiveness of E-SDM transmission, we set the numberof transmitters and receivers to eight and four, respectively. The maximum 8 × 4 MIMO-OFDM transmission can be evaluated using a bandwidth of 100 MHz.
In the transmitters, the transmit signals are generated in a personal computer (PC), and uploaded to adigital/analog (D/A) converter as shown in Fig. 1.
After D/A conversion of these signals, frequency

2.2 Communication flow of MIMO-OFDM
testbedIn this sub-section, we describe the frame format, thescheme for estimating the channel matrix, and the communication flow used in our MIMO-OFDM testbed.
The frame format used to achieve 8 × 4 transmit
beamforming such as E-SDM in the MIMO-OFDM
testbed is shown in Fig. 3. Its signal parameters are
based on the IEEE802.11a standard, which is used forcommercial wireless LANs. This frame format is
extended to estimate the channel matrix for MIMOOFDM transmission. When we use the SDM schemewithout beamforming, the maximum number oftransmit antennas is four because the number ofreceivers is four. Details of the frame format for 4 × 4

Table 1. Parameters for MIMO-OFDM transceiver.
Number of antennas

8 (Tx), 4 (Rx)

Frequency

4.85 GHz

Bandwidth

100 MHz

Range of AD/DA

14 bits

Transmission power

0 dBm (without HPA)

Sensitivity–20 to –70 dBm

Sequence of estimation of H
4.0 × 4 = 16.0 µs

Sequence of initial sync.
0.8 × 10 = 8.0 µs

Data sequence
4.0 × P µs

Tx1 S S S S S S S S S S GI

Lw11

GI

Lw12

GI

Lw13

GI

Lw14

GI

Dw11

GI

Dw12

GI

Dw1p

Tx2 S S S S S S S S S S GI

Lw21

GI

Lw22

GI

Lw23

GI

Lw24

GI

Dw21

GI

Dw22

GI

Dw2p

Tx3 S S S S S S S S S S GI

Lw31

GI

Lw32

GI

Lw33

GI

Lw34

GI

Dw31

GI

Dw32

GI

Dw3p

Tx8 S S S S S S S S S S GI

Lw81

GI

Lw82

GI

Lw83

GI

Lw84

GI

Dw81

GI

Dw82

GI

Dw8p

Short preamble

Long preamble ×1/2

S (short preamble): 16 samples, L (long preamble): 64 samples, GI (guard interval): 16 samples
D (data sequence): 64 samples, P: frame length

Fig. 3. Frame format for 8 × 4 transmit beamforming.

52

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MIMO-OFDM transmission are given in Refs. [13]and [14].
In Fig. 3, a short preamble is used for timing detection of the fast Fourier transform (FFT) window of
the OFDM signals. Timing detection uses sliding correlation methods. Next, the channel matrix for the
MIMO channels is estimated using a long preamble
as shown in Fig. 3. Term Lwmk represents the OFDM
signals, which are weighted with the m-th (m = 1 – 8)transmit antenna obtained by multiplying the k-th (k= 1 – 4) eigenvector and the long preamble.
In the data sequence, P OFDM symbols are transmitted per stream. The four pilot subcarriers areinserted in all OFDM symbols to compensate for thephase rotation, and the number of these pilot subcarTable 2. Parameters of MIMO-OFDM transmission.
Bandwidth

