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360 cellutions casestudy

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360 cellutions casestudy

  1. 1. CustomerA Optimization Service 360Cellutions Case Study February 2012
  2. 2. P a g e | 3 Mission Statement To bring quantitative improvement in CustomerA network through enhanced visibility, extensive field testing, comprehensive statistical analysis, precise technical recommendations and an efficient follow up process
  3. 3. P a g e | 4 Executive Summary The 360Cellutions Optimization service for the SSS network has been a resounding success. In the short time of four months, 451 recommendations were given by the 3 team out of which 202 have been implemented. 38% of the implemented recommendations resulted in the problem being solved, 41% are under investigation. Only 20% showed no change and 1% showed degradation. All network KPIs have shown a significant improvement: CINR 15%, Throughput 15%, Utilization 5%, Usage 27%, QPSK 8%, BaseDiversity 11%. The details are given in the next section titled Network Improvement Summary. Less than 2% of recommendations have required addition of CapEx (new site or sector). In addition to the considerable network performance improvement, 360Cellutions has provided vital help in other areas. An advanced method of viewing statistics was introduced called SYS, which CustomerA team has appreciated so much that they have decided to model their main statistics interface on the same lines (health-check report). SYS has helped increase network visibility by the design of customized reports like Daily Dashboards, City Reports, Worst-Cell Reports. Comprehensive drive test of the three major cities has been done daily by the 360Cellutions team and analyzed using an advanced post-processing software called FDI, which has revealed issues previously unknown. This has contributed immensely to the successful results mentioned above. A scanning interface called JET was provided by 360Cellutions to address the absence of a scanning tool in CustomerA. Scanning mode drive test is widely regarded as the most relevant and important way of drive testing a nomadic Wimax network like CustomerA’s, JET filled this void with its simple interface and efficient sampling capability. In addition to this, 360Cellutions had noticed around 400 AP sectors’ stats were missing, and hence not visible in any statistics analysis. 360Cellutions provided a solution for making them visible so their performance can be monitored and faults detected and fixed. 360Cellutions has explored new data sources, like Dereg codes, which has given a new perspective on Network Performance, and helped solve chronic problems by correlating these data sources with conventional data sources like AP stats and drive test. A constructive and cordial working relationship between 360Cellutions and CustomerA teams has prevailed and it has been evident in the results.
  4. 4. P a g e | 5 Network Improvement Summary The graphs below show statistical improvement on sectors where recommendations have been implemented. • CINR Good (RF Quality) has improved by 15% • Usage in Mega Bytes has increase much more sharply (27%) than Utilization (5%) showing new traffic added is mostly of good quality and at higher data rates • The above point is further confirmed by two methods: change in coding scheme distribution (QPSK has been lowered by 8% and QAM-64 increased by 4%) and by the fact that Base Diversity has reduced by 11% and replaced by MIMO • Throughput increased by 15% 0 20 40 60 80 100 120 140 3-Oct 11-Oct 19-Oct 28-Oct 5-Nov 13-Nov 21-Nov 30-Nov 12-Dec 20-Dec 28-Dec NESR UL NI CINR Good 0 5 10 15 20 25 30 35 3-Oct 11-Oct 19-Oct 28-Oct 5-Nov 13-Nov 21-Nov 30-Nov 12-Dec 20-Dec 28-Dec RF_DL_Util RF_UL_Util 0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 7,000,000 8,000,000 9,000,000 10,000,000 3-Oct 12-Oct 22-Oct 31-Oct 9-Nov 18-Nov 28-Nov 11-Dec 20-Dec 29-Dec DL sector usage MB Total sector usage MB 0 10 20 30 40 50 60 70 80 90 100 3-Oct 11-Oct 19-Oct 28-Oct 5-Nov 13-Nov 21-Nov 30-Nov 12-Dec 20-Dec 28-Dec QAM64 (%) QAM16 (%) QPSK (%) 0 10 20 30 40 50 60 70 80 90 100 3-Oct 11-Oct 19-Oct 28-Oct 5-Nov 13-Nov 21-Nov 30-Nov 12-Dec 20-Dec 28-Dec MIMOA DL MIMOB DL BaseDiv DL 0 0.2 0.4 0.6 0.8 1 1.2 1.4 3-Oct 10-Oct 17-Oct 25-Oct 1-Nov 8-Nov 15-Nov 22-Nov 30-Nov 11-Dec 18-Dec 25-Dec 1-Jan DL_RF_Throughput
  5. 5. P a g e | 6 Analysis Solution Stats and Drive Analysis On field testing Enhanced Visibility Technical Recommendations Data collection Introduction The mission statement of this project clearly identifies the objective, strategy and methodology for the implementation of the project. The objective of the project is to bring quantitative improvement in CustomerA network performance. The strategy is divided into three phases: Data Collection, Analysis and Solution. This is translated into four distinct sections. 1. Visibility 2. Field Testing 3. Stats and Drive analysis 4. Technical Recommendations This report will cover in detail these four sections. The fifth section of the report will provide the details of the follow up process designed and adopted during this project. The last section, Extra mile, will highlight additional initiatives taken by 360Cellutions to directly and indirectly help accomplish the overall goal of improving the CustomerA network.
