WCDMA/UMTS RADIO NETWORK PLANNING FOR DIFFERENT TRAFFIC AND MOBILITY MODELS Dr. H. M. EL Badawy National Telecommunication Institute, Cairo, Egypt
[email protected] Abstract – Nowadays, there is a great interest in 3G networks planning process which enable users to have different applications with different rates. WCDMA/UMTS is an example of such networks. Unlike 2G planning techniques, UMTS planning process requires care about both uplink and downlink simultaneously. In this paper, the planning process is done by simulation techniques that allow analyzing different network parameters e.g.: coverage, capacity and QoS. Different network case studies will be investigated, which will include: mixed traffic, MS power, mobility models, and user distribution. Finally, the performance will be evaluated by means of system parameters such as SHO probability.
:ﻤﻠﺨﺹ ﺍﻟﺒﺤﺙ
ﻴﺘﺯﺍﻴﺩ ﺍﻹﻫﺘﻤﺎﻡ ﺍﻵﻥ ﺒﻌﻤﻠﻴﺔ ﺍﻟﺘﺨﻁﻴﻁ ﻟﺸﺒﻜﺎﺕ ﺍﻟﺠﻴل ﺍﻟﺜﺎﻟﺙ ﻭ ﺍﻟﺘﻲ ﺘﺴﺘﺨﺩﻡ ﺘﻘﻨﻴـﺎﺕ ﺘﺘـﻴﺢ ﻟﻠﻤـﺴﺘﺨﺩﻡ ( ﺃﺤـﺩUMTS) ﺍﻟﻌﺩﻴﺩ ﻤﻥ ﺍﻟﺘﻁﺒﻴﻘﺎﺕ ﺫﺍﺕ ﺍﻟﻤﻌﺩﻻﺕ ﺍﻟﻤﺨﺘﻠﻔﺔ ﻭ ﻴﻌﺘﺒﺭ ﺍﻟﻨﻅﺎﻡ ﺍﻟﻌﺎﻟﻤﻲ ﻟﻼﺘﺼﺎﻻﺕ ﺍﻟﻤﺘﺤﺭﻜﺔ ﺃﻫﻡ ﺍﻷﻤﺜﻠﺔ ﻟﻬﺫﻩ ﺍﻟﺘﻘﻨﻴﺎﺕ ﻭ ﺍﻟﺘﻲ ﺘﺘﻁﻠﺏ ﺇﺴﺘﺨﺩﺍﻡ ﺃﺴﺎﻟﻴﺏ ﺘﺨﻁﻴﻁ ﺘﺠﻤﻊ ﻓﻲ ﺁﻥ ﻭﺍﺤﺩ ﺒﻴﻥ ﺍﻟﻘﻨﻭﺍﺕ ﺍﻟﺨﺎﺼـﺔ ﺒﺎﻹﺭﺴﺎل ﻤﻥ ﻭ ﺇﻟﻰ ﺍﻟﻨﻅﺎﻡ ﻭ ﺫﻟﻙ ﻋﻠﻰ ﻋﻜﺱ ﺍﻷﺴﻠﻭﺏ ﺍﻟﻤﺘﺒﻊ ﻓﻲ ﺘﺨﻁﻴﻁ ﺃﻨﻅﻤﺔ ﺍﻟﺠﻴل ﺍﻟﺜﺎﻨﻲ ﻭ ﻴﺘﻨﺎﻭل ﻫﺫﺍ ﺍﻟﺒﺤﺙ ﻋﻤﻠﻴﺔ ﺍﻟﺘﺨﻁﻴﻁ ﻟﺘﻠﻙ ﺍﻟﺸﺒﻜﺎﺕ ﺒﺎﻹﻋﺘﻤﺎﺩ ﻋﻠﻰ ﻨﻤﺎﺫﺝ ﺍﻟﻤﺤﺎﻜﺎﺓ ﻭ ﺍﻟﺘﻲ ﺘﺘﻴﺢ ﺘﺤﻠﻴل ﻭ ﺩﺭﺍﺴﺔ ﻟﻠﻤﻌﺎﻤﻼﺕ
ﺍﻟﻤﺨﺘﻠﻔﺔ ﻟﻠﻨﻅﺎﻡ ﻤﺜل ﺍﻟﺘﻐﻁﻴﺔ ﻭ ﺍﻟﺴﻌﺔ ﺒﺎﻹﻀﺎﻓﺔ ﺇﻟﻰ ﺠﻭﺩﺓ ﺍﻟﺨﺩﻤﺔ ﻜﻤﺎ ﻴﻘﺩﻡ ﺍﻟﺒﺤﺙ ﺩﺭﺍﺴﺔ ﻟﻤﺨﺘﻠﻑ ﺤـﺎﻻﺕ ﻭ ﺃﻭﻀﺎﻉ ﺍﻟﺘﺸﻐﻴل ﻟﻠﻨﻅﺎﻡ ﻭ ﺍﻟﺘﻲ ﺘﺸﺘﻤل ﻋﻠﻰ ﺩﺭﺍﺴﺔ ﻟﺘﺄﺜﻴﺭ ﺨﺩﻤﺔ ﻤﺯﻴﺞ ﻤﻥ ﺍﻟﺨـﺩﻤﺎﺕ ﺍﻟﻤﺨﺘﻠﻔـﺔ ﻭﺍﻟﻘـﺩﺭﺓ
ﺍﻟﺨﺎﺼﺔ ﺒﻭﺤﺩﺍﺕ ﺍﻟﻌﻤﻼﺀ ﻭ ﺩﺭﺍﺴﺔ ﻟﻠﻨﻤﺎﺫﺝ ﺍﻟﻤﺨﺘﻠﻔﺔ ﻟﻠﺘﺤﺭﻙ ﻭ ﻜﺫﻟﻙ ﺃﻤﺎﻜﻥ ﺘﻭﺍﺠـﺩ ﺍﻟﻤـﺴﺘﺨﺩﻤﻴﻥ ﺒﺎﻟﻨـﺴﺒﺔ ﻷﻤﺎﻜﻥ ﺍﻟﻤﺤﻁﺎﺕ ﻭ ﺴﻴﺘﻡ ﺘﻘﻴﻴﻡ ﺘﻠﻙ ﺍﻟﺤﺎﻻﺕ ﺒﺩﺭﺍﺴﺔ ﻤﻌﺎﻤﻼﺕ ﺍﻟﺸﺒﻜﺔ ﻤﺜل ﺇﺤﺘﻤﺎﻟﻴﺔ ﺍﻟﻤﻨﺎﻭﻟﺔ ﺍﻟﻤﺘﻭﻗﻌـﺔ ﻓـﻲ .ﺍﻟﻨﻅﺎﻡ 1
Keywords: WCDMA planning, Radio Planning Tool, 3G Planning Process, Performance analysis of UMTS networks.
I
INTRODUCTION
The third-generation (3G) systems such as the Universal Mobile Telecommunications System (UMTS) introduces variable data rates on the air interface, as well as the independence of the radio access infrastructure and the service platform. For users this makes available a wide spectrum of circuitswitched or packet data services through Wideband Code Division Multiple Access (WCDMA). The variable bit rate and mixed traffic on the air interface have presented a lot of potentials for both operators and users, but also challenges to network planning and optimization. UMTS planning phases cannot be separated into coverage and capacity planning as in the 2G wireless networks. For post-2G systems data services start to play an important role. Mixed services require the whole planning process to overwhelm a set of modifications [1]. One of the modifications is related to the Quality of Service (QoS) requirements. So far, it has been adequate to specify the speech coverage and blocking probability only, but it is increasingly necessary to consider the indoor and in-car coverage probabilities. In the case of UMTS the problem is multi-dimensional [2]. For each service the QoS targets have to be set and naturally also met. In practice this means that the tightest requirement shall determine the site density. In addition to the coverage probability, the packet data QoS criteria are related to the acceptable delays and throughput. Estimation of the delays in the planning phase requires precise modeling for user behavior and understanding of the functions of the packet scheduler. In order to study various topics related to radio network planning for WCDMA/UMTS system a network simulator has been introduced in [3],[4] and [5]. In addition, the simulator has been adapted for supporting multi rate and multi user distributions. Various scenarios can be studied separately. Not only voice users or high data rate users can be studied, but also heterogeneous traffic scenarios can be analyzed. The paper is organized as follows: Section II will briefly discuss the simulation of the planning process. Section III, is introducing the proposed scenarios and the operation parameters based on the real cases and pre-published work [6],[7],[8]. Section IV, will illustrate the obtained results and discusses the different parameters that may affect the planning process based on the proposed case studies. Section V, will introduces the paper conclusions and future work. 2
