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244 MIMO System Technology for Wireless Communications

the simultaneously scheduled users given the CSI feedback, whereas for

PARC there is no protection between the streams. Third, due to the reduced

variance of received SINR, gains from max SINR scheduling are smaller in

Vehicular A than in Pedestrian A channel. The smaller variance in SINR can

also be seen from the CDF curves of average user bit rates, the slopes being

steeper in Vehicular A channel.

8.6 Conclusions and Discussion

We studied different options for introducing multiple-input multiple-output

(MIMO) transceivers to 3G WCDMA uplink and downlink. Basic universal

terrestrial radio access (UTRA) frequency-division duplex (FDD) parameters

were discussed in order to illustrate the boundary conditions in UTRA FDD

that need to be taken into account when designing MIMO transceivers. We

also presented the various MISO techniques supported by the present UTRA

FDD speciﬁcation, Release 6.

It was shown that the uplink coverage and capacity of UTRA FDD mode

can be greatly improved by SIMO and MIMO. While the gain from transmit

diversity is noticeable only in the presence of heavy intercell interference,

the gain from additional receive antennas is remarkable also in isolated cells.

Information MIMO introducing additional scrambling codes should be used

with high data rates instead of diversity MIMO. This is mostly due to the fact

that heavy code puncturing can be avoided by using the information MIMO.

UTRA FDD uplink is not code limited and therefore diversity and information

FIGURE 8.13

User throughput CDFs, ITU Vehicular A channel with 30 km/h mobile speed.

100 200 300 400 500 600

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

roughput(kbps)

Cumu

ative pro

ity

CDF



roug

put in ITU Ve

A at 30

CL Mode 1

MUB, RR

MUB, max SINR

2 × 2 PARC

4190_book.fm Page 244 Tuesday, February 21, 2006 9:14 AM

Multiuser MIMO for UTRA FDD 245

MIMO can be implemented by allocating additional channelization or scram-

bling codes to different transmit antennas. Thus, the receiver in the base

station can separate the signals from different antennas in code domain, and

it is not necessary to rely on spatial signatures and space–time code design.

This makes the system more robust and receivers can utilize well-known

multiuser and interference cancellation receivers developed for CDMA sys-

tems. Furthermore, these MIMO schemes can be implemented with only

minor changes to the present speciﬁcation.

In contrast to uplink, UTRA FDD downlink is code limited and it is

necessary to search for spectrally efﬁcient MIMO techniques that are able to

reuse channelization codes. Therefore, similar MIMO techniques as in UTRA

FDD uplink cannot be employed. The work item on MIMO transceivers in

downlink has been active for several years within the third generation part-

nership project (3GPP), and the current target is set to Release 7. Several

concept proposals have been presented in standardization meetings and

added into the technical report [10]. At the time of writing, the gains of

different MIMO proposals are being evaluated against two-antenna receive

diversity. Based on the performance evaluation, Work Group 1 will select a

single MIMO scheme (two transmit antennas) in meeting No. 44 in February

2006 for further analysis. The decision whether to include the MIMO feature

in Release 7 speciﬁcations will be made in June 2006, being based on system

performance and overall complexity evaluation of the selected scheme.

Introduction of MIMO techniques to UTRA FDD downlink has not pro-

ceeded smoothly. First, adding multiple antennas and radio transceiver

chains to user equipments is not straightforward due to cost and complexity

of implementation. Second, new MIMO techniques need to be backward

compatible with earlier releases. In particular, the performance of legacy user

equipment, which is able to receive signals from two transmit antennas,

should not suffer when new base stations use, say, four antennas for trans-

mission. In addition, 3GPP has outlined several other requirements for

MIMO performance. Increasing peak data rates is not considered as the

primary target, which does not favor information MIMO (spatial multiplexing)

techniques. Instead, the goal is to increase the number of users and coverage

of the services. To this end, we introduced a multiuser beamforming tech-

nique that improves system throughput without any modiﬁcations to user

equipments and feedback channels in the current UTRA FDD speciﬁcation.

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249

Multifunctional Reconﬁgurable Microelectro-

mechanical Systems Integrated Antennas for

Multiple Input Multiple Output Systems

Bedri Artug Cetiner

CONTENTS

9.1 Introduction................................................................................................249

9.2 MRA Concept and Its Links with MIMO Systems..............................252

9.2.1 Multifunctional Reconﬁgurable Antenna..................................252

9.2.2 Links among Transmission Algorithms, Antenna

Properties, and Propagation Environment ...............................254

9.3 RF MEMS Technology Compatible with Microwave Laminates for

Fabricating MRAs......................................................................................257

9.4 RF MEMS Integrated Antennas ..............................................................258

9.4.1 Three-Element Selection Diversity Antenna.............................258

9.4.2 Multifunctional Reconﬁgurable Spiral Antenna......................263

9.4.2.1 Antenna Structure and Operational Mechanism ......263

9.4.2.2 Microfabrication and Results........................................266

9.5 Concluding Remarks.................................................................................268

References.............................................................................................................270

