Enhanced Cellular Network Performance with Adaptive ... - CiteSeerX

Enhanced Cellular Network Performance with Adaptive Coverage based on Position Location of Mobile Terminals Ch. Dimitriadis1, P.C.F. Eggers2, S. Kyriazakos1, A. Markopoulos, P. Pissaris, Rama.R.T2 and E.D. Sykas1 1

National Technical University of Athens Dept. of Electrical & Computer Engineering, 157 73 Athens, Greece, www.telecom.ntua.gr 2

Aalborg University Center for PersonKommunikation DK-9220 Aalborg, Denmark, www.cpk.auc.dk ABSTRACT Radio resource management is one of the most challenging issues in wireless systems of present and future generation. Lack of bandwidth, increased number of subscribers and high data-rate services, often cause congestion situations in wireless systems. One of the main concerns of cellular operators is to adopt intelligent mechanisms to overcome these network shortcomings. To achieve this, an efficient traffic monitoring is required. Position location of mobile terminals is one of the means to combine measurements performed by the users and their location, resulting in a monitoring system, which consists of databases with a set of network performance indicators. This information can be exploited in a way to predict traffic overload and reconfigure the system on-the-fly. In this paper we tackle the issue of resource management and we describe an adaptive coverage system that is capable to adjust radio resources in an efficient way for the network. Our main concern is to show the potential of the location-based system improvement, the adaptive coverage system architecture and the appropriate antennas that are used. I. INTRODUCTION The work presented in this paper is part of the work performed under the framework of IST-CELLO project. CELLO is related to cellular system optimization based on localization information. One of the activities that are carried out is the efficient system coverage as a result of geographical placement and evaluation of existing network and mobile terminal measurements. For this purpose a system consisting of network components that evaluate the measurements and take decisions for the antenna configuration is implemented. In addition appropriate adaptive antennas that can be integrated in the network are manufactured. The system will be validated and demonstrated in a real cellular networking environment of a cellular DCS1800 operator. In Chapter II we present the general architecture that exploits network measurements and

combines them with the location information, resulting in a GIS with useful key indicators about the system performance. It is explained how this GIS is fed with data and in which terms the system can be improved, exploiting the information in this database. In Chapter III is presented one of the functionalities of the system, namely the adaptive coverage. The adaptive coverage is divided in two parts. The first one is the use of GIS information to enhance coverage by selecting new network plans, while the second one utilizes the GIS information in terms of optimum forming of the antenna radiation pattern. In Chapter IV the expected results and future work are discussed. Finally, in chapter V, we sum up with the conclusions. II. PROBING AND NETWORK SUPPORT BASED ON POSITION LOCATION The main idea is to evaluate OMC measurements and combine them with user’s location to result in a Mobile GIS (MGIS) with structured information about network performance. Above this MGIS, a set of tools is installed that have access to the GIS and control several mechanisms. One of them is the ACT (Adaptive Coverage Tool), which exploits the performance indicators and selects an appropriate antenna pattern. Position location can be achieved over different methods. Some of them require additional measuring units, while others are based on existing measurements that are available in the network. The interface between BTS and BSC, i.e. Abis, is one of the standardized interfaces where information can be extracted and evaluated. This information can be either on-the-fly or at a later time processed resulting in an estimation of the user position. While the user is moving, a set of procedures usually takes place. In addition, there are counters at the network side that are triggered, whenever a call is blocked, whenever a call is terminated due to a failure or even a handover can be executed. The combination of this information is stored in the MGIS, so that the operator can know the system performance at each place. Furthermore, it is possible to access this data and use specific mechanisms to detect at which time congestion is expected. Traffic congestion is

one of the most critical issues in cellular systems. Several studies show how dramatically the blocked calls can increase in cases of congestion. Therefore, the ACT should utilize the available information and change the network planning, either by switching additional antenna elements, or modifying the antenna pattern of an array by using a phase-steered adaptive antenna system solution. This type of switched beam architecture will improve the capacity of GSM / DCS cellular networks, can be achieved by steering the energy to the serving mobile through a series of fixed beams, by forming a narrow beam towards each desired user, the resulting spatial filtering can significantly improve the average SNR in the network [10]. III. ADAPTIVE COVERAGE SYSTEM The Adaptive Coverage System (ACS) concept is the idea of exploiting localization-information for adjusting the antennas in order to achieve an increased network capacity and stability. ACS can be considered as a tool (Adaptive Coverage Tool, ACT) that takes advantage of the information stored in the MGIS. ACT is a web-based application that communicates with the MGIS server (Figure 1). It is responsible for adjusting ACS antenna elements of a specific cell. The adjustment parameters are automatically fed from the MGIS server whenever the network plan changes or when the ACT is turned on. The evaluation of data stored in MGIS by means of applications running on top of MGIS can detect areas where additional capacity is needed. It is possible to observe how the capacity requirements depend on the time of the day and if they are related to special occasions like for example sports events. The ACS controls special base station antenna modules, which can be driven to produce different kinds of radiation patterns. By using prediction tools and MGIS data, the goal is to find an optimum combination of base station antenna patterns for various traffic conditions. In particular, when traffic is localized in hot spots, the less occupied area capacity can be redirected to cover the more distressed areas. The time frame of change in adaptive coverage is in order of 10s of minutes or hours, thus adaptive coverage is not attempting to combat short term or shadow fading/interference, but rather adjust to changes in traffic during the day (i.e. rush hours, special mass events etc).