II
SIMULATION OF THE PLANNING PROCESS
Radio system planning is a process that defines the stages, visits in the area, measurements, planning, documentation required to provide a desired radio network plan for a certain geographical area. Moreover, the radio system planning process has to be defined carefully and carried out in different phases in order to maximize; • Coverage • Capacity • Quality of service (QoS) And manage the strong influences between them. These three areas must all be optimized in order to achieve a cost-efficient and overall high Quality of Service radio network. Three major radio system planning phases are: • Initial planning or Dimensioning • Detailed radio system planning • Network optimization and monitoring A - Dimensioning Dimensioning is the first phase of the radio system planning process and its purpose is to initially draft the radio network configuration and deployment strategy for the long-term. This work could also be called a strategy of radio system planning because the aim is to define the essential radio parameter values and technologies in order to deploy the network. B - Detailed Radio Network Planning Detailed radio planning is the second phase in the radio system planning process. After defining the required site density and site configurations for the area of interest in the dimensioning phase (based on the traffic and coverage threshold requirements), the required radio network has finally to be designed and implemented. In dimensioning it was assumed that traffic is evenly distributed. Also, it was assumed in dimensioning that propagation is similar for all the cells. Thus all the cells are identical in dimensioning. The detailed radio network planning takes into account the real site locations, the propagation conditions calculated on digital maps and real user distributions based on the operator's traffic forecasts, where the traffic distribution is used to allocate the predicted traffic to the planned cells. This may lead to situations in which the load between the cells can vary remarkably, some cells may have a load that is very close to the maximum acceptable load and some cells may have a fairly low load. In the detailed planning phase coverage targets are also checked as it can be quite 3
different between the cells due to propagation environment and due to traffic distribution. Detailed Radio Planning includes; • Configuration planning • Coverage planning • Capacity planning • Code and frequency planning C - Network Optimization and Monitoring Network optimization is a process to improve the overall network quality as experienced by the mobile subscribers and to ensure that network resources are used efficiently. WCDMA systems are very sensitive to interference, so it is important not to receive much of it. Means of controlling interference include optimizing: • Site locations and configurations (sectorization). • Height, direction, beam-width and tilt of antennas. • Antenna installations (cable loss). • Usage of mast head amplifiers (MHA). The optimization phase is an adjustment process based on real life changes that were not taken into account in the original radio system planning, which was based on the coverage threshold requirements and traffic forecasts. The WCDMA system needs continuous monitoring due to the variation of mobile users’ location and traffic