9.1 Introduction

A wireless communications system that is capable of performing multiple

functions utilizing a single architecture is deﬁned as a multifunctional sys-

tem. A system consisting of multiple subsystems, each of which performs a

separate function, does not fall within this deﬁnition. In this context, a true

multifunctional system must also be reconﬁgurable so that a single architecture

4190_book.fm Page 249 Tuesday, February 7, 2006 12:44 PM

250 MIMO System Technology for Wireless Communications

can reconﬁgure itself for performing each function. A good example of a

multifunctional wireless communications system is a software deﬁned radio

that enables a single device to operate over different communications and

networking standards. A number of articles on multifunctional radio fre-

quency (RF) systems can be found in the recent special issue in IEEE Trans-

action on Microwave Theory and Techniques [1].

This chapter focuses on a new class of antenna, henceforth referred to as

microelectromechanical systems (MEMS) integrated multifunctional recon-

ﬁgurable antenna (MRA), which can be employed in many wireless systems

applications. In accordance with the deﬁnition of a multifunction system

given above, an MRA is a single antenna that is capable of performing

multiple functions by dynamically reconﬁguring its architecture. Dynamic

reconﬁguration in the antenna architecture is accomplished by MEMS.

Progress continues on many existing applications of MEMS technology, such

as RF/wireless, biomedical, optical, and microﬂuidics, while new application

areas such as fuel cells and power generators are also opening up. Estab-

lishment of MRAs requires a new RF MEMS technology, which has recently

been developed by the author and others [2,3]. This technology will be

introduced in the next sections. The implementation of MRAs in MIMO

systems promises to further improve the system performance and is the topic

of this chapter.

The research efforts on MIMO systems with associated transmission algo-

rithms such as space–time codes (STCs) and spatial multiplexing (SM) aim

at making the best use of limited and costly wireless bandwidth by exploiting

the high spectral efﬁciencies offered by multiple antennas. The signal pro-

cessing and space–time coding aspects of MIMO systems are discussed in

Chapters 4 and 5.

The motivation behind the topic of this chapter is the fact

that there is additional room for further exploitation of the theoretical gains

of MIMO systems when the antenna/electromagnetic aspects and the asso-

ciated signal processing and coding aspects are integrated together in a

multidisciplinary approach [4]. The performance of MIMO systems depends

on several parameters such as the following:

• The physical structure of the channel: scattering density and dispo-

sition of the scatterers

• The space–time processing algorithms for MIMO channels: spatial

multiplexing (SM), space–time coding (STC), and beamforming

• The antenna array conﬁguration and element properties: radiation

pattern, polarization, operation frequency, and input impedance

Due to the time varying nature of the wireless channel, the true beneﬁts

of MIMO can be exploited only through a smart design that is able to respond

to the channel dynamics. The ability of the network to respond to the channel

may be expressed in the following terms.

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Multifunctional Reconﬁgurable Microelectromechanical Systems

251

• Shaping the Channel Statistics:

The ability to shape the channel

statistics in a way that the spatial dimensions can be resolved. This

allows multiple data pipes to simultaneously carry information across

spatial dimensions and between various users while facing the min-

imum interference. Key to resolvability is the ability to reconﬁgure

the antenna radiation pattern, polarization, operation frequency.

• Adaptability:

The ability to adapt to the channel in an opportunistic

way where the spatial dimensions associated with good channel

conditions are utilized more than the spatial dimensions affected by

poor fading conditions. Key to adaptability is the scheduling algo-

rithm as well as the adaptive algorithm that chooses beamforming,

or the best space–time coding strategy for the channel condition [5].

While adaptability is important to MIMO systems in general, resolvability

is especially important for multiuser MIMO systems where the interference

presented by simultaneous communications is the primary bottleneck. It is

therefore crucial in a wireless network to ﬁrst shape the channel statistics

and then to use link adaptation algorithms that jointly optimize the modu-

lation level, coding rate, and the transmission signaling schemes such as SM,

STC, and beamforming [5]. However, MIMO systems are constrained to

employ ﬁxed antenna parameters, which are determined by the initial

antenna design, over the varying channel condition. Thus, non-reconﬁgurable

antenna designs are unable to shape the channel statistics to minimize interference.

By treating the antenna element properties and array conﬁguration as an

additional component in the joint optimization of the adaptive system

parameters, an additional degree of freedom is achieved. The goal of joint

optimization of antenna array properties and the associated transmission

algorithm can only be achieved if the structural geometry of each individual

element of the array can be dynamically reconﬁgured. MRAs can dynami-

cally reconﬁgure their structural geometry and thus are capable of altering

radiation, polarization, and frequency characteristics to adapt to the changes

in their operating environments. Therefore, an adaptive MIMO system

equipped with MRAs will not be constrained to employ a ﬁxed antenna

design over varying channel conditions. This feature will permit the selection

of the best antenna properties and conﬁguration in conjunction with the

adapted transmission scheme with respect to the channel condition. Thus

the gap between theoretical MIMO performance and practice is minimized.

