1. ABSTRACT

Smart antennas are a promising technology to increase the capacity of

cellular systems. However, under severe channel conditions, the capacity gain may

be small. This work presents a general methodology for the analysis of the effect of

the power angular dispersion on the capacity gain when using smart antennas. The

omni-directional case becomes particular case of the presented methodology.

Finally, the maximum number of users is determined for a smart antenna system

and for general antenna beam pattern.

As the growing demand for mobile communications is constantly increasing,

the need for better coverage, improved capacity, and higher transmission quality

rises. Thus, a more efficient use of the radio spectrum is required. Smart antenna

systems are capable of efficiently utilizing the radio spectrum and are a promise for

an effective solution to the present wireless systems’ problems while achieving

reliable and robust, high-speed, high-data-rate transmission. The purpose of this

topic is to provide a broad view of the system aspects of smart antennas. In fact,

smart antenna systems comprise several critical areas such as individual antenna

array design, signal processing algorithms, space-time processing, wireless channel

modeling and coding, and network performance. In this topic an overview of smart

antenna concepts is included.

Aim of this contribution is to illustrate the state of the art of smart antenna

research from several perspectives. The bow is drawn from transmitter issues via

channel measurements and modeling, receiver signal processing, network aspects,

technological challenges towards first smart antenna applications and current status

of standardization. Moreover, some future prospects of different disciplines in

smart antenna research are given.

2. INTRODUCTION

Throughout the world, including the United States, there is significant

research and development on smart antennas for wireless systems. This is because

smart antennas have tremendous potential to enhance the performance of future

generation wireless systems as evidenced by the antennas’ recent deployment in

many systems.

In mobile communication systems, capacity and performance are usually

limited by two major impairments. They are multipath and co-channel interference.

Multipath is a condition which arises when a transmitted signal undergoes

reflection from various obstacles in the propagation environment. This gives rise to

multiple signals arriving from different directions. Since the multipath signals

follow different paths, they have different phases when they are arrive at the

receiver. The result is degradation in signal quality when they are combined at the

receiver due to the phase mismatch. Co-channel interference is the interference

between two signals that operate at the same frequency. In cellular communication

the interference is usually caused by a signal from a different cell occupying the

same frequency band.

Smart antenna is one of the most promising technologies that will enable a

higher capacity in wireless networks by effectively reducing multipath and co-

channel interference. This is achieved by focusing the radiation only in the desired

direction and adjusting itself to changing traffic conditions or signal environments.

Smart antennas employ a set of radiating elements arranged in the form of an array.

Smart antenna systems consist of multiple antenna elements at the transmitting and/or receiving side of the communication link, whose signals are processed adaptively in order to exploit the spatial dimension of the mobile radio channel. Depending on whether the processing is performed at the transmitter, receiver, or both ends of the communication link, the smart antenna technique is defined as

multiple-input single-output (MISO), single-input multiple-output (SIMO), or multiple-input multiple-output (MIMO).

The signals from these elements are combined to form a movable or

switchable beam pattern that follows the desired user. In a Smart antenna system

the arrays by themselves are not smart, it is the digital signal processing that makes

them smart. The process of combining the signals and then focusing the radiation

in a particular direction is often referred to as digital beam-forming.

The early smart antenna systems were designed for use in military

applications to suppress interfering or jamming signals from the enemy. Since

interference suppression was a feature in this system, this technology was

borrowed to apply to personal wireless communications where interference was

limiting the number of users that a network could handle. It is a major challenge to

apply smart antenna technology to personal wireless communications since the

traffic is denser. Also, the time available for complex computations is limited.

However, the advent of powerful, low-cost, digital processing components and the

development of software-based techniques have made smart antenna systems a

practical reality for cellular communications systems.

3. WHAT IS A SMART ANTENNA?Smart antennas are the antenna arrays with smart signal processing

algorithms used to identify spatial signature such as direction of arrival (DOA) of

the signal, and use it to calculate the beam-forming vectors, to track and locate the

antenna beam on the target (mobile-phone). In the context of smart antennas, the

term "antenna" has an extended meaning. The block diagram of Smart Antenna

System is shown below:

Figure 1: Block Diagram of Smart Antenna System It consists of a number of radiating elements, a combining/dividing network

and a control unit. The control unit can be called the smart antenna’s intelligence, normally realized using a DSP component. The processor controls feeder parameters of the antenna, based on several inputs, in order to optimize the communications link. This shows that smart antennas are more than just the antenna,” but rather a complete transceiver concept. One may wonder why it is necessary to invest time and money into such an idea, what was wrong with the current use of the cellular antennas?