behavior all the time. This monitoring requirement is only emphasized in the WCDMA because the traffic demand can vary strongly and this variation influences directly the radio network quality. The better and more accurately the traffic amount and locations can be modeled the better and more efficiently (cost, quality, etc.) the radio network can be designed and implemented. The indicators that should be monitored are, for example: traffic, soft handoff, dropped calls, throughput. Many of the listed indicators should be collected on a cell and service basis because it may give some directions on how to optimize the performance of the network. In order to achieve the different phases of the planning process, radio planning tool (RNP) is used for representing both of the network and user parameters. Network parameters include detailed information about the base stations such as: antenna type, height, gain, beam-width and operating frequency. The user parameters include detailed user information such as: location, data rate, traffic type, velocity, and mobile station antenna gain. The workflow supported by a typical Radio Network Planning (RNP) tool is presented in Figure (1) [4]. 4
Figure 1: Workflow supported by RNP tool [4] III
NETWORK SCENARIOS AND SYSTEM PARAMETERS
In this section, a group of scenarios for a possible coverage/capacity analysis are given. First the network scenario and the traffic distribution are introduced. Then the needed parameters are presented. The operational parameters are: UMTS/WCDMA, 2.1GHz carrier frequency. The network is consisting of 25 sites; each one is divided into three sectors. The service area is a square of 100Km2. The area is considered as a business area i.e. dense urban traffic model. The user mobility model is considered as a mixed speed user varying from pedestrian case (5Km/h), moderate speed of (60Km/h) and highway speed (90km/h). Each subscriber has the possibility of moving in any direction. In addition, two types of user distributions over the area will be investigated. The first one is the uniform distributed users over the area under study. The second one is Gaussian distributed users over the area under study. Also, the effect of varying the maximum output power from each MS will be studied. The number of users is varying from 1000 to 10000 subscribers. The users' different and or mixed data rates will be taken into consideration as a one of the main key features of the 3G services. As an illustration of the traffic map, a uniform user distribution is presented. Figure 2 shows the distributions for both of BTS's and the case of having 1000 subscribers with different data rates. The user distribution is assumed to be uniformly 5
distributed over the service area according to the ratios presented in table 1. These ratios are assumed for different traffic mix between different classes of rates ranging from voice traffic (8kbps) to high speed packet switched users (384kbps). Table 1. Traffic distribution [5],[6] Traffic Type Voice (8Kbps) Data class1 (64kbps) Data class2 (144Kbps) Data class3 (384Kbps)
Percentage 70% 20% 7% 3%
Figure 2:. The distribution of BTS's and users The most important parameters used in the simulation are introduced in table 2. Table 2. Parameters used in the example [4] Max. MS TX power Max. BTS TX power Max. allowed uplink load Path loss model Voice activity BTS antennas MS antennas BTS/MS noise figure BTS/MS losses
21dBm 43dBm 50% UMTS vehicle mode 0.67 (speech); 1.0 (data) 65°/17dBi Omni/ 1.5 dBi 5dB/7dB 3dB/1.5dB 6
The simulation scenarios may be collected in the shown flow char presented in figure 3. IV
RESULTS AND ANALYSIS In this section, examples for the obtained results may be illustrated as in the following figures. The criteria that had been used in the simulation process is as illustrated in figure3.
