Introduction



1.INTRODUCTION

Global demand for voice, data and video related services continues to grow faster than the required infrastructure can be deployed. Despite huge amount of money that has been spent in attempts to meet the need of the world market, the vast majority of people on Earth still do not have access to

quality communication facilities. The greatest challenge faced by governments and service providers is

the “last-mile” connection, which is the final link between the individual home or business users and

worldwide network. Copper wires, traditional means of providing this “last-mile” connection is both

costly and inadequate to meet the needs of the bandwidth intensive applications. Coaxial cable and

power line communications all have technical limitations. And fiber optics, while technically superior

and widely used in backbone applications, is extremely expensive to install to every home or business

user. This is why more and more the wireless connection is being seen as an alternative to quickly

and cost effectively meeting the need for flexible broadband links

The universal and spread use of mobile phone service is a testament to the public’s acceptance of

wireless technology. Many of previously non-covered parts of the world now boast of quality voice

service thanks in part to the PCS (Personal Communications Service) or cellular type wireless systems.

Over the last few years the demand for service provision via the wireless communication bearer has

risen beyond all expectations. At the end of the last century more than 20 million users in the United

States only utilized this technology [2]. At present the number of cellular users is growing annually

by approximately 50 percent in North America, 60 percent in western Europe, 70 percent in Australia

and Asia and more than 200 percent in South America.

The proliferation of wireless networks and an increase in the bandwidth required has led to shortages in the scarcest resource of all, the finite number of radio frequencies that these devices use. This has increased the cost to obtain the few remaining licenses to use these frequencies and the related

infrastructure costs required to provide these services.

In a majority of currently deployed wireless communication systems, the objective is to sell a product at a fair price (the product being information transmission) . From a technical point of view,

information transmission requires resources in the form of power and bandwidth. Generally, increased

transmission rates require increased power and bandwidth independently of medium. While, on the

one hand, transmission over wired segments of the links can generally be performed independently

for each link (if we ignore the cross-talk in land lines) and, on the other hand, fibers are excellent

at confining most of the useful information (energy) to a small region in space, wireless transmission

is much less efficient. Reliable transmission over relatively short distances in space requires a large

amount of transmitted energy, spread over large regions of space, only a very small portion of which

is actually received by the intended user. Most of the wasted energy is considered as interference to

other potential users of the system.

Somewhat simplistically, the maximum range of such systems is determined by the amount of power that can be transmitted (and therefore received) and the capacity is determined by the amount of

spectrum (bandwidth) available. For a given amount of power (constrained by regulation or practical

considerations) and a fixed amount of bandwidth (the amount one can afford to buy) there is a finite

(small) amount of capacity (bits/sec/Hz/unit-area, really per unit-volume) that operators can sell to

their customers, and a limited range over which customers can be served from any given location.

Thus, the two basicp roblems that arise in such systems are:

1. How to acquire more capacity so that a larger number of customers can be served at lower costs

maintaining the quality at the same time, in areas where demand is large (spectral efficiency).

2. How to obtain greater coverage areas so as to reduce infrastructure and maintenance costs in

areas where demand is relatively small (coverage).

In areas where demand for service exceeds the supply operators have to offer, the real game being

played is the quest for capacity. Unfortunately, to date a universal definition of capacity has not

evolved. Free to make their own definitions, operators and consumers have done so. To the consumer,

it is quite clear that capacity is measured in the quality of each link he gets and the number of times

he can successfully get such a link when he wants one. Consumers want the highest possible quality

links at the lowest possible cost. Operators, on the other hand, have their own definitions of capacity

in which great importance is placed on the number of links that can simultaneously be established.

Since the quality and number of simultaneous links are inversely related in a resource-constrained

environment, operators lean towards providing the lowest possible quality links to the largest possible

number of users. The war wages on: consumers are wanting better links at lower costs, and operators

are continually trying to maximize profitability providing an increasing number of lower quality links

at the highest acceptable cost to the consumer. Until the quest for real capacity is successful, the

battle between operators and their consumers over capacity, the precious commodity that operators

sell to consumers, will continue.

There are many situations where coverage, not capacity, is a more important issue. Consider the

rollout of any new service. Prior to initiating the service, capacity is certainly not a problem -operators have

no customers. Until a significant percentage of the service area is covered, service cannot begin. Clearly, coverage is an important issue during the initial phases of system deployment.

Consider also that in many instances only an extremely small percentage of the area to be served is

heavily populated. The ability to cover the service area with a minimum amount of infrastructure

investment is clearly an important factor in keeping costs down.