In truth, antennas are not smart-antenna systems are smart. Generally co-

located with a base station, a smart antenna system combines an antenna array with

a digital signal-processing capability to transmit and receive in an adaptive,

spatially sensitive manner. In other words, such a system can automatically change

the directionality of its radiation patterns in response to its signal environment. One

should say that their smarts reside in their digital signal processing facilities. Smart

antenna not only combats multipath fading, but also suppresses interference

signals. It employs Diversity and Adaptive combining schemes. Smart Antenna

techniques have been considered mostly for the base stations so far because of high

system complexity and high power consumption. Recently, smart antenna

techniques have been applied to mobile stations or handsets.

The following are distinctions between the two major categories of smart antennas

regarding the choices in transmit strategy:

1. Switched beam-A finite number of fixed, predefined patterns or combining

strategies (sectors).

2. Adaptive array-An infinite number of patterns (scenario-based) that are

adjusted in real time.

3.1 Beam forming

Beam forming is the method used to create the radiation pattern

of the antenna array by adding constructively the phases of the signals

in the direction of the targets (mobile-phones) desired, and nulling the

pattern of the targets (mobile-phones) that are undesired/interfering

targets. This can be done with a simple FIR tapped delay line filter.

The weights of the FIR filter may also be changed adaptively, and

used to provide optimal beam forming, in the sense that it reduces the

MMSE between the desired and actual beam pattern formed. Typical

algorithms are the steepest descent, and LMS algorithms.

3.2 Types of Smart Antenna Systems

There are basically two approaches to implement antennas that dynamically

change their antenna pattern to mitigate interference and multipath affects while

increasing coverage and range. They are

• Switched beam

This type is a phased array or multi-beam antenna, which consists of either a

number of fixed beams with one beam turned on towards the desired signal or a

single beam (formed by phase adjustment only) that is steered towards the desired

signal. The Switched beam approach is simpler compared to the fully adaptive

approach. It provides a considerable increase in network capacity when compared

to traditional omni-directional antenna systems or sector-based systems. In this

approach, an antenna array generates overlapping beams that cover the surrounding

area as shown in figure 2(a). When an incoming signal is detected, the base station

determines the beam that is best aligned in the signal-of-interest direction and then

switches to that beam to communicate with the user.

2(a) 2(b)

Figure 2: Beam formation for switched beam antenna system

•Adaptive Arrays

The Adaptive array system is 'smarter' of the two approaches. The adaptive

antenna array is an array of multiple antenna elements, with the received signals

weighted and combined to maximize the desired signal to interference plus noise

power ratio. This essentially puts a main beam in the direction of the desired signal

and nulls in the direction of the interference. This system tracks the mobile user

continuously by steering the main beam towards the user and at the same time

forming nulls in the directions of the interfering signal as shown in figure 3. Like

switched beam systems, they also incorporate arrays. Typically, the received signal

from each of the spatially distributed antenna elements is multiplied by a weight.

The weights are complex in nature and adjust the amplitude and phase. These

signals are combined to yield the array output. These complex weights are

computed by a complicated adaptive algorithm, which is pre-programmed into the

digital signal-processing unit that manages the signal radiated by the base station.

3(a) 3(b)

Figure 3: Beam formations for adaptive array antenna system

An adaptive beam former is able to automatically update the weight vector, in

order to separate desired signals from interfering signals. Adaptive beam forming

can be done in many ways. Many algorithms exist for many applications, varying

in complexity. It is accomplished using software and advanced signal processing.

The technology combines the inputs of multiple antennas (from an antenna array)

to form very narrow beams toward individual user in a cell.

A generic adaptive beam former is shown in Fig. 4. The weight vector w is

calculated using the signal x (t) received by multiple antennas. An adaptive

processor will minimize the error e (t) between a desired signal d (t) and the array

output y (t). Adaptive beam forming requires sophisticated signal processing,

which until today was considered too expensive for commercial application. The

cost of processing has immensely reduced, making beam forming relevant to the

commercial market as a cost effective solution for wide-scale deployment of

broadband wireless networks. With digital beam forming in a wireless

communication system, the received signals must be available as complex digital

data. Therefore a radio receiver must convert the ‘received RF signals to digital

baseband signals, for every antenna.