Figure.3. Scenarios Criteria
For the uniform user distributions scenarios, the analysis and simulation had been done in order to find out the effects on the soft handoff probabilities for the main link (1 connection) and also, for the other candidates (2,3,4, and 5 connections). This study had been done from different point of views. First of all, the effect of cell crossing (i.e. the user MS speed) on the probability of having only one connection which means that there is no need for handoff system request. The results of this case are shown in figure 3. In addition the effect on the cell loading is shown in figure 4.
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SHO Vs MS Speed for uniform distributed users Prob. of one connection (no handoff request) %
85
80
5Km/h 60Km/h 90Km/h 75 2000
4000
6000
8000
10000
No# of Users
Figure. 3. SHO Vs MS Speed for uniform distributed users It may be illustrated from figure 6 that, as the MS speed increases, the possibility of having more cell cross over will be increased. So, the probability of handoff request is increasing. On the other hand the possibility of having more customers will consume the system resource at the node B (the UMTS BTS). In order that, the probability of having one connection is increasing as the number of customers increase. It may be illustrated from figure 4 that, as the MS speed increases, the possibility of having more cell-loading. When the density of calls increases the loading factor will increase, as a result capacity of the system will increase. Cell Loading vs MS Speed for uniform distributed users 50
45
Cell loading %
40
35
30
5Km/h 60Km/h 90Km/h
25
20 2000
4000
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8000
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No# of Users
Figure. 4. Cell loading vs MS Speed for uniform distributed users Figure 5, will illustrate the study of the MS max power effect on the probability of handoff requests. The case will study the effect of MS power levels around the nominal power (21dBm). 8
SHO main connection Vs MS Max power for uniform distributed users 86
Prob. of having one connection (%)
84
82
80
78
10dBm 76
21dBm 31dBm
74
2000
4000
6000 No# of Users
8000
10000
Figure. 5. SHO main connection vs MS Max power for uniform distributed users It may be illustrated from figure 8 that, as the MS max power increases, the possibility of having more than one connection is decreased. This may be explained as a result of having MS power that will be sufficient to be listen by another sites. It may be noticed that, as the number of the customers increases, the difference between the probabilities of having one connection will decreases. This may be explained as follows, as the number of customers' increases, the limitations in the radio resources becomes more and more restricted. So, the probability of having one connection will be, approximately, independent of the MS max power [7], and [8]. In order to study the effect of having central mall (or dense business area) in the middle of the service area, this may be simulated by considering Gaussian user distribution all over the area and concentrated around the middle point of the service area. In this scenario, the effect of having different MS max power will be investigated. The MS power will vary around the nominal MS max power (21dBm) [9]. But, in this scenario, the obtained results will focus on the probabilities of having multi-connection. The probability of having one connection means that there is no need for handoff. But on the other hand, having 2-connections means that, there are two active BTS are servicing the current MS. For illustration, the MS number is chosen to be 8000 subscriber; all of them are using voice applications. The obtained results of the Gaussian distribution case is shown in figure 6.