  6. 6. P a g e | 7 1. Visibility Telecommunication networks generate a colossal amount of data related to the performance of the network. All of this data is useful and can potentially indicate faults. It’s a challenging task to develop a system to organize this important data and give visibility of network faults to the network engineers. 360Cellutions has provided a comprehensive system of gaining visibility to the CustomerA network and its performance. This can be divided into the following sections, each section will be explained in the following pages:  SYS Service – A method to store and analyze network statistics  KPI Formulating and Threshold – Key Performance Indicator definition and prioritization  FDI Service – A method to store and analyze drive test data  Daily Reports – The creation and design of reports on various network aspects for a variety of audiences  Dereg – A procedure for export and storage of Dereg codes  Alarms – A procedure for export and storage of AP alarms 1. SYS Service SYS is a KPI and statistics analysis tool for cellular networks. It's multi-vendor, scalable and customizable, as per the client requirements. It has a simple and efficient interface and produces comprehensive reports. Stats downloaded from the CustomerA server are loaded in the SYS database through a fully-automated process. SYS is used for the following tasks:  Detailed reports  Worse cell compilation  Intuitive graphical view  Correlation with Alarm logs, Dereg codes and CAPC stats  Multiple time intervals (hourly, daily, BI)  Custom reports  Custom KPI definitions  Multiple level grouping (city, network, cell) SYS provides a comprehensive platform for network stats, organized in the following categories:  Intervals – Daily, Busy Interval and hourly  Entities – CapC, AP  Grouping is done by cities and cells SYS outputs graphical as well as tabular data, an example of a report is given below. Its called Health Check and shows the complete performance of a network entity in one screen:
  7. 7. P a g e | 8 2. KPI formulation and threshold setting 360Cellutions in consultation with CustomerA team formulated a system of Key Performance Indicators (KPIs) to monitor the network efficiently. The different aspects of this initiative are as follows:  A criteria was formulated by 360Cellutions in cooperation with CustomerA team to come up with 5 most important and diverse KPIs which form the Worst Cell Report. This report is regularly used to indicate the faulty cells in the network. For each of these cells HealthCheck is run to confirm the problem and recommend a solution.  HealthCheck is a one page report which gives a complete snapshot of a network entity (sector, AP, city, network etc). The 26 KPIs that form the healthcheck were carefully selected to ensure that all aspects of the entity are represented. 360Cellutions engineers as well as CustomerA team have become familiar with the health check format and in one quick glance they are able to pinpoint the fault. Otherwise this could have taken hours and many issues would have been missed, if the traditional way of looking at tabular data was used.  Some new KPIs were introduced by 360Cellutions to make the stats analysis more comprehensive. An example is the End to End NESR analysis using CapcC stats, and
  8. 8. P a g e | 9 breaking NESR into three parts: Air Interface, Authentication and Registration, which gives the success rate of a new connection over all interfaces. 3. FDI service FDI is a drive test post-processing software, which takes drive based optimization to the next level. It provides optimizers with previously unheard of features which are designed to intelligently pin-point network issues, and effectively solve problems. It has many advanced features, like best server option for scanned mode drives, binning over user defined grids for any layer, theoretical layers of low coverage and interference for scanned mode drives using user defined parameters. As will be shown in the following sections, numerous coverage, interference and other issues were precisely found and rectified with the help of FDI by the 360Cellutions team. 4. Daily Reports  Network Dashboard: contains 5 major KPIs listed for last 2 days. It gives a quick glance at any improvement or deterioration in last 2 days, and is a quick glance for senior management to see the overall network performance. Any deterioration is caught at a glance and hence leads to further analysis and trouble shooting. All Network Dashboards sent can be found on the accompanying DVD.  