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Smart Antennas in 3G Network

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Smart Antennas in 3G Network

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Smart Antennas in 3G Network

  1. 1. Smart Antenna in 3G Networks Syed Abdul Basit Advisor: Engr. Tabeer H. Ikram College of Engineering Pakistan Air Force - Karachi Institute of Economics & Technology, Korangi Creek Karachi – 74190 (Pakistan) sabasit2006@gmail.com Abstract The technology of smart antenna for mobile communications has received enormous interest worldwide in recent decade, especially in WiMax. A smart antenna forms a pattern that adapts to the current radio conditions improving the communication link. The main reason for applying smart antennas is the possibility for a large increase in capacity and to introduce new services. The purpose of this paper is to give an introduction of smart antennas in 3G networks, its algorithms used in creating beamforming patterns, how the cell capacity and coverage improves, and what benefits will get from it. Keywords: Smart Antennas (SA), Adaptive Antennas (AA), Switched Beam Antennas. 1. Introduction With the development of mobile communication industry, frequency resources are becoming a bottleneck for mobile service operators, which will be more severe as subscribers increasing at explosive rate [1] . Base station antennas have up till now been omnidirectional or sectored. This can be regarded as a "waste" of power as most of it will be radiated in other directions than toward the user. In addition, the power radiated in other directions will be experienced as interference by other users. The idea of smart antennas is to use base station antenna patterns that are not fixed, but adapt to the current radio conditions. This can be visualized as the antenna directing a beam toward the communication partner only. The difference between the fixed and the smart antenna concept is illustrated in Figure 1. Smart antennas will lead to a much more efficient use of the power and spectrum, increasing the useful received power as well as reducing interference. The purpose of smart antenna is to transform its main lobe and gain into the desired direction through automatic means. 2. Smart Antennas Basic Concepts Antenna Elements: The functions of SA are conducted by both antenna array as well as base-band digital signal processor [5] . The elements can be arranged in many structures, such as uniform linear array (ULA), uniform Figure 1: Range extension using an adaptive antenna [2]
  2. 2. circle array (UCA), etc. The distance between two elements is half of wavelength, which showed in Figure 2 and Figure 3. SA utilizes 4 to 16 antennas structure and makes element distance 1/2 wavelengths in FDD (Frequency Division Duplexing) mode and 5 wavelengths in TDD (Time Division Duplexing) mode [6] . SA verdicts the direction of arrival of user signal (i.e. DOA estimation) by means of digital signal processing technology, as well as forms an antenna main beam in this direction. The elevation angle of main beam to each antenna element is identical, and its azimuth angle diagram is controlled by base-band processor which produces a large number of beams simultaneously. According to the distribution of users, beams are formed in the range of 360 [7] . Beamforming 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/mobiles desired, and nulling the pattern of the targets/mobiles that are undesired/interfering targets. This can be done with a simple FIR tapped delay line filter. SA utilizes digital method to fulfill beamforming, i.e. DBF (Digital Beam Forming) antenna, which makes adaptive algorithm update in software designing and makes system more flexible on the premise not changing system hardware configuration [5] . And then DBF summates the weighted antenna signals to process formed antenna beams, of which main beam aims at expected users and zero point aims at interference directions. Sectorization schemes, which attempt to reduce interference and increase capacity, are the most commonly used spatial technique that have been used in current mobile communications systems for years. Cells are broken into three or six sectors with dedicated antennas and RF paths. Increasing the amount of sectorization reduces the interference seen by the desired signal. One drawback of current sectorization techniques is that their efficiency decreases as the number of sectors increases due to antenna pattern overlap. Furthermore, increasing the number of sectors increases the handoffs the mobile experiences while moving across the cell. Compare this technique to that of a narrow beam being directed towards a desired user. It is clear that some interference that would have been seen by the existing 120° sector antenna will be outside the beamwidth of the array. Any reduction in the interference level translates into system capacity improvements. Smart antennas could be divided into two major types, fixed multiple beams and AA systems. Both systems attempt to increase gain in the direction of the user. This could be achieved by directing the main lobe, with increased gain, in the direction of the user, and nulls in the directions of the interference [3, 4] . 3. Types of Smart Antennas Smart Antennas consists of switched beam antenna and adaptive array antenna. Switched beam antenna can cover entire user cell by means of several parallel beams whose direction is fixed and beamwidth is decided by the number of antenna elements [5] . Taking advantage of base-band digital signal processing technology, adaptive arrays allow the antenna to steer the beam to any direction of interest while simultaneously nulling interfering signals. Figure 2: 4-element ULA [5] Figure 3: 8-element UCA [5]