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SHO all connection Vs MS Max power for Gaussian distributed users 100 10dBm 21dBm 31dBm
Handoff probability(%)
80
60
40
20
0 1
2
3
No# of Connections
4
5
Figure. 6. SHO for all connections vs MS Max power for Gaussian distributed users It may be illustrated from figure 6 that, as the MS max power increases, the possibility of having more than one connection will increase. This may be explained as a result of having MS power that will be sufficient to be listen by another sites. In other words, when MS power increases, soft handoff probabilities will increase [10]. This is due to; there will be more than BTS will receive a signal from the user. V
CONCLUSIONS
In order to examine the complex interaction of coverage and capacity in network performance analysis of WCDMA a 3rg generation network simulator has been developed and modified for supporting heterogeneous traffic distributions and mixed traffic analysis. Also, the MS max power effects on the system performance had been studied for different traffic distributions. In addition, optimization strategies for planning 3rd generation networks has been discussed. Furthermore, practical solutions have been proposed for some problems that may face the network planning team, especially for high data rates and large amount of traffic handling which is one of the main objectives in the roll-out of 3G services.
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References [1] A. Wacker, J. Laiho-Steffens, K. Sipilä, M. Jäsberg, "Static simulator for studying WCDMA radio network planning issues", IEEE VTS Proceedings of Vehicular Technology Conference 1999 spring, Houston, Texas, May 1999, pp. 2436-2440. [2] H. Holma, Z. Honkasalo, S. Hämäläinen, J. Laiho, K. Sipilä, A. Wacker, Radio network planning, WCDMA for UMTS, John Wiley & Sons, 2001. [3] J. Laiho-Steffens, A. Wacker, P. Aikio, "The impact of the radio network planning and site configuration on the WCDMA network capacity and Quality of Service", IEEE VTS Proceedings of Vehicular Technology Conference 2000 spring, Tokyo, Japan, May 2000, pp. 1006-1010. . [4] J. Laiho, K. Raivio, P. Lehtimäki, K. Hätönen, O. Simula, "Advanced Analysis Methods for 3G Cellular Networks", Report A65, Publications in Computer and Information Science, Helsinki University of Technology, 2002. [5] J. Laiho, M. Kylväjä, A. Höglund, "Utilization of Advanced Analysis Methods in 3G Networks", IEEE VTS Proceedings of Vehicular Technology Conference 2002 spring, Birmingham, Alabama, pp. 726-730. [6] H. Kaaranen, A. Antuaunen, L. Laitinen, S. Naghian, V. Niemi , UMTS Networks Architecture, Mobility and Services, John Wiley & Sons, 2nd Edition, 2006. [7] M. St-Hilaire, S. Chamberland, and S. Pierre, "Global and Sequential Approaches for UMTS Network Design", paper# 491 in Proceeding Communications and Computer Networks (CCN2005) – USA, Oct. 2005 [8] Dailly, N.; Martins, P.; Godlewski, P.,"Performance evaluation of L2 handover mechanisms, for Inter-Radio Access Networks", Vehicular Technology Conference, 2006. VTC 2006-Spring. IEEE 63rd Volume 1, 2006 Page(s):491 - 495 [9] Jie Zhang; Jun Yang; Aydin, M.E.; Wu, J.Y.; "Mathematical Modeling and Comparisons of Four Heuristic Optimization Algorithms for WCDMA Radio Network Planning",Transparent Optical Networks, 2006 International Conference on Volume 3, June 2006 Page(s):253 - 257 [10] Cardeiro, J.; Correia, L.M., "Optimization of Base Station Location in UMTS-FDD for Realistic Traffic Distributions", Personal, Indoor and Mobile Radio Communications, 2006 IEEE 17th International Symposium on., Sept. 2006 Page(s):1 - 5
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