20 MHzSampling rate (A/D)

40 MHzSampling rate (D/A)

80 MHzNumber of FFT points

64

Number of subcarriers

48

Number of pilot subcarriers

4

Guard interval length

0.8 µs

Effective signal length

3.2 µsLength of short preamble

2 OFDM symbols

Length of preamble

4 OFDM symbols

Modulation scheme

QPSK, 16QAM,
64QAM, 256QAM

Coding rate

1/2, 2/3, 3/4, 5/6, 7/8

Modulation control

riers is given in Table 2. Term Dwml denotes the
OFDM signals at the l-th (l = 1 – P) timing, which isweighted by the m-th (m = 1 – 8) transmit antenna
obtained by multiplying the first and fourth eigenvectors and the first and fourth streams, respectively. We
used the modulation schemes and coding rates given
in Table 2.
The signal processing in our MIMO-OFDM testbed
before D/A conversion and after A/D conversion isshown in Figs. 4 and 5, respectively. At the transmitter site in Fig. 4, the transmit bits are first divided into
four streams, and convolutional coding with a constraint length of seven is used. Next, these bits areinterleaved and modulated, and the signals are multiplied by the weights for transmit beamforming. In
this paper, E-SDM is used for the transmit beamforming. The eigenvectors are obtained by singulardecomposition of the channel matrix in E-SDM. The
channel matrix H k for subcarrier f k is obtained
through feedback from the receiver to the transmitter
via the cable in the MIMO-OFDM testbed. The singular value decomposition is shown in the following
equations.
Hk = Uk ∑ k VkH(1)

Uk = [uk ,1uk ,2 ,···, uk , L ](2)

Vk = [vk ,1vk ,2 ,···, vk , L ](3)∑k = diag[ λk ,1 , λk ,2 ,···, λk , L ],(4)

Add preamble
D/A

Convolutional
encoder

IFFT

Interleaving
Mapper

D/AInterleaving
MapperConvolutional
encoderInterleaving

Convolutional
encoderInterleaving

MapperMapperTransmit weight control

S/P for SDM

Convolutional
encoder

#1
D/A

IFFT

Tx
data
1, 0, 1,…

Add GI

Add GI

#2
D/A
D/A

IFFT

Add GI

#3
D/A

D/A
IFFT

Add GI#8
D/A

Fig. 4. Signal processing part before D/A converter.

Vol. 3 No. 9 Sep. 2005

53

Selected Papers

Viterbi
decoder

Deinterleaver

DemapperDeinterleaver

DemapperDeinterleaver

FFT

FFT

DemapperFFT
Deinterleaver

A/D

RemoveGI

RemoveGI

RemoveGI

RemoveGI#1
A/D
Symbol timing detection

Viterbi
decoder

FFT
Estimation of channel matrix

Viterbi
decoder

DemapperSDM detector

1, 0, 1,…

BER calculation

Viterbi
decoder

A/D
#2
A/D

A/D
#3
A/D

A/D
#4
A/D

Fig. 5. Signal processing part after A/D converter.

where Uk and Vk denote the eigenvectors of the transmitter and receiver for subcarrier fk, respectively.
Eigenvector Vk is used as the transmit weight for subcarrier fk. In addition, ∑k represents the matrix whose
diagonal terms consist of eigenvalues for subcarrierfk, and the numbers of eigenvector beams, modulation
schemes, and coding rates are generally determinedaccording to the values of these eigenvalues for eachsubcarrier. In this paper, for simplicity, the number of
eigenvector beams is fixed to four and three for 8 × 4
and 4 × 4 E-SDM, respectively. The modulation
scheme and coding rate for each stream are also fixedamong the subcarriers. Finally, the inverse fast Fourier transform (IFFT) process is applied to the signals
after beamforming, and D/A conversion is performed.
At the receiver site in Fig. 5, the baseband signals
are first converted to digital signals by the A/D converter after frequency conversion. Next, timing detection using the short preamble in Fig. 3 and FFT are
applied to these signals after the guard interval has
been removed. After FFT processing, the channel
matrix is estimated by utilizing the sequence of thelong preamble in Fig. 3, and the SDM decoding algorithm is applied using channel matrix Hk for subcarrier fk. In this paper, the ZF algorithm is used as theSDM decoding algorithm. The decoding signals are
given by the following equations:
Yk = ( HkH Hk ) −1 HkH Xk(5)

Xk = [ x k ,1 ,··· x k ,4 ]T(6)