Figure 9.1 highlights the performance improvement offered by an adaptive

MIMO system equipped with MRAs.

In the next section, ﬁrst the MRA concept is discussed. Then the interre-

lationships among transmission signaling schemes, physical channel condi-

tions, and antenna radiation/polarization properties are identiﬁed so that

the best antenna design for a given transmission-scheme and channel con-

dition is always selected. The following section discusses the RF MEMS

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252 MIMO System Technology for Wireless Communications

technology compatible with microwave laminates for constructing MRA

systems. Finally, a discussion of two different MEMS integrated antennas is

given.

9.2 MRA Concept and Its Links with MIMO Systems

9.2.1 Multifunctional Reconﬁgurable Antenna

In the literature, a smart, intelligent, or adaptive antenna refers to an antenna

array of elements that are typically standard monopoles, dipoles, or patches.

The antenna elements themselves do not possess any intelligence. Intelli-

gence is associated with the signal-processing domain where the time

domain

signals from or to the individual antenna elements are weighted and com-

bined such that the resulting radiation pattern (i.e., the spatial

response of

the array) satisﬁes some conditions. This is the key concept of beamforming

through which the electromagnetic energy is focused in the direction of the

desired signal, with a null placed in the direction of noise or interference

sources. On the other hand, an MRA array consists of antenna elements,

each of which has some intelligence

. This intelligence

stems from the ability

to reconﬁgure the physical structure of individual elements through which

polarization/radiation and frequency properties of the array are changed.

The elements in the MRA array have the ability to intelligently process the

signals in spectral

and angular

domains, adding to the already present time

domain processing of the system. In the language of phased-array antennas,

an MRA array alters not only the array factor but also the element factor. In

FIGURE 9.1

Potential beneﬁt of adaptive MIMO systems employing MRA arrays.

eoretical MIMO gains

Adaptive MIMO with

reconﬁgurabgle antenna

Adaptive MIMO

Beamforming

Space–time

coding

4190_book.fm Page 252 Tuesday, February 7, 2006 12:44 PM

Multifunctional Reconﬁgurable Microelectromechanical Systems

253

current phased-array technology, the element factor cannot be modiﬁed once

individual elements are laid out. The total electric ﬁeld of a linear array of

identical antenna elements with equal spacing can be given as the sum of

the ﬁelds due to the N

elements at the observation point P (R

, V, K)

(9.1)

where R

is the distance between the center of the array and the observation

point, R

is the distance between i

th antenna element and the observation point,

denotes the square root of –1, a

and ^

represent the amplitude and phase

of the excitation, respectively, giving rise to E

relative to a reference excita-

tion, and f

) represents the element factor. Since the elements are identical,

the element factor f

) is the same for all the elements and, hence, this

term can be factored out from the summation resulting in the simple expres-

sion given in Equation 9.1. As is seen from Equation 9.1, the radiation pattern

of a classical phased array antenna is changed only by variation of the

amplitude and/or phase of the excitation (a

and ^

). In an MRA array,

however, elements are not necessarily the same and do not exhibit the iden-

tical directional patterns that result in variable element factor. For example,

an MRA array may be reconﬁgured into a polarization diversity scenario in

which the elements would radiate different senses of polarization, such as

linear, right-hand circular, and left-hand circular. An MRA that can change

its polarization between right-hand and left-hand circular polarization will

be introduced in Section 9.4.

Block diagrams of a conventional smart antenna

array and a reconﬁgurable antenna array are provided in Figure 9.2a and

Figure 9.2b, respectively.

In a reconﬁgurable array, the antenna element spacing can also be changed

allowing efﬁcient selection and application of beamforming and space–time

coding schemes. While beamforming requires antennas to be closely spaced

(antennas are correlated) to avoid the negative effects of side lobes, space–

time coding will perform well if the spacing between antennas is large

enough to ensure low correlation. As a result, a MIMO system with recon-

ﬁgurability in the geometrical domain of antenna will not be constrained to

use the same antenna design over varying channel conditions, resulting in

better utilization of the available channel capacity.

Finally, a reconﬁgurable antenna is also advantageous in terms of the

physical scale of the antenna systems. In today’s miniature, compact, and

highly integrated telecommunication devices, the area devoted to antenna

elements is typically very limited. This has prompted the antenna commu-

nity to actively research small efﬁcient antenna design [6,7]. An antenna is

said to be an electrically small antenna if it can ﬁt inside a sphere of radius

= 1/k

, where k

is the wave number (k

= 2

, Q

is the wavelength) associated

with the radiated electromagnetic ﬁeld. A rule-of-thumb formula that relates

ER E R f

(, ) (, ) (,)

,,VK VK VK==



jikd

ae e





Vcos

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