Advanced WCDMA Analysis of XYZ

Prepared by Ian Hung

November 30, 2007

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Table of Contents 1 Introduction................................................................................................................. 3 2 Network Modeling with ASMT, Urban Model, and Attribute Analysis .................... 4

2.1 Asserting ASMT Modeling................................................................................. 4 2.2 Asserting Urban-WCDMA 850 Model............................................................... 4 2.3 Asserting Attribute Text File .............................................................................. 5 2.4 Attribute Plot....................................................................................................... 6

3 WCDMA Analysis with Live Traffic (Run 1)............................................................ 9 3.1 Coverage Report and Ec/NO, RSCP, HSDPA Plots .......................................... 9

4 WCDMA Analysis with Live Traffic x 8 (Run 2).................................................... 15 4.1 Analysis of DL R99 TCH Power Load............................................................. 21 4.2 Analysis of DL Code Blocking......................................................................... 22 4.3 Recommendations to solve high DL Power Load and high DL code blocking 22

5 Appendix................................................................................................................... 24

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1 Introduction This report fulfills all required deliverables set forth in ABC. The purpose of this assignment was to familiarize ourselves with the work flow of applying ASMT and Urban models and in asserting live traffic data for WCDMA analysis.

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2 Network Modeling with ASMT, Urban Model, and Attribute Analysis Instead of using a generic model to calculate our unmasked pathloss bins as performed in Assignment XYZ, a combination of Automatic Sector Model Tuning (ASMT) and Urban Model definitions are used to better represent the network. 2.1 Asserting ASMT Modeling Given the provided AMI database and parameters specified in the assignment, 47 cells were modeled with ASMT.

2.2 Asserting Urban-WCDMA 850 Model After defining the Urban-WCDMA 850 model according to the assignment, the model is applied to the following list of sites that are less than or equal to 20m in antenna height. Table 1: List of Cells with Antenna Heights less than or equal to 20m Site Sector Technology Antenna Type Azimuth ElectricMechanGroundHeight AGLT41KJ Ant-T41KJU1 WCDMA 850 ERC_KRE-101-1916_MET09_850MHz 30 8 0 0 12.7

Ant-T41KJU2 WCDMA 850 ERC_KRE-101-1916_MET10_850MHz 120 9 0 0 12.7Ant-T41KJU3 WCDMA 850 ERC_KRE-101-1916_MET09_850MHz 250 8 0 0 12.7

T02KJ Ant-T02KJU1 WCDMA 850 ERC_KRE-101-1916_MET09_850MHz 50 8 0 0 14.5Ant-T02KJU2 WCDMA 850 ERC_KRE-101-1916_MET09_850MHz 170 8 0 0 14.5Ant-T02KJU3 WCDMA 850 ERC_KRE-101-1916_MET09_850MHz 290 8 0 0 14.5

T72LP Ant-T72LPU1 WCDMA 850 ERC_KRE-101-1916_MET09_850MHz 50 8 0 0 14.5Ant-T72LPU2 WCDMA 850 ERC_KRE-101-1916_MET10_850MHz 170 9 0 0 14.5Ant-T72LPU3 WCDMA 850 ERC_KRE-101-1916_MET09_850MHz 290 8 0 0 14.5

T32KA Ant-T32KAU1 WCDMA 850 ALG_7920-00_MET09_850MHz 50 8 0 0 14.6Ant-T32KAU2 WCDMA 850 ALG_7920-00_MET09_850MHz 170 8 0 0 14.6

T22KA Ant-T22KAU1 WCDMA 850 ERC_KRE-101-1916_MET09_850MHz 50 8 0 0 15Ant-T22KAU2 WCDMA 850 ERC_KRE-101-1916_MET09_850MHz 170 8 0 0 15Ant-T22KAU3 WCDMA 850 ERC_KRE-101-1916_MET08_850MHz 290 7 0 0 15Ant-T32KAU3 WCDMA 850 ALG_7920-00_MET09_850MHz 290 8 0 0 16.5