Yk = [ yk ,1 ,··· yk ,4 ]T ,(7)

where Yk and Xk represent the decoded and received
54

signal vectors for subcarrier fk, respectively. Finally,
the de-interleaver and Viterbi decoder are used forthese decoded signals, and the BER is calculated.
3. Experiment using MIMO-OFDM testbed
3.1 Measurement environment
To clarify the basic characteristics of our MIMOOFDM testbed, we conducted measurements in anindoor environment (Fig. 6). Sleeve antennas* wereused for the transmit and receive antennas. Rectangular and linear arrays were used for the transmit andreceive arrays, respectively, which both had an element spacing of 1.0 wavelength. The heights of thetransmit and receive antennas were 2.0 and 1.2 m,
respectively. The total transmission power was 6
dBm, and the transmission power per antennachanged according to the number of antennas used.
For example, when we used four transmit antennas,
Antennas #1 to #4 in Fig. 6 were used. The transmit
antennas were located at Point T and the receive
antennas were located at the four points A to D. To
clarify how the transmission quality depended on the
direction of the receive array antenna, we evaluatedfour rotation angles (–45°, 0°, 45°, 90°) at each
receiving point.
Table 3 gives the combinations of the transmit andreceive antennas and the SDM scheme at the transmitter and receiver. The BER and frequency utiliza* Sleeve antennas: Sleeve antenna is generally used for the measurement antenna because this antenna has omni-directional pattern in horizontal plane and can be relatively easily manufactured.
The characteristics of radiation pattern and gain of the sleeveantenna are the same with those of the dipole antenna.

NTT Technical Review

Selected Papers

12.10 mTransmit antenna#5 #6 #7 #8
Transmitter(x,y)=(0,0)
T

8m

3m

(5,3) B#1 #2 #3 #4

1m
Receive antenna
13.45 m(1,3) A

–45°

Receiver(1,8) C
Window#4 #3 #2 #1

0°

#4
#3
#2
#1

5m
(5,8) D

#1
#2
#3
#4

Height = 3 m

45°

#1
#2
#3
#4
90°

Fig. 6. Measurement environment.
Table 3. Number of antennas and SDM scheme.
Number ofTx and Rx

Transmit
beamforming

Decoding
algorithm

1, 1

None

None

1, 4

None

MRC

None

ZF

E-SDM

ZF

2, 2
2, 4
3, 3
3, 4
4, 4
4, 4
8, 4

tion for one to four antennas are given when we evaluated the SDM scheme without transmit beamforming. We used the ZF algorithm, which is basicallyused as the decoding algorithm for the SDM scheme.
When using the ZF algorithm, the number of streams
equaled the number of receive antennas. We also
evaluated 4 × 4 and 8 × 4 E-SDM, where the decoding algorithm was ZF with E-SDM.
In this measurement, we used the modulation signals given in Table 1 and the frame format in Fig. 3
with P = 50. The total number of bits was almost 107,
so the frequency utilization was obtained from the
BER for almost 107 bits. The frequency utilization(2.7 bits/s/Hz, or 54 Mbit/s per 20 MHz) based on the
64QAM modulation scheme with coding rate R = 3/4
in wireless LAN systems based on the IEEE802.11astandard was used as the standard. In this case, 4.5
Vol. 3 No. 9 Sep. 2005

bits per subcarrier per OFDM symbol could be transmitted. In this study, we regarded a signal with a BER
of less than 10–5 as being error-free, and we defined
the point at which BER = 10–5 intersects the function
fitting curve, which was obtained from the BER characteristics versus the transmission rate, as the frequency utilization.
3.2 Frequency utilization when applying ZF
algorithm
In this sub-section, the performance of the ZFSDM decoding scheme without transmit beamforming is evaluated. The BER characteristics versus frequency utilization for one to four transmit and receive
antennas are shown in Fig. 7, which shows the results
for receiving point A and a rotation angle of 0°. For 2
× 2 MIMO transmission using the ZF algorithm, thefrequency utilization was 1.8 times that for 1 × 1
transmission. However, when the numbers of transmit and receive antennas were increased to greaterthan two, the frequency utilization did not exhibit asignificant increase. This is because noise enhancement caused by the ZF algorithm completely suppressed the inter-stream interference when the number of streams was increased [3].
To resolve the above problems, researchers areinvestigating methods in which a larger number ofreceive antennas or other SDM decoding schemes areused [3], [13]. In this paper, we clarify the diversity
effect at the receivers achieved by increasing thenumber of receive antennas to greater than the num55

Selected Papers

8

10–1

BER

10–3
1×1

10–4

2×2

3×3

4×4

10–5
With ZF
10–6

3×4

7
Frequency utilization (bit/s/Hz)

10

Rx-A
0°

–2

2

3

4

5

6

7

8

2×4
4×4

6
3×3
2×2
5
1×4

4

3

1×1

Rx-A
0°

Frequency utilization (bits/s/Hz)
2

Fig. 7. BER versus frequency utilization(with ZF algorithm).