As it is often painfully obvious to operators, the two requirements, increased capacity and increased

range, conflict in most instances. While up to recently used technology can provide for increased

range in some cases and up to a limit increased capacity in other cases, it rarely can provide both

simultaneously.

The International Mobile Telecommunications-2000 (IMT2000) and the European Universal Mobile

Telecommunications System (UMTS) are two systems among the others that have been proposed to

take wireless communications into this century . The core objective of both systems is to take the

“personal communications user” into new information society where mass-market low-cost telecommunications.

services will be provided. In order to be universally accepted, these new networks have to

offer mobile access to voice, data and multimedia facilities in an extensive range of operational environments,

as well as economically supporting service provision in environments conventionally served

by other wired systems. None of the proposals that include improved air interface and modulation

schemes, deployment of smaller radio cells with combinations of different cell types in hierarchical architectures, and advanced signal processing, fully exploit the multiplicity of spatial channels that arises because each mobile user occupies a unique spatial location. Space is truly one of the final frontiers when it comes to new generation wireless communication systems. Spatially selective transmission and reception of RF energy promises substantial increases in wireless system capacity, coverage and quality. That this is certainly the case is attested to by the significant number of companies that have been recently brought the products based on such concepts to the wireless market place. Filtering in the space domain can separate spectrally and temporally overlapping signals from multiple mobile units.

MA (CDMA). This approach is usually referred to as space-division multiple access (SDMA) and

enables multiple users within the same radio cell to be accommodated on the same frequency and

frequency-division multiple access (FDMA), time-division MA (TDMA) and code-division

time slot

Realization of this filtering technique is accomplished using smart antennas, which are effectively

antenna systems capable of modifying its time, frequency and spatial response. By exploiting the

spatial domain via smart antenna systems, the operational benefits to the network operator can be

summarized as follows:

• Capacity enhancement. SDMA with smart antennas allows for multiple users in a cell to use

the same frequency without interfering with each other since the Base Station smart antenna

beams are sliced to keep different users in separate beams at the same frequency.

• Coverage extension. The increase in range is due to a bigger antenna gain with smart antennas.

This would also mean that fewer Base Stations might be used to cover a particular geographical

2.EVOLUTION FROM OMNIDIRECTIONAL TO SMART ANTENNAS

An antenna in a telecommunications system is the port through which radio frequency (RF) energy is coupled from the transmitter to the outside world for transmission purposes, and in reverse, to

the receiver from the outside world for reception purposes . To date, antennas have been the most neglected of all the components in personal communications systems. Yet, the manner in which

radio frequency energy is distributed into and collected from space has a profound influence upon

the efficient use of spectrum, the cost of establishing new personal communications networks and the

service quality provided by those networks. The goal of the next several sections is to answer to the

question “Why to use anything more than a single omnidirectional (no preferable direction) antenna

at a base station?” by describing, in order of increasing benefits, the principal schemes for antennas

deployed at base stations.

2.1Omnidirectional Antennas

Since the early days of wireless communications, there has been the simple dipole antenna, which

radiates and receives equally well in all directions (direction here being referred to azimuth). To

find its users, this single-element design broadcasts omnidirectionally in a pattern resembling ripples

radiation outward in a pool of water

While adequate for simple RF environments where no specific knowledge of the users’ whereabouts is either available or needed, this unfocused approach scatters signals, reaching desired users with only a small percentage of the overall energy sent out into the environment . Given this limitation, omnidirectional strategies attempt to overcome environmental challenges by simply boosting the power level of the signals broadcast. In a setting of numerous users (and interferers), this makes a bad

situation worse in that the signals that miss the intended user become interference for those in the same or adjoining cells. In uplink applications (user to base station), omnidirectional antennas offer no preferential gain for the signals of served users. In other words, users have to shout over competing

signal energy. Also, this single-element approach cannot selectively reject signals interfering with

those of served users and has no spatial multipath mitigation or equalization capabilities. Therefore,

omnidirectional strategies directly and adversely impact spectral efficiency, limiting frequency reuse.

These limitations of broadcast antenna technology regarding the quality, capacity, and geographic

coverage of wireless systems prompted an evolution in the fundamental design and role of the antenna

in a wireless system.

2.2 Directional Antennas and Sectorized Systems

A single antenna can also be constructed to have certain fixed preferential transmission and reception directions. Sectorized antenna system take a traditional cellular area and subdivide it into sectors that are covered using directional antennas looking out from the same base station location .