City Report: contains detailed health check graphs of each city Karachi, Lahore and Islamabad/Rawalpindi. Both daily and Busy Interval analysis are included in this report. All City Reports sent can be found on the accompanying DVD.  Worst Cell Report: contains cells that underperform on a particular day. Performance of cells for this report is analyzed using five performance metrics (KPIs) namely; o Average Uplink Noise and Interference o Network Entry Success Rate o Base Diversity Downlink Slot Utilization o MIMO B Downlink Slot Utilization o Downlink RF Quality by Kilobyte Low (QPSK)  Down Sites: contains detailed health check graphs of cells that are not working. Down Cells are traced using network stat Average Uplink Noise and Interference. It’s an important report and shows cells whose outage could potentially be causing in the loss of revenue and poor coverage. All Down Sites Reports sent can be found on the accompanying DVD.  Low Traffic Cells: contains cells with low usage. This report is generated using stats of last day and a week prior to last day. Only cells which had high usage earlier are included to indicate cells underperforming and discard cells that have low usage regularly. All Low Traffic Reports sent can be found on the accompanying DVD. 5. Deregistration Codes When a customer disconnects from CustomerA’s network it generates a Deregistration reason code depicting the reason for its disconnection. These codes are stored in the network for retrieval and analysis. Only the latest Dereg codes are available in the APs, and older ones are regularly deleted due to limited space on the AP. 360Cellutions, for the first time in the CustomerA network extracted these important codes and used these codes in CustomerA network analysis. These codes are now permanently stored in SYS. Several issues were identified as a result of this analysis. CPEs that were
  9. 9. P a g e | 10 causing KPI deterioration persistently and Sites (AP’s) that were causing degradation have been identified. 6. Alarm analysis Network elements generate alarms whenever an active element malfunctions. 360Cellutions has formulated a process of extracting Network Alarms from CustomerA and Alarms are now stored permanently in SYS.
  10. 10. P a g e | 11 1. Field Testing Field testing is one of the important sources of data for any wireless communications network. On field data collection provides important information related to coverage, interference and over shooting. In this project, 360Cellutions team conducted two different types of field testing. 1. Scan Mode Scan mode drive test collects the RF information of all the frequencies in the network. This is most important and frequent type of field test for Wimax network as it provides information about Coverage level (RSSI), Carrier to Interference Ratio (CINR) and site attributes (BSID, Preamble, frequency). The scan mode field data coupled with state of the art FDI service provided a very detailed drive analysis. The 360Cellutions team detected, low coverage issues, high interference areas, database mismatches, swap sectors and cell over shoots by analyzing scan files through FDI. Initially, Agilent E6474 was used to collect the on field data using Motorola USB Wimax device. Later, scan mode data collection over Green packet was made possible through introduction of JET, a scan mode data collection tool. 2. Dedicated Mode Dedicated mode drive test was conducted to further investigate worse cells detected through stats analysis. It provides information regarding modulation scheme, UL/DL throughput and MIMO type. In this mode relevant sector frequency is locked and drive is done in the coverage area of that cell while uploading and downloading files. Since it provides information related to one cell at a time the dedicated mode campaign was specific to worse cells. In total, the testing was conducted on 46 sites in Karachi (where dedicated mode drive test kit was available). In order to monitor the data collection and analysis activity Cities are divided into clusters of reasonable size. The cluster strategy also helped CustomerA team to implement recommended changes in chunks. Karachi city was divided in 14, Lahore in 17 and Islamabad/Rawalpindi in 6 clusters. Table 3.1 shows the list of clusters with naming convention containing information of the covered area. During field testing speed was kept below 35km/h to get samples for all the 5 frequencies at a particular location.