Figure 4: Concept of adaptive beam forming

4. SWITCHED BEAM SYSTEMS

This type of adaptive technique actually does not steer or scan the beam in the

direction of the desired signal. Switched beam employs an antenna array which

radiates several overlapping fixed beams covering a designated angular area. It

subdivides the sector into many narrow beams. Each beam can be treated as an

individual sector serving an individual user or a group of users. Consider a

traditional cellular area shown below in figure 5 that is divided into three sectors

with 120° angular width, with each sector served by six directional narrow beams.

The spatially separated directional beams lead to increase in the possible reuse of a

frequency channel by reducing potential interference and also increases the range.

These antennas do not have a uniform gain in all directions but when compared to

a conventional antenna system they have increased gain in preferred directions.

The switched beam antenna has a switching mechanism that enables it to select and

then switch the right beam which gives the best reception for a mobile user under

consideration. The selection is usually based on maximum received power for that

user. The same beam can be used both for uplink and downlink communication.

Figure 5: Switched beam coverage pattern

A typical switched beam system for a base station would consist of multiple

arrays with each array covering a certain sector in the cell. Consider a switched

beam forming system shown in figure 6. It consists of a phase shifting network,

which forms multiple beams looking in certain directions. The RF switch actuates

the right beam in the desired direction. The selection of the right beam is made by

the control logic. The control logic is governed by an algorithm which scans all the

beams and selects the one receiving the strongest signal based on a measurement

made by the detector.

Figure 6: Block diagram of Switched beam systems

This technique is simple in operation but is not suitable for high interference

areas. Let us consider a scenario where User 1 who is at the side-edge of the beam

which he is being served by. If a second user were at the direction of the null then

there would be no interference but if the second user moves into the same area of

the beam as the first user he could cause interference to the first user. Therefore

switched beam systems are best suited for a little or zero-interference environment.

In case of a multipath signal there is a chance that the system would switch the

beam to the indirect path signal rather than the direct path signal coming from the

user. This leads to the ambiguity in the perception of the direction of the received

signal, thus, switched beam systems are only used for the reception of signals.

Since these antennas have non-uniform gains between the beams the mobile user

when moving away from the edge of the beam is likely to suffer from a call loss

before he is handed off to the next beam because there is no beam serving that

area. Also, these systems lead to frequent hand-offs when the mobile user is

actively moving from the area of one beam to another. Therefore these intra-cell

hand-offs have to be controlled. Switched beam systems cannot reduce multipath

interference components with a direction of arrival close to that of the desired

signal. Despite of all these disadvantages, the switched beam approach is less

complicated (compared to the completely adaptive systems) and provides a

significant range extension, increase in capacity, and a considerable interference

rejection when the desired user is at the center of the beam. Also, it less expensive

and can be easily implemented in older systems.

Different approaches can be used to provide the fixed beams in a Switched Beam

system. Some of them are discussed below which use fixed phase shifting

networks:

4.1 Butler Matrix Arrays

In this approach a Butler Matrix is used to provide the necessary

phase shift for a linear antenna array. An N×N butler matrix can produce N

beams looking in different directions with an N-element array. An N×N

butler matrix requires an (N/2) log2 (N) 90° hybrids interconnected by rows

of (N/2) (log2 (N)-1) fixed phase shifters to form the beam pattern. When a

signal impinges upon the input port of the Butler Matrix, it produces a

different inter-element phase shifts between the output ports. The set of

different inter-element phase shifts is given by:

Where N is the number of ports of the matrix

Consider the 8×8 Butler matrix array shown in figure 7. It consists of

twelve 90° hybrids and eight fixed phase shifters that form a beam forming

network. When one of the input ports is excited by an RF signal, all the

output ports feeding the array elements are equally excited but with a

progressive phase between them. This results in the radiation of the beam at

a certain angle. For example if the 2R beam needs to be activated then the

2R input port needs to be activated. If multiple beams are required, two or

more input ports need to be excited simultaneously. Figure 8 shows the

radiation of two beams 1R and 3L, which is achieved by simultaneous

excitation of input ports 1R and 3L. Each beam can have a dedicated

transmitter and/or receiver, or a single transmitter and/or receiver and the

appropriate beam can be selected using an RF switch as mentioned earlier.

Figure 7: 8×8 Butler Matrix array

Figure 8: Radiation pattern for 8×8 Butler Matrix array

The Butler matrix is one of the most popular switched beam networks.

It is easy to implement and requires few components to build compared to

other networks. The loss involved is very small, which comes from the

insertion loss in hybrids, phase shifters and transmission lines. However in a

butler matrix, beam width and beam angles tend to vary with frequency

causing the beam squint with frequency. Also, as the matrices get bigger,

more and more crossovers make interconnections complex.