Operationally, each sector is treated as a different cell in the system, the range of which can be greater than in the omni directional case, since power can be focused to a smaller area. This is commonly referred to as antenna element gain. Additionally, sectorized antenna systems increase the possible

reuse of a frequency channel in such cellular systems by reducing potential interference across the

original cell. As many as six sectors have been used in practical service, while more recently up to

16 sectors have been deployed . However, since each sector uses a different frequency to reduce cochannel interference, handoffs (handovers) between sectors are required. Narrower sectors give better

performance of the system, but this would result in to many handoffs.

While sectorized antenna systems multiply the use of channels, they do not overcome the major

disadvantages of standard omnidirectional antennas such as filtering of unwanted interference signals

from adjacent cells.

2.3 Diversity Systems

Wireless communication systems are limited in performance and capacity by three major impairments. The first of these is multipath fading, which is caused by multiple paths that

the transmitted signal can take to the receive antenna. The signals from these paths add with different

phases, resulting in a received signal amplitude and phase that vary with antenna location, direction

and polarization as well as with time (with movement in the environment). The second impairment

is delay spread, which is the difference in propagation delays among the multiple paths. When the

delay spread exceeds about 10 percent of the symbol duration, significant intersymbol interference

can occur, which limits the maximum data rate. The third impairment is co-channel interference.

Cellular systems divide the available frequency channels into channel sets, using one channel set per

cell, with frequency reuse (e.g. most TDMA systems use a frequency reuse factor of . This results in

co-channel interference, which increases as the number of channel sets decreases (i.e. as the capacity

of each cell increases). In TDMA systems, the co-channel interference is predominantly from one or

two other users, while in CDMA systems there are typically many strong interferers both within the

cell and from adjacent cells. For a given level of co-channel interference (channel sets), capacity can be

increased by shrinking the cell size, but at the cost of additional base stations. We define the diversity

gain (which is possible only with multipath fading) as the reduction in the required average output

signal-to-noise ratio for a given BER with fading.

There are three different ways to provide low correlation (diversity gain): spatial, polarization and

angle diversity.

For spatial diversity, the antennas are separated far enough for low fading correlation. The required separation depends on the angular spread, which is the angle over which the signal arrives at the

receive antennas. With handsets, which are generally surrounded by other objects, the angular spread

is typically 3600, and quarter-wavelength spacing of the antennas is sufficient.

For outdoor systems with high base station antennas, located

above the clutter, the angular spread may be only a few degrees (although it can be much higher in urban areas), and a horizontal separation of 10-20 wavelengths is required, making the size of the

antenna array an issue.

For polarization diversity, two orthogonal polarizations are used (they are often ±450). These orthogonal polarizations have low correlation, and the antennas can have a small profile. However,

polarization diversity can only double the diversity, and for high base station antennas, the horizontal

polarization can be 6−10 dB weaker than the vertical polarization, which reduces the diversity gain.

For angle diversity, adjacent narrow beams are used. The antenna profile is small, and the adjacent

beams usually have low fading correlation.

However, with small angular spread, when the received signal is mainly arriving on one beam, the adjacent beams can have received signal levels more than 10 dB weaker than the strongest beam, resulting in small diversity gain.

Three antenna diversity options with four antenna elements for a 1200 sectorized system shows spatial diversity with approximately seven wavelengths (7λ) spacing between elements (3.3 m at 1900 MHz). A typical antenna element has an 18 dBi gain with a 650 horizontal and 80 vertical beamwidths. two dual polarization antennas, where the antennas can be either closely spaced (λ/2) to provide both angle and polarization diversity in a small profile, or widely spaced (7λ) to provide both spatial and polarization diversity. The antenna elements shown are 450 slant polarization antennas, which are also commonly used, rather than vertically and horizontally polarized antennas. Finally shows a closely spaced (λ/2) vertically polarized array, which provides angle diversity in a small profile. polarization diversity with angular and spatial diversity; (c) angular diversity.

Diversity offers an improvement in the effective strength of the received signal by using one of the following two methods

• Switched diversity. Assuming that at least one antenna will be in a favorable location at a given

moment, this system continually switches between antennas (connects each of the receiving

channels to the best serving antenna) so as always to use the element with the highest signal

power.

• Diversity combining. This approach corrects the phase error in two multipath signals and effectively

combines the power of both signals to produce gain. Other diversity systems, such as

maximal ratio combining systems, combine outputs of all the antennas to maximize the ratio of

combined received signal energy to noise.

The diversity antennas merely switch operation from one working element to the other. Although

this approach mitigates severe multipath fading, its use of one element at a time offers no uplink

gain improvement over any other single-element approach. The diversity systems can be useful in

environments where fading is the dominant mechanism for signal degradation.

In environments with significant interference, however, the simple strategies of locking onto the strongest signal or extracting maximum signal power from the antennas are clearly inappropriate and can result in crystal-clear reception of an interferer at the expense of the desired signal.