T52KP Ant-T52KPU1 WCDMA 850 ERC_KRE-101-1916_MET10_850MHz 50 9 0 0 18Ant-T52KPU2 WCDMA 850 ERC_KRE-101-1916_MET09_850MHz 170 8 0 0 18Ant-T52KPU3 WCDMA 850 ERC_KRE-101-1916_MET10_850MHz 290 9 0 0 18

T60KJ Ant-T60KJU1 WCDMA 850 CSA_X65-20-AA_MET10_850MHz 50 10 0 0 19Ant-T60KJU2 WCDMA 850 CSA_X65-20-AA_MET09_850MHz 170 9 0 0 19Ant-T60KJU3 WCDMA 850 CSA_X65-20-AA_MET09_850MHz 290 9 0 0 19

T25KP Ant-T25KPU1 WCDMA 850 ERC_KRE-101-1916_MET10_850MHz 50 9 0 0 19.8Ant-T25KPU2 WCDMA 850 ERC_KRE-101-1916_MET10_850MHz 170 9 0 0 19.8Ant-T25KPU3 WCDMA 850 ERC_KRE-101-1916_MET09_850MHz 290 8 0 0 19.8

T24K Ant-T24KU1 WCDMA 850 ERC_KRE-101-1916_MET09_850MHz 30 8 0 0 20Ant-T24KU2 WCDMA 850 ERC_KRE-101-1916_MET10_850MHz 170 9 0 0 20Ant-T24KU3 WCDMA 850 ERC_KRE-101-1916_MET09_850MHz 290 8 0 0 20

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2.3 Asserting Attribute Text File To visualize the cells for which ASMT or Urban Model have been applied and thus validate the previous steps, an attribute text file is generated and later imported into TCP and plotted. The original attribute file used to generate the plots is appended below: Table 2: Print out of Attribute Text File Type Attribute Version 1 Date 11/28/2007 11:00 Comment Attribute:UTRAN cell:Integer:Model Number::1:0:100 Attribute:UTRAN cell:Text:Model:Pred Model:9999 model Attribute:UTRAN cell:Decimal number:Height::0.00:-9.22E18:9.22E18:2 UTRAN cell Model Number Model Height T01KJU1 0 9999 27.7 T01KJU2 0 9999 21.8 T01KJU3 0 9999 27.7 T01KU1 0 9999 33.2 T01KU2 0 9999 33.2 T01KU3 0 9999 33.2 T02KAU1 0 9999 47 T02KAU2 0 9999 47 T02KAU3 0 9999 47 T02KJU1 1 Urban 14.5 T02KJU2 1 Urban 14.5 T02KJU3 1 Urban 14.5 T02KU1 0 9999 41 T02KU2 0 9999 41 T02KU3 0 9999 41 T05KU1 0 9999 49 T05KU2 2 ASMT 49 T05KU3 2 ASMT 49 T06KAU1 0 9999 35.6 T06KAU2 0 9999 35.6 T06KAU3 0 9999 35.6 T06KQU1 0 9999 33.5 T06KQU2 0 9999 33.5 T06KQU3 0 9999 33.5 T06KU1 0 9999 47.5 T06KU2 0 9999 47.5 T06KU3 0 9999 47.5 T07KPU1 0 9999 45 T07KPU2 0 9999 45 T07KPU3 0 9999 45 T07KU1 0 9999 45.7 T07KU2 0 9999 45.7 T07KU3 0 9999 45.7 T08KU1 0 9999 71.1 T08KU2 0 9999 71.1 T08KU3 0 9999 71.1 T09JKU1 0 9999 43 T09JKU2 2 ASMT 40 T09JKU3 0 9999 42 T09JU1 0 9999 59 T09JU2 2 ASMT 62 ... [excerpt]

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2.4 Attribute Plot With the attribute text file generated, the data is imported into TCP. The following plots are generated:

Figure 1: Attribute Plot (0=9999, 1=Urban, 2=ASMT)

8Figure 2: Attribute Plot (Gradient of Antenna Heights [m])

3 WCDMA Analysis with Live Traffic (Run 1) Live traffic data is pulled from the switch. After much data manipulation into the proper format, WCDMA traffic is assumed to be similar to GSM traffic and scaled according to the various Data (R99), Speech, HSDPA, and Video bearers. Having imported our traffic data into TCP, Monte Carlo analysis can be performed with greater accuracy instead of formerly assuming an even distribution of traffic throughout the selection area. Certain locales can be biased with greater traffic and thus better show actual utilization of the network which is particularly crucial in formulating our Ec/No predictions in varied suburban/urban environments.