3.3 Effectiveness of E-SDM transmission
The BER characteristics versus frequency utilization when applying the E-SDM scheme are shown in
Fig. 9. Frequency utilization of 9.8 and 13.7 bit/s/Hz
could be obtained using the 4 × 4 and 8 × 4 E-SDM
schemes, respectively. These values correspond to
improvements of 3.6 and 5.1 times the frequency utilization values for commercial wireless LAN systems
based on IEEE802.11a. Moreover, the frequency utilization for the 8 × 4 E-SDM (13.7 bits/s/Hz) is thehighest transmission rate reported to date in any official publication related to MIMO technology. These
results were for a bandwidth of 20 MHz. When we set
a 100-MHz bandwidth, which is the maximum that our
testbed can handle, we obtained frequency utilizationsof 11.2 and 15.2 bit/s/Hz using 4 × 4 and 8 × 4 E-SDM
schemes, respectively, with a guard band of 4 MHz.
To clarify why 8 × 4 E-SDM could obtain such a
56

2

3

4

Number of transmit antennas

Fig. 8. Frequency utilization versus number of transmit
antennas (Decoding algorithm is ZF).
10–1
1×1
10–2

4×4
ZF

3×4
ZF

8×4
E-SDM

10–3
BER

ber of streams. The frequency utilization versus thenumber of transmit and receive antennas is shown in
Fig. 8. The frequency utilization could be improvedby setting the number of receive antennas, but not the
number of streams, to four. For example, 2 × 4 and 3
× 4 MIMO transmission with the ZF algorithm exhibited frequency utilization that was 2.3 and 2.5 times
that for 1 × 1 transmission, respectively. Moreover,
we could confirm that the frequency utilization of 3 ×
4 SDM with the ZF algorithm was higher than that of
4 × 4 SDM with the ZF algorithm. Therefore, when
the ZF algorithm without transmit beamforming isused for MIMO transmission, receive diversity isvery effective in improving the frequency utilization.

1

4×4
E-SDM

10–4

10–5
Rx-A
0°
10–6

2

4

6
8
10
12
Frequency utilization (bits/s/Hz)

14

16

Fig. 9. BER versus frequency utilization with E-SDM.

high frequency utilization, we considered the eigenvalue distribution obtained by channel matrix H. The
1st to 4th eigenvalues versus the number of subcarriers in 4 × 4 and 8 × 4 MIMO channels, respectively,
are shown in Fig. 10. The 4th eigenvalues changed
greatly versus the number of subcarriers in 4 × 4
MIMO channels, and these values were about 1/1000of the 1st eigenvalue. Thus, in this study, it was difficult to allocate the modulation schemes to the fourth
stream in 4 × 4 E-SDM. On the other hand, the valuesof the 4th eigenvalue did not change much versus thenumber of subcarriers in 8 × 4 MIMO channels, andwe could allocate 64QAM schemes to the fourth
NTT Technical Review

Selected Papers

101

101
#1

#1
#2

#3
10

#2

100
Eigenvalue

Eigenvalue

100

–1

#4
10–2

#3
10–1

10–2

10–3

#4

10–3
0

10

20

30

40

0

50

10

20

30

Subcarrier number

Subcarrier number(a) 8 × 4 MIMO(b) 4 × 4 MIMO

40

50

Fig. 10. Eigenvalue versus number of subcarriers.
Table 4. Frequency utilization comparison between
E-SDM and SDM with ZF.