  3. 3. Switched Beam Antennas: The switched beam method is considered an extension of the current cellular sectorization scheme. The switched beam approach further subdivides the macro-sectors into several micro-sectors. Each micro-sector contains a predetermined fixed beam pattern with the greatest gain placed in the center of the beam. When a mobile user is in the vicinity of a micro-sector, the switched beam system selects the beam containing the strongest signal. During the call, the system monitors the signal strength and switches to other fixed beams if required. Adaptive Arrays: The main advantage of adaptive antenna arrays compared with switched beam antennas is their ability to steer beams towards desired users and nulls toward interfering signals as they move around a sector. Several beamforming approaches exist with varying degrees of complexity. A conventional beamformer or delay-and-sum beamformer has all the weights of equal magnitudes. To steer the array in a particular direction, the phases are selected appropriately. In order to be able to null an interfering signal, the null-steering beamformer can be used to cancel a plane wave arriving from a known direction producing a null in the response pattern at this direction. See Figure 4 and 5. 4. Weight Adaptation Algorithms In the beamforming case the major question is: How to calculate the complex weights w the individual antenna elements for each user? Before answering this question one should reflect upon the different processes in the baseband signal processing unit, before the antenna weights can be adapted. Basically the signal processing unit is responsible for the user identification, user separation and beam forming. First, the base station has to estimate the directions of arrival of all multipath components. Next, it has to determine whether the echo from a certain direction comes from a desired user or from an interferer. Finally, it can compute the antenna weights in order to increase the SNIR as much as possible [11] . Adaptation algorithms are designed to process the above mentioned demands. They can basically be classified as temporal reference (TR), spatial reference (SR) and blind (BA) algorithms. 4.1 Temporal Reference Algorithms TR algorithms are based on the prior knowledge of the time structure of parts of the received signals. The training sequences of both 2G and 3G systems fulfill this requirement. The receiver adjusts the complex weights in such a way that the difference between the combined signal at the output and the known training sequence is minimized. Those weights are then used for the reception of the actual data [11] . Figure 4: Switched multibeam antennas has fixed beam pattern [10] . Figure 5: Adaptive antenna array has variable beam pattern depend upon the location of the user [10] .
  4. 4. 4.2 Spatial Reference Algorithms SR algorithms estimate the direction of arrival (DOA) of both the desired and interfering signals. They are based on the prior knowledge of the physical antenna geometry. In most mobile communication systems, the time a wavefront takes to pass through the antenna array is much smaller than the bit (or chip) interval Tb [11] . 4.3 Blind Algorithms Instead of using a training sequence or the properties of the receiver array, “blind” algorithms can be applied for weight adaptation as well. Blind Algorithms basically try to extract the unknown channel impulse response and the unknown transmitted data from the received signal at the antenna elements. Even though they do not know the actual bits, Blind Algorithms use additional knowledge about the structure of the transmitted signal, e.g. finite alphabet [11] . If training sequences are used in combination with blind algorithms, they are called semi- blind algorithms which show better performance than temporal reference algorithms or blind algorithms alone [9] . 5. Strategies For Coverage & Capacity Improvement Smart antennas can increase the coverage area and/or the capacity of a wireless communication system. The coverage, or coverage area, is simply the area in which communication between a mobile and the base station is possible. The capacity is a measure of the number of users a system can support in a given area. Three strategies that employ smart antennas, which are range extension: increase coverage, while the interference reduction/rejection and spatial division multiple access (SDMA) approaches seek to increase the capacity of a system. 5.1 Range Extension In sparsely populated areas, extending coverage is often more important than increasing capacity. In such areas, the gain provided by adaptive antennas can extend the range of a cell to cover a larger area and more users than would be possible with omnidirectional or sector antennas. This approach is shown in Figure 1. 5.2 Interference Reduction & Rejection In populated areas, increasing capacity is of prime importance. Two related strategies for increasing capacity are interference reduction on the downlink and interference rejection on the uplink [2] . To reduce interference, directional beams are steered toward the mobiles. Interference to co-channel mobiles occurs only if they are within the narrow beamwidth of the directional beam. This reduces the probability of co-channel interference compared with a system using omnidirectional base station antennas. Interference can be rejected using directional beams and/or by forming nulls in the base station receive antenna pattern in the direction of interfering co-channel users. Interference reduction and rejection can allow Nc (which is dictated by co-channel interference) to be reduced, increasing the capacity of the system [2] . Interference reduction can be implemented using an array with steered or switched beams. By using directional beams to communicate with mobiles on the downlink, a base station is less likely to interfere with nearby co-channel base stations than if it used an omnidirectional antenna. This is depicted in Figure 7. 5.3 Spatial Division Multiple Access Smart antennas also allow a base station to communicate with two or more mobiles on the same frequency using space division multiple access (SDMA). In SDMA, multiple mobiles can communicate with a single base station on the same frequency. By using highly directional beams and/or forming nulls in the directions of all but one of the mobiles on a frequency, the base station creates multiple channels using the same frequency, but separated in space [2] . This approach is shown in Figure 8.