Figure 1: General architecture of ACS The ACS will be tested in three different operation modes [11]: • Sector relocation: changing bearing angle of a sector towards a desired hot spot area

•

•

Sector focusing: focusing towards major traffic area, sporting event, daily rush hours or where user concentration is high. Resources can be dedicated depending on the areas of high traffic intensity, keeping the same cell layout but modifying beam width to exclude less important areas. In Figure 2 is described the concept of sector focusing, cell layout before/after shrinking. Sector range extension: loaded cells can be covered by sector extension of unloaded cells, keeping the general cell layout area but modifying boundaries.

By controlling sector size, flexibility is brought into the network. Base stations can now effectively borrow neighbor resources as and when required. Increasing or reducing sectors will provide potential capacity gain as well as enabling the network to modify its coverage area at any given time for optimum performance. The Adaptive Coverage System (ACS) concept is an economical and system-independent solution for added network performance compared to adaptive antennas. Cost effectiveness is based on the fact that expensive real-time DSP hardware is not required at the base station. While being a cost-effective solution ACS is believed to be a potential candidate for urban areas where the base station density is high and the capacity problem is most severe. In the implementation of 3G/WCDMA systems the ACS concept may be an alternative to adaptive antennas, which are defined as an optional feature in the specifications. Furthermore the ACS concept allows the effects of the coverage control to be first predicted by a planning tool, while the effects of adaptive antennas cannot be accurately predicted. Base station

before after

Hot-spot area

Figure 2: Example of using ACS in a hot-spot area In CELLO there will be two demos of the adaptive coverage system. In the first demo, the ACS will be implemented using fixed, commercial, antenna elements. The antenna elements will be connected to a custom Switch Box and they will be switched on/off respectively in predefined and discrete positions. The information about the area that needs additional capacity is given by the MGIS. The first demo of the ACS is very simple and feasible to implement since it can be realized by readily available components. The switch box is remotely controlled via a GSM data link. In the second demo, the ACS will be implemented using a more complicated antenna (Modular Antenna Array, MAA). The MAA is expected to be a flexible and challenging solution since it is going to include many

features, which will differentiate the MAA from the existing base station antennas. The MAA is going to be a dual polarized array. In addition, the MAA will be a compact construction, so that it will be aesthetically acceptable. Finally, the MAA is going to have manufacturing flexibility. This means that the array elements can be configured into any array structure (vertical, horizontal) as desired at specific sites. This is also called “Lego Brick” manufacture and is going to be a quite good solution for any site-specific needs. Concerning the Modular Antenna Array design and construction, the main and most important issue, which was investigated, is the choice of the array element. The type of element that will be used is expected to implement the main MAA requirements concerning the ACS objectives. In general, there are many types of elements, which are used for the design of a base station antenna. Two of them, widely used, are the half-wave dipole and the micro strip antennas. As a first step, we investigated which of these two types of elements is appropriate for the Modular Antenna design according to the MAA specifications. Firstly, the half-wave dipole was excluded although it is compliant with the MAA specifications. The results of the study showed that the half wave dipole wasn’t an appropriate choice for the MAA design, since the total array size would be extremely large. The reason for the large size is the necessity for low cross polarization and low mutual coupling between the elements. Another type of element, widely used, is the microstrip antenna element. Microstrip antennas are low profile, conformable to planar and nonplanar surfaces, simple and inexpensive to manufacture using printed-circuit technology. They are mechanically robust when mounted on rigid surfaces, compatible with MMIC designs. When the particular patch shape and mode are selected, they are very versatile in terms of resonant frequency, polarization, pattern and impedance. On the other side, microstrip antennas have some operational disadvantages. The main disadvantages are their low efficiency, low power, spurious feed radiation and narrow frequency bandwidth [13]. Concerning the MAA design, the microstrip antenna element is a good solution since objectives of ACS can be easily achieved. The MAA can be adapted to the Adaptive Coverage System by means of differential antenna configuration (array instead of separate elements in demo 1). By changing the supply input, MAA can dynamically focus and steer the beam to the hot-spot area. In particular, the adaptivity of beams will be implemented, with Butler Matrix network (MAA-BM) as shown in Figure 3. This system will eventually allow dynamic pattern manipulations and appropriate array geometry at sites of an operational system. Butler matrix is a simple beamforming network [7], offers low complexity, doesn’t require baseband signals for beamforming and is flexible for orthogonal beamforming and beam steering [9]. Butler matrix distributes RF signals to radiating elements with almost constant beam crossover, which allows a good coverage pattern and full system gain in the coverage area, but on the other hand, it forms phase-steered beams that squint