3.1 Coverage Report and Ec/NO, RSCP, HSDPA Plots With live traffic data loaded, the following coverage report and plots are generated (colours are based on definitions in Assignment XYZ): Table 3: Coverage Report from Run 1 BEST SERVER STATISTICS FOR GIVEN THRESHOLD Channel: WCDMA 850-1037 Service: WCDMA bearer Video AREA: XYZ TOTAL AREA (km²): 609.74 COVERAGE AREA (km²): 601.62 COVERAGE AREA (%): 98.67 Threshold DL CPICH margin: 0 Threshold DL TCH margin: 0 Threshold UL TCH margin: 0 CATEGORY TOTAL AREA (km²) COVERAGE AREA (km²) COVERAGE AREA (%) 1 FreshWater 28.69 28.52 99.4 2 Ocean 0 0 0 3 Coniferous Forest 10.01 9.8 97.93 4 Deciduous Forest 4.95 4.88 98.55 5 Open Land 272.42 268.82 98.68 6 Airports 9.89 9.6 97.1 7 Industrial 119.11 118.01 99.08 8 Urban 3.97 3.94 99.14 9 Dense Urban 0.71 0.71 99.87 10 Core Urban 0.17 0.17 100 11 Wetland 0 0 0 12 Transportation Corridors 14.66 14.49 98.83 13 Low Density Urban 27.71 27.34 98.67 14 High Density Urban 117.44 115.33 98.2 15 Unknown 0 0 0

Figure 3: Ec/No Prediction [Run 1]

11Figure 4: RSCP Prediction [Run 1]

12Figure 5: HSDPA Bit Rate Prediction [Run 1]

13Figure 6: Neighbour List for T25KAU2

14Figure 7: Neighbour Plot for T25KAU2

4 WCDMA Analysis with Live Traffic x 8 (Run 2) Traffic data is multiplied by a factor of 8 times and a similar process is repeated as before. The coverage report and our usual plots paired with their corresponding delta plots are shown below: Table 4: Coverage Report from Run 2

COVERAGE AREA (km²): 524.79 COVERAGE AREA (%): 86.07 Threshold DL CPICH margin: 0 Threshold DL TCH margin: 0 Threshold UL TCH margin: 0 CATEGORY TOTAL AREA (km²) COVERAGE AREA (km²) COVERAGE AREA (%) 1 FreshWater 28.69 22.43 78.18 2 Ocean 0 0 0 3 Coniferous Forest 10.01 8.98 89.7 4 Deciduous Forest 4.95 3.66 73.82 5 Open Land 272.42 225.37 82.73 6 Airports 9.89 6.94 70.22 7 Industrial 119.11 110.07 92.41 8 Urban 3.97 3.88 97.67 9 Dense Urban 0.71 0.68 95.18 10 Core Urban 0.17 0.17 97.87 11 Wetland 0 0 0 12 Transportation Corridors 14.66 13.37 91.23 13 Low Density Urban 27.71 24.92 89.93 14 High Density Urban 117.44 104.31 88.82 15 Unknown 0 0 0

Figure 8: Ec/No Prediction [Run 2]

17Figure 9: Ec/No DELTA Plot [magnitude of 6dB to 0dB difference in 1dB step]

18Figure 10: HSDPA Bit Rate Prediction [Run 2]

19Figure 11: HSDPA Bit Rate Delta Plot [magnitude of 600Kbps to 0Kbps difference in 100Kbps step]