  5. 5. 6. Benefits Smart Antennas can be used to achieve different benefits. The most important is higher network capacity, i.e. the ability to serve more users per base station, thus increasing revenues of network operators, and giving customers less probability of blocked or dropped calls [11] . Also, the transmission quality can be improved by increasing desired signal power and reducing interference. A schematic model of how Smart Antennas work is shown in Figure 9. 7. Application Of SA in 3G Base Stations As an important measurement of enhancing communications system capacity, SA is mainly used in base stations. Future operation frequency in mobile communications system will be higher and the size of antenna will be smaller provided half wavelength antenna element gap. Now I introduce what SA brings for 3G base station as follows [8] : 7.1 Forming many beams It takes SA in base station forming many beams to cover entire cell as an example. A cell can be covered by 3 beams with 120 ° or 6 beams with 60 ° width. Each beam can be treated as an independent cell. When a MS (Mobile Station) leaves a beam covering area for another, the beam will conduct a handoff [5] . 7.2 Forming adaptive beams SA can locate each MS and form the beams covering a MS or MS groups. Thus, each beam may be taken as an intra-frequency cell in order that variable traffic can be covered by changing the shape of beams dynamically. When a MS is moving, it is very favorable to Figure 7: Interference reduction using adaptive antennas (directional beams interfere with fewer cells) [2] Figure 8: Spatial division multiple access (SDMA) using adaptive antennas [2] Figure 9: Smart antenna patterns in a multi-service UMTS system with high data rate interferers and desired low data rate users [11].
  6. 6. control BS transmit power if we select different beams to cover every MS groups, which is available when MS’s are moving in groups or restricted routines [5] . 7.3 Forming beam null By virtue of the difference in incident angels between desired signals and jamming signals, SA may choose proper merging weights to form correct antenna receiving mode (i.e. main lobe focus on desired signals and side lobe focus on main jamming signals) for the purpose of reducing interference more effectively and reducing frequency reuse efficiency in higher proportion. In some sense, SA is a more flexible fan antenna with a narrower main lobe [5] . 7.4 Forming dynamic cell The concept of adaptive beamforming can be generalized to dynamic variation of cell shape, which demands for SA having the capabilities of positioning and tracing MS to adjust system parameters adaptively to meet business requirements. It shows that SA can change cell border and assign some channels for each cell dynamically thereby [5] . 8. Conclusion From a technology point of view, smart antennas can be seen as an extension of the "conventional" resource allocation schemes used in radio communications. In addition to dividing the space into cells, it will now also be possible to employ space division inside each cell. Different degrees of utilization of the spatial dimension are possible, and different steps have been described here. Smart antenna technology is a broad concept and implementations range from simple techniques that involve switching between lobes to advanced algorithms maximizing the received signal-to-interference ratio. Implementation of smart antennas is done using array antennas. The techniques for beamforming with array antennas are well known, and must be employed in both duplex directions for the improvements to be substantial. However, with rapid channel variations it is not a trivial task to provide optimum beamforming, especially for the downlink direction. The use of smart antennas is not purely a radio transmission issue. It also influences network services such as handover and connection setup. Introducing the spatial domain in the resource management system makes this more complex. Several smart antenna testbeds and field trials have been set up and run by manufacturers and research institutions. The first tests allowing commercial traffic over a base station employing smart antennas were performed by Ericsson and Mannesmann Mobilfunk in Germany in the autumn of 1998 [2] . Smart antennae are used for many applications, especially now a days in Wi-Max. They are used notably in acoustic signal processing, track and scan RADAR, radio astronomy and radio telescopes, and mostly in cellular systems like W-CDMA and UMTS References [1] Lal C.Godora. Application of antenna arrays to mobile communications, Part I: Performance improvement, feasibility, and system consideration. Proceedings of the IEEE, July 1997, 85(7): 1031-1060. [2] W. L. Stutzman and G. A. Thiele, Application of Smart Antennas to Mobile Communications Systems [3] Rappaport, T. S., (ed.), Smart Antennas: Adaptive Arrays, Algorithms and Wireless Position Location, New York: IEEE Press, 1998. [4] Tsoulos, G.V., (ed.), “Adaptive Antennas for Wireless Communications,” IEEE Press, 2001.
  7. 7. [5] XIAO Jian, YU Lei, Smart Antenna technology in 3G system, Journal of Communication and Computer, ISSN1548-7709, Volume 4, No.7 (Serial No.32), USA, Jul. 2007. [6] Bellofiore, S., Foutz, J., Balanis, C.A., Spanias, A.S. Smart-antenna systems for mobile communication networks, Part 2: Beamforming and network throughput. Antennas and Propagation Magazine, IEEE, Aug 2002, 44(4): 106-114. [7] LI Shi-he. The principles and realization of smart antennas. Telecommunication Construction, 2001, (4): 22-26. [8] WANG Ji-feng. Smart antenna technology based on software radios. Journal of Nanjing University of Posts and Telecommunications: Natural Science, 2001: 45-47. [9] J. Laurila, Semi-Blind Detection of Co-Channel Signals in Mobile Communications , PhD thesis, Technische Universität Wien, March 2000, www.nt.tuwien.ac.at/mobile/ [10] Jack H. Winters, SMART Antennas For Third Generation TDMA, AT&T Labs - Research, Middletown, NJ 07748, November 27, 2000 [11] Symena Software & Consulting, Smart Antennas – A Technical Introduction

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