with frequency as beamwidth and beam angle are affected by frequency. Multiple beamforming can be possible using MAA-BM with RF switch network by exciting two or more beam ports with RF signals at the same time. As the Butler Matrix is a linear device, it doesn’t prevent implementation of optimum combining or any other diversity scheme in base band signal processing. MAA-BM can generate a number of independent beams directed towards the specified points, so that all the beams are covering a desired region of space. By weighing the signal delivered from the beam ports, an adaptive MAA-BM can extract energy selectively from the desired region of the space and can perform adaptively functions such as tracking and nulling [8]. In order to make the individual beams combine to the dynamically desired pattern, phase shifts can also be inserted between the switch and butler matrix, amplitude weighting could also be include together with the phase shift. When a hot-spot area occurs, the Adaptive Coverage Tool will exploit MGIS information, and then the information is sent through the GSM-Modems to the microcontroller (as in demo 1). The microcontroller sends the appropriate commands to the Butler Matrix and finally the Butler Matrix generates dynamically the radiation beams directed towards the areas that need additional coverage.

Figure 3: Beam Switching with Modular Antenna Array and Butler matrix As a result, a continuous and optimum coverage scheme can be achieved. On the contrary, the ACS with single elements cannot offer continuous coverage (it can offer coverage only to the fixed areas covered by each element). So, assuming that the MGIS offers detailed location information about the hot spot area, the antenna pattern can be fine-tuned and provide additional capacity in the area needed. Obviously, in this way, interference will be kept very low, and the disturbance to ongoing calls will be minimum, compared to the initial solution of separate elements. IV. EXPECTED RESULTS AND FUTURE WORK The system will be validated at a real wireless networking environment of a cellular DCS1800 operator

In Helsinki, Finland. It is expected that at the trial site the congestion will be high. First, the Adaptive Coverage System will not be utilized, so that the basic of performance metrics can be extracted. Then, the MGIS when it predicts congestion will inform the system to use a more suitable planning. Obviously there is going to be an initial plan for switching the antenna elements so that no interference problems will arise. Finally the MAA will be used and the planning should be performed dynamically. It is expected that the hotspot areas will be served in a more efficient way, due to the additional coverage offered by the antennas. In addition, the interference can be minimized as well as the blocking rate. After the system is tested and evaluated, the next step is to apply the system for next generation systems. For that purpose, several aspects are already considered, such as key performance indicators that should be monitored. In addition several modifications in the MGIS should be performed, so that the MGIS will contain the necessary data. V. CONCLUSIONS In this paper we have presented an adaptive coverage system concept, as part of the CELLO architecture. The idea of detecting problematic areas and providing additional coverage was described. The system will be tested in a real cellular system environment using initially switched antenna elements and then a multiple patch antenna array. We strongly believe the ACS concept has a big potential, since cellular systems of present generation cannot respond on the rapidly increased traffic, a situation that is also described as traffic congestion. The system reconfigurability offered by CELLO will enable the automatic network improvement to result in stable systems. The use of switched antennas is the first step towards this achievement while the use of patch-antenna arrays will enable a higher accuracy on the hot-spot adaptive coverage. VI. ACKNOWLEDGEMENT This work has been performed in the framework of the project IST CELLO, which is partly funded by the European Community. The Author(s) would like to acknowledge the contributions of their colleagues from VTT Information Technology, Cosmote Mobile Telecommunications S. A., Center for PersonKommunikation, Elisa Communications Corporation, Motorola S.p.A, Institute of Communication and Computer Systems / National Technical University of Athens, Teleplan AS. VII. REFERENCES [1] M.E Theologou “Mobile Networks”, National Technical University of Athens, Athens, May 1998. [2] Nam Nguyen & Kim – Thoa Nguyen, “Location Management Methods for Mobile Systems”, CS6390 – Section 501, Group 5.13, Spring 98.

[3] D.Plassman , “Location management strategies for mobile cellular networks of 3rd generation”, IEEE VTC ’94, pp. 649-653, 1994. [4] L.J. Ng, R. W. Donaldson and A.D. Malyan, “Distributed architectures and databases for intelligent personal communication networks”, Proc. IEEE Int. Conference on Selected Topics in Wireless Commun, pp. 300-304, 1992. [5] S. Kyriazakos, P. Fournogerakis, G. Karetsos “ Location-Aided Handover in Cellular Networks", WPMC 2001, September 2001, Aalborg, Denmark [6] Bernhard H. Walke, “Mobile Radio Networks: Networking and Protocols”, John Wiley & Sons, 1999. [7] Antenna Feed Networks - Butler Matrices, Anaren Microwave,www.anaren.com [8] Nicolau.E & Zaharia.D, ‘Adaptive arrays’, 1989, Elsevier [9] Digital Beamforming in Wireless Communications, Litva.J & Lo.T.K.Y, 1996, Artech House [10] Smart Antennas for Wireless Communications, Liberti.J.C & Rappaport.T.S,1999, PrenticeHall [11] ACS Requirements & Specifications, D6, CELLOWP4-CPK-D06-006-Apr.doc [12] G. Y. Liu, G. Maguire, “Efficient Mobility Management Support for Wireless Data Services”, in Proceedings of the Vehicular Technology Conference, 1995, p. 902. [13] Antenna Theory, Analysis and design, Second edition, Constantine A. Balanis