1.4

Capacity improvement

1.3
Measured
point

1.2

Rotation
angle
(°)

8×4
E-SDM

4×4
E-SDM

3×4
ZF

–45

13.57

9.97

8.18

0

13.74

9.86

7.13

45

13.76

9.85

8.45

90

13.88

9.66

7.74

–45

11.78

9.25

5.09

0

12.66

9.44

5.05

45

12.53

8.81

6.66

1.1
A

1
0.9
0.8

B
MLD

E-SDM

4 × 4 MIMO

MLD

E-SDM

8 × 4 MIMO

Fig. 11. Improvement in channel capacity using the
eigenvalues obtained by the channel matrix.

stream in 8 × 4 E-SDM transmission. Therefore, 8 ×
4 E-SDM could obtain the very high frequency utilization of 13.7 bits/s/Hz because we could utilize all
four streams in 8 × 4 MIMO channels.
The ideal channel capacity [5], which is obtainedusing all eigenvalues in 8 × 4 and 4 × 4 MIMO channels, respectively, is shown in Fig. 11. This result isbased on the ideal reception decoding, and this channel capacity theoretically corresponds to that of MLD[3]. Furthermore, the channel capacity with 4 × 4 ESDM was normalized to one. As can be seen in Fig.
11, the channel capacity of E-SDM was almost thesame as that of MLD in 4 × 4 MIMO channels. On theother hand, E-SDM could improve the channel
capacity by 1.3 times that for MLD in 8 × 4 MIMO
Vol. 3 No. 9 Sep. 2005

C

D

AverageFrequency utilization (bits/s/Hz)

90

12.31

8.87

5.71

–45

10.52

8.72

7.71

0

12.14

8.76

7.28

45

11.35

8.94

7.00

90

10.94

8.71

6.28

–45

12.37

9.23

6.78

0

12.14

8.62

6.96

45

12.43

9.47

6.88

90

12.21

9.72

7.24

12.40

9.24

6.88

channels. Therefore, using E-SDM is very effective if
the number of antennas at the access point is greaterthan the number of mobile terminals. Moreover, we
could confirm that this improvement with 8 × 4 ESDM almost coincided with the result in Fig. 9.
The frequency utilizations at all receiving points
and rotating angles when the 8 × 4 E-SDM, 4 × 4 ESDM, and 3 × 4 ZF schemes were used are shown in
Table 4. The changes in frequency utilization were57

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mainly due to the differences at the receiving points
or in the directions of the receive array antenna. Thisis because the spatial correlation characteristics
between transmit and receive antennas changed when
the directions or locations were changed, and the ZF
algorithm had a significant effect on the spatial correlation characteristics. On the other hand, the deterioration due to the differences in directions and locations of the receive array antenna was relatively small
compared with the ZF-SDM when E-SDM was used.
From the average frequency utilization of all measured points, we could confirm that 8 × 4 and 4 × 4 ESDM could obtain frequency utilization 1.8 and 1.35
times better than 3 × 4 ZF.
Transmit beamforming such as E-SDM should not
only improve the frequency utilization, but also
expand the service area through its radiation patterncontrol. To confirm the improvement in the service
area achieved by E-SDM, we evaluated the frequency utilization when the transmit power was changed.
The frequency utilization versus transmit power for 8
× 4 E-SDM and 3 × 4 ZF is shown in Fig. 12. Transmit power of 0 dBm was necessary to obtain frequency utilization of 7.7 bits/s/Hz when 3 × 4 ZF wasused, but transmit power of –15 dBm could achieve
the same frequency utilization when 8 × 4 E-SDM
was used. This large reduction in transmit power (15dB) shows that 8 × 4 E-SDM will be very effective for
expanding the service area. Moreover, since the peakto-average-power ratio (PAPR) should be reduced in
MIMO-OFDM systems, E-SDM should also be
effective from this viewpoint.

14
Frequency utilization (bit/s/Hz)

Rx-A
0°
12

8×4
E-SDM

10
8
6
3×4
ZF

4
2
–16

–14

–12

–10

–8

–6

–4

–2

0

Transmission power per antenna (dBm)

Fig. 12. Frequency utilization versus transmission power.