4.2 Blass Arrays The Blass matrix uses directional couplers and transmission lines to

provide the necessary phase shift for the arrays in order to produce multiple

beams. Figure 9 shows an 8-element array fed by a Blass Matrix. Each node

is the direction coupler to cross-connect the transmission lines. Port 0

provides equal delays to all elements and hence produces a broad side beam,

whereas other ports provide progressive time delays between elements and

hence produces beams at different angles. Therefore, when you send signal

into the different inputs, you will get different steering angles. The Blass

Matrix is simple but has a low performance because its loss is attributed to

the resistive terminations.

The Blass matrix is simple in the sense that it has simpler

interconnection layout of the circuit since it does not involve any crossovers

as in Butler matrix. There is no beam squinting with frequency. However

they require more components compared to the Butler matrix, which makes

it costlier and heavier.

Figure 9: Blass Matrix beam forming network

5. ADAPTIVE ARRAY SYSTEMS

From the previous discussion it was quite apparent that switched beam

systems offer limited performance enhancement when compared to

conventional antenna systems in wireless communication. However, greater

performance improvements can be achieved by implementing advanced signal

processing techniques to process the information obtained by the antenna

arrays. Unlike switched beam systems, the adaptive array systems are really

smart because they are able to dynamically react to the changing RF

environment. They have a multitude of radiation patterns compared to fixed

finite patterns in switched beam systems to adapt to the ever-changing RF

environment. An Adaptive array, like a switched beam system uses antenna

arrays but it is controlled by signal processing. This signal processing steers the

radiation beam towards a desired mobile user, follows the user as he moves, and

at the same time minimizes interference arising from other users by introducing

nulls in their directions. This is illustrated in a simple diagram shown below in

figure 10.

Figure 10: Beam formation for adaptive array antenna system

The adaptive array systems are really intelligent in the true sense and can

actually be referred to as smart antennas. The smartness in these systems comes

from the intelligent digital processor that is incorporated in the system. The

processing is mainly governed by complex computationally intensive algorithms.

5.1 Basic Working Mechanism

A smart antenna system can perform the following functions: first the

direction of arrival of all the incoming signals including the interfering

signals and the multipath signals are estimated using the Direction of Arrival

algorithms. Secondly, the desired user signal is identified and separated from

the rest of the unwanted incoming signals. Lastly a beam is steered in the

direction of the desired signal and the user is tracked as he moves while

placing nulls at interfering signal directions by constantly updating the

complex weights.

As in the case of phased arrays it is quite evident that the direction of

radiation of the main beam in an array depends upon the phase difference

between the elements of the array. Therefore it is possible to continuously

steer the main beam in any direction by adjusting the progressive phase

difference β between the elements. The same concept forms the basis in

adaptive array systems in which the phase is adjusted to achieve maximum

radiation in the desired direction. To have a better understanding of how an

adaptive array system works, let us consider a typical adaptive digital beam

forming network shown below in figure 11.

Figure 11: Block diagram of Adaptive array systems

In a beam forming network typically the signals incident at the

individual elements are combined intelligently to form a single desired beam

formed output. Before the incoming signals are weighted they are brought

down to baseband or intermediate frequencies (IF’s). The receivers provided

at the output of each element perform the necessary frequency down

conversion. Adaptive antenna array systems use digital signal processors

(DSP’s) to weight the incoming signal. Therefore it is required that the

down-converted signal be converted into digital format before they are

processed by the DSP. Analog-to-digital converters (ADC’s) are provided

for this purpose. For accurate performance, they are required to provide

accurate translation of the RF signal from the analog to the digital domain.

The digital signal processor forms the heart of the system, which accepts the

IF signal in digital format and the processing of the digital data is driven by

software. The processor interprets the incoming data information,

determines the complex weights (amplification and phase information) and

multiplies the weights to each element output to optimize the array pattern.

The optimization is based on a particular criterion, which minimizes the

contribution from noise and interference while producing maximum beam

gain at the desired direction. There are several algorithms based on different

criteria for updating and computing the optimum weights.

5.2 Adaptive Algorithm Classification

The adaptive algorithms can be classified into categories based on

different approaches.

Based on adaptation

1. Continuous adaptation: Algorithms based on this approach adjust

the weights as the incoming data is sampled and keep updating it such

that it converges to an optimal solution. This approach is suitable

when the signal statistics are time varying.

Examples: The Least Mean Square (LMS) algorithm and the

Recursive Least square (RLS) algorithm.