The need to transmit to numerous users more efficiently without compounding the interference problem led to the next step of the evolution antenna systems that intelligently integrate the simultaneous

operation of diversity antenna elements.

3. SMART ANTENNA TECHNOLOGY

In mobile communication systems, capacity and performance are usually limited by two major impairments. They are multipath and co-channel interference [5]. 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. 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 beamforming . This term will be extensively used in the following sections.

[pic] [pic]

3.1 phased array 3.2 adaptive array

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 has made smart antenna systems a practical reality for cellular communications systems

4. 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

• Adaptive Arrays

The Switched beam approach is simpler compared to the fully adaptive approach. It provides a considerable increase in network capacity when compared to traditional omnidirectional antenna systems or sector-based systems. In this approach, an antenna array generates overlapping beams that cover the surrounding area as shown in figure 4.1. 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.

[pic]

4.1 Beam formation for switched beam antenna system

The Adaptive array system is the “smarter” of the two approaches. 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 . 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.

[pic]

4.2 Beam formation for adaptive array antenna system

4.1 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 that is divided into three sectors with 120° angular width, with each sector served by six directional narrow beams. The spatially separated directional beams leads 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. Note that same beam can be used both for uplink and downlink communication.

[pic]

4.3 Switched beam coverage pattern

A typical switched beam system for a base station would consists of multiple arrays with each array covering a certain sector in the cell. Consider a switched beamforming system shown in figure . 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.

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 a non-uniform gain between

Phase Shifting N/W

RF Switch

or

Control Log

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 of 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:

4.2 Butler Matrix Arrays

In this approach a Butler Matrix is used to provide the necessary phase shift for a linear antenna array. Abutler matrix can producebeams looking in different directions with an N-element array. A butler matrix requires an ( 90° hybrids interconnected by rows of NN×/(N NNN×)(log2)(log)2/2NN)1)(2−Nfixed 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.

Consider the8 Butler matrix array . 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

[pic]

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, beamwidth 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.simultaneously. 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 usinganRFswitchasmentionedearlier.

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 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.

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

[pic]

4.4 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.

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 discussed previously in the section 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 beamforming

In a beamforming network typically the signals incident at the individual elements are combined intelligently to form a single desired beamformed 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. ADAPTIVE ALGORITHM CLASSIFICATIONS

The adaptive algorithms can be classified into categories based on different approaches

Based on adaptation

5.1. 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.

5.2. 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 Cyclostationary algorithm, and the Decision-Directed algorithm

The above-mentioned examples and more will be further discussed in a brief manner next in the Adaptive Beamforming section.

PARISON BETWEEN SWITCHED BEAM AND ADAPTIVE ARRAY SYSTEMS SWITCHED BEAM SYSTEM

• It uses multiple fixed directional beams with narrow beamwidths.

• 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. upgradation 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.

• It provides better coverage and increased capacity because of improved interference rejection as compared to the Switched beam system.

• It can either reject multipath components or add them by correcting the delays to enhance the signal quality.

7.BENEFITS OF SMART ANTENNA TECHNOLOGY

7.1 Reduction in co-channel interference

Smart antennas has 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.

Who can use smart antennas

• Smart antenna technology can significantly improve wireless system performance and economics for a range of potential users.

• It enables operators of PCS, cellular, and wireless local loop (WLL) networks to realize significant increases in signal quality, capacity, and coverage.

8.USES OF SMART ANTENNA

• Phased arrays are mainly being studied for point-to-point wireless systems, e.g., for wireless local loops.

• Adaptive arrays are being considered on cellular terminals where local scattering causes wide angular spread.

• In the TDMA system ANSI-136 adaptive antenna algorithms have been widely deployed.

9. CONCLUSION

• The use of smart antennas is not purely a radio transmission issue.

• It also influences network services such as handover and connection setup.

A smart antenna is a digital wireless communications antenna system that takes advantage of diversity effect at the source (transmitter), the destination (receiver), or both.

10. REFERENCES

1. “Smart Antenna Systems Tutorial”, The International Engineering Consortium,

2. Lehne, P.H. and Pettersen M., “An Overview of Smart Antenna Technology for Mobile Communications Systems”, IEE Communications Surveys, Fourth Quarter 1999, vol. 2, no.4,

3. Schüttengruber, W., Molisch A.F. and Bonek E., “Smart Antennas for Mobile Communications Tutorial”,

4. “Smart Antennas Tutorial,”

5. “Smart Antennas – A Non-technical Introduction”, SYMENA Software & Consulting GmbH, Antennas - A Nontechnical Introduction - SYMENA.pdf

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