58

4. Conclusion
This paper described the features and basic characteristics of a broadband MIMO-OFDM testbed thatcan evaluate 8 × 4 E-SDM transmission. This testbed
can not only obtain the correlation and eigenvalue
distribution, which are key parameters in MIMO
channels, but also evaluate the transmission quality
including the error correction used in MIMO-OFDM
transmission. We evaluated the frequency utilization
when using this MIMO-OFDM testbed in an actualindoor environment. Using 8 × 4 E-SDM transmission, we obtained maximum frequency utilization of
13.7 bits/s/Hz, which is the highest value reported todate for MIMO-OFDM.
References[1]

G. L. Stuber, J. R. Barry, S. W. McLaughlin, Y. Li, M. A. Ingram, andT. G. Pratt, “Broadband MIMO-OFDM wireless communications,”
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[2] S. Korosaki, Y. Asai, T. Sugiyama, and M. Umehira, “A SDMCOFDM scheme employing a simple feed-forward inter-channelinterference canceller for MIMO based broadband wireless LANs,”
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NTT Technical Review

Selected Papers

Kentaro Nishimori

Yasushi Takatori

Research Engineer, Wireless Systems Innovation Laboratory, NTT Network Innovation Laboratories.
He received the B.E., M.E., and Dr.Eng.
degrees in electrical and computer engineeringfrom Nagoya Institute of Technology, Nagoya,
Aichi in 1994, 1996, and 2002, respectively. He
joined NTT Wireless Systems Laboratories in
1996. He received the Young Engineers Award
from the Institute of Electronics, Information andCommunication Engineers (IEICE) of Japan in2001 and Young Engineer Award from IEEE
AP-S Japan Chapter in 2001. His current
research interest is smart antennas for mobile
communications and MIMO systems. He is amember of IEEE and IEICE.

Research Engineer, Wireless Systems Innovation Laboratory, NTT Network Innovation Laboratories.
He received the B.E. degree in electrical andcommunication engineering and the M.E. degree
in system information engineering from Tohoku
University, Sendai, Miyagi in 1993 and 1995,
respectively. He joined NTT Wireless Systems
Laboratories in 1995. He was a visiting
researcher at the Center for TeleInFrastruktur(CTIF), Aalborg University, Aalborg, Denmark
from 2004 to 2005. He received the Young Engineers Award from IEICE in 2000, the Excellent
Paper Award of WPMC (International Symposium on Wireless Personal Multimedia Communications) in 2004, and the YRP (Yokosuka
Research Park) Award in 2005. His current
research interests are smart antennas, MIMO systems, and spatial signal processing techniques.
He is an associate editor of the Springer Journalof Wireless Personal Communications. He is amember of IEEE and IEICE.

Riichi Kudo
Engineer, Wireless Systems Innovation Laboratory, NTT Network Innovation Laboratories.
He received the B.E. and M.E. degrees in geophysics from Tohoku University, Sendai, Miyagi
in 2001 and 2003, respectively. He joined NTT
Network Innovation Laboratories in 2003. His
current research interest is MIMO communication systems. He is a member of IEICE.

Vol. 3 No. 9 Sep. 2005

Koichi Tsunekawa
Senior Manager, Wireless Systems Innovation
Laboratory, NTT Network Innovation Laboratories.
He received the B.S., M.S., and Ph.D. degrees
in engineering science from the University ofTsukuba, Tsukuba, Ibaraki in 1981, 1983, and1992, respectively. He joined the ElectricalCommunications Laboratories of Nippon Telegraph and Telephone Public Corporation (nowNTT), Tokyo in 1983. Since 1984, he has been
engaged in R&D of portable telephone antennas
in land mobile communication systems. From1993 to 2003, he was with NTT DoCoMo, Inc.
where he worked on radio propagation research,
intelligent antenna systems for wireless communications, and the developing IMT-2000 antenna
systems. His research interests are antenna systems for MIMO transmission, millimeter-wave
broadband access, and ubiquitous wireless systems. He is a member of IEICE and IEEE.

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