20Figure 12: Soft Hand Over Map Prediction [Run 2]

4.1 Analysis of DL R99 TCH Power Load The print out of the sectors with the Highest DL R99 TCH power load is attached below. Please refer to Section 4.3 for commentary. Table 5: Top 5 Sectors with Highest DL R99 TCH Power Load Name R99 DL traffic power (dBm) T78LU1 42.681107 T25KAU2 42.597843 T08KU3 42.595 T06KQU3 42.566982 T76KPU2 42.423832

Figure 13: Distribution of R99 DL Traffic Power Average of R99 DL traffic power (dBm) Total 38.42415349 Var of R99 DL traffic power Total 11.83967647 StdDev of R99 DL traffic power Total 3.440883095

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4.2 Analysis of DL Code Blocking The five greatest offenders to the network in DL blocking are calculated by dividing the number of User Blocked by the # of Attempts and are listed below (Please see the following Section 4.3 for commentary): Table 6: Top 5 Sectors with Highest DL Code Blocking WCDMA module--Statistical results for system parametersService #attempts %served #Insuff.CPI#Insuff.DL #Insuff.UL #DL overLo#Blocked U#Blocked D#Blocked C#Blocked H#Blocked s #Pkt Data U#Pkt Data U#Pkt Data U#Blocked uA-DCH_category12 2474.4 34.99434 206.3 0 0.2 0 0 0 0 31.4 0 0 787.4 612.5 1370.6WcdmaBearer Speech 3655.3 90.09657 306.4 0 0.4 26 0 0 0 14.4 0 0 0 0 14.8WCDMA bearer Video 147.1 77.70224 11.8 17.3 0 2.4 0 0 0 0.6 0 0 0 0 0.7WcdmaBearer Data 1484.8 71.84133 127.1 102.4 0.1 66.1 0 0 5.3 57.6 0 0 1043.8 375.6 59.5 Summary 7761.6 68.80282 651.6 119.7 0.7 94.5 0 0 5.3 104 0 0 1831.2 988.1 1445.6 WCDMA module -- Statistical results for site parameters. Service-A-DCH_category12 Site Name #Attempts Users Served Users Blocked % Users Blocked T25KA 40.8 9.2 31.6 77.5% T40K 40.3 9.3 31 76.9% T78L 40.7 9.5 31.2 76.7% T76K 36.3 9.5 26.8 73.8% T06KQ 35.8 9.4 26.4 73.7%

4.3 Recommendations to solve high DL Power Load and high DL code blocking

With 8 times GSM traffic, we observe EcNo and resulting HSDPA Bit Rate to suffer.

In evaluating our DL R99 TCH Power, we find that most of the cells exhibit 37dBm or greater power utilization. If we dissect the data further and taking example of our worst offender, T78LU1, we find that its azimuth is aimed 130 degrees (as opposed to our standard 50 degrees) and is extremely close to its neighbours. This can cause severe pilot pollution, large soft handover boundaries, and thus diminish our Ec/No performance and ultimately affecting our overall bit rate for the area. The delta plots clearly validate this phenomenon (HSDPA bit rate fringe is shown in red with a difference of 600Kbps or greater).

ADCH /HSDPA bearer exhibited the greatest blocking. However, it can also be noted that R99 data performance is the second worst offender. Again, we find that T78L is also one of the worst offenders for code blocking and therefore this validates our data obtained before. Moreover, four of the five cells are also listed as consuming the most amount of DL R99 TCH Power.

Recommendations to solve both of these problems are to improve the underlying Ec/No performance of the network. As seen from the 34% served ADCH bearer and with majority of sites tipping the scale at around 38dBm power utilization, the overall network will need to be optimized as opposed to just a handful of sites. We need greater density

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of cells with more defined coverage boundaries (which entail possibly shorter structures, antennas with sharper beam pattern isolation, more effective downtilts above and beyond the current MET settings, etc.)

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5 Appendix

Figure 14: Traffic Distribution Plot (Dark Areas = Higher Traffic)

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