2. Block adaptation: Algorithms based on this approach compute the

weights based on the estimates obtained from a temporal block of

data. This method can be used in a non-stationary environment

provided the weights are computed periodically.

Example: The Sample Matrix Inversion (SMI) algorithm.

Based on information required

1. Reference signal based algorithms: These types of algorithms are

based on minimization of the mean square error between the received

signal and the reference signal. Therefore it is required that a

reference signal be available which has high correlation with the

desired signal.

Examples: The Least Mean Square (LMS) algorithm, The Recursive

Least square (RLS) algorithm and the Sample Matrix Inversion (SMI)

algorithm

The reference signal is not the actual desired signal, in fact it is

a signal that closely represents it or has strong correlation with it.

Reference signals required for the above algorithms are generated in

several ways. In TDMA every frame consists of a sequence, which

can be used as a reference signal. In digital communication,

synchronization signals can be used for the same purpose.

2. Blind adaptive algorithms: These algorithms do not require any

reference signal information. They themselves generate the required

reference signal from the received signal to get the desired signal.

Examples: The Constant Modulus Algorithm (CMA), The Cyclo-

stationary algorithm, and the Decision-Directed algorithm.

6. Comparison Between switched beam and adaptive array systems

Switched beam system

• It uses multiple fixed directional beams with narrow beam-widths.

• The required phase shifts are provided by simple fixed phase shifting

networks like the butler matrix.

• They do not require complex algorithms; simple algorithms are used for beam

selection.

• It requires only moderate interaction between mobile unit and base station as

compared to adaptive array system.

• Since low technology is used it has lesser cost and complexity.

• Integration into existing cellular system is easy and cheap.

• It provides significant increase in coverage and capacity compared

conventional antenna based systems.

• Since multiple narrow beams are used, frequent intra-cell hand-offs between

beams have to be handled as mobile moves from one beam to another.

• It cannot distinguish between direct signal and interfering and/or multipath

signals, this leading to undesired enhancement of the interfering signal more

than the desired signal.

• Since there is no null steering involved; Switched beam systems offers limited

co-channel interference suppression as compared to the adaptive array

system.

Adaptive array system

• A complete adaptive system; steers the beam towards desired signal-of-

interest and places nulls at the interfering signal directions.

• It requires implementation of DSP technology.

• It requires complicated adaptive algorithms to steer the beam and the nulls.

• It has better interference rejection capability compared to Switched beam

systems.

• It is not easy to implement in existing systems, i.e. up-gradation is difficult

and expensive.

• Since continuous steering of the beam is required as the mobile moves; high

interaction between mobile unit and base station is required.

• Since the beam continuously follows the user; intra-cell hand-offs are less.

7. Benefits of Smart Antenna Technology

7.1 Reduction in co-channel interference

Smart antennas have a property of spatial filtering to focus radiated

energy in the form of narrow beams only in the direction of the desired

mobile user and no other direction. In addition they also have nulls in their

radiation pattern in the direction of other mobile users in the vicinity.

Therefore there is often negligible co-channel interference.

7.2 Range improvement

Since smart antennas employs collection of individual elements in the

form of an array they give rise to narrow beam with increased gain when

compared to conventional antennas using the same power. The increase in

gain leads to increase in range and the coverage of the system. Therefore

fewer base stations are required to cover a given area.

7.3 Increase in capacity

Smart antennas enable reduction in co-channel interference, which

leads to increase in the frequency reuse factor. That is smart antennas allow

more users to use the same frequency spectrum at the same time bringing

about tremendous increase in capacity.

7.4 Reduction in transmitted power

Ordinary antennas radiate energy in all directions leading to a waste of

power. Comparatively smart antennas radiate energy only in the desired

direction. Therefore less power is required for radiation at the base station.

Reduction in transmitted power also implies reduction in interference

towards other users.

7.5 Reduction in handoff

To improve the capacity in a crowded cellular network, congested cells

are further broken into micro cells to enable increase in the frequency reuse

factor. This results in frequent handoffs, as the cell size is smaller. Using smart

antennas at the base station, there is no need to split the cells since the capacity

is increased by using independent spot beams. Therefore, handoffs occur rarely,

only when two beams using the same frequency cross each other.

7.6 Mitigation of multipath effects

Smart antennas can either reject multipath components as

interference, thus mitigating its effects in terms of fading or it can use the

multipath components and add them constructively to enhance system

performance.

7.7 Compatibility

Smart antenna technology can be applied to various multiple access

techniques such as TDMA, FDMA, and CDMA. It is compatible with

almost any modulation method and bandwidth or frequency band.