  11. 11. P a g e | 12 Table 3-1: List of clusters Karachi Lahore Islamabad/Rawalpindi KHI01_E_01 LHR01_E_01 ISB01 KHI01_E_02 LHR01_E_02 ISB02 KHI01_E_03 LHR01_E_03 ISB03 KHI01_E_04 LHR01_E_04 ISB04 KHI01_E_05 LHR01_E_05 ISB05 KHI01_E_06 LHR01_E_06 ISB06 KHI01_E_07 LHR01_E_07 KHI01_E_08 LHR01_E_08 KHI01_E_09 LHR01_E_09 KHI01_E_10 LHR01_E_10 KHI01_E_11 LHR01_E_11 KHI01_E_12 LHR01_E_12 KHI01_E_13 LHR01_E_13 KHI01_E_14 LHR01_E_14 LHR01_E_15 LHR01_E_16 LHR01_E_17
  12. 12. P a g e | 13 Implementation Status The first round of scan mode drive test and analysis is finished in all three cities. Whereas the second round is 60% completed for Lahore. The initial schedule was disturbed due to unavailability of drive testing equipment. Table 3.2 provides the detail of the drive schedule. Scan mode drive test of Karachi, Lahore and Islamabad/Rawalpindi is completed. Figure 3.1, 3.2 & 3.3 provide snap shot of drive test done in Karachi, Lahore and Islamabad respectively. Figure 3-3: Islamabad scan drive updated Figure 3-1: Karachi scan drive update Figure 3-2: Lahore scan drive update
  13. 13. P a g e | 14 This was an important service as it provided the information leading to many fault removal. For example; there are 41 swap sectors detected till date through field testing and analysis. Figure 3.4 shows on of the detected cases. Figure 3-4: Swap sectors detected through Scan Drive. Post drive shows the condition after implementation of recommendation Pre Post
  14. 14. P a g e | 15 2. Network Analysis Network analysis is of two types: 1. Stats and KPI Analysis • Worst Cell Report is a routine process to identify the worst performing cells and give recommendations for performance improvement on a regular basis • Congestion Report identifies the worst congested cells and give recommendations to solve congestion on these cells • Low Traffic Cells Report identifies the lowest traffic cells • Down Sites Report identifies Down sites 2. Drive Data Analysis A drive analysis report on cluster basis, giving details of each problem found in the drive test and giving recommendations for solving these problems The details of stats and drive analysis are given below divided into three sections: Worst Cell Report; Other KPIs analysis; Drive Analysis. Insight into the methodology used and some examples are given to show how this analysis has helped in fixing faults and improving network performance.
  15. 15. P a g e | 16 1. Worst Cell Report Worst cell report contains the daily worst cells of the network due to the following KPIs KPI Name Meaning Criteria Data Sources for Analysis Common Cause and Solution Network Entry Success Rate (NESR) Percentage of times CPEs successfully connect to an AP sector • Entry attempts > 1000 • Peak CPEs daily average > 10 • NESR < 20% • Atleast 2 days • AP stats • Dereg codes Faulty or unauthorized CPEs trying to access. Dereg codes can identify these CPEs which need to be removed or replaced Uplink Noise Interference (NI) High Noise Interference in the Uplink direction • NI > -125 • Atleast 2 days • NI = 95 indicates down sector • AP stats • Alarms Frequency Interference, misaligned ODU, hardware fault High Base Diversity (BD) Instead of using MIMO the AP sector is using Base Diversity affecting the performance adversely • Peak CPEs daily average > 10 • Base Div % = 100% • Atleast 2 days • AP stats • Alarms Transceiver, passive elements and RF head need to be checked for fault Zero MIMO-B MIMO-B enhances sector capacity and average throughput • MIMO-A > 10% • MIMO-B = 0% • Atleast 2 days • AP stats • Alarms Antenna or passive elements need to be checked for fault High QPSK High percentage of QPSK modulation usage • QPSK > 10% • Peak CPEs daily average > 10 • Atleast 2 days AP Stats Bad coverage, faulty hardware A few examples are given below. The details of each recommendation given by 360Cellutions can be found in all the Worst Cell reports given on the accompanying DVD.
  16. 16. P a g e | 17 Poor NESR Example: 0 20 40 60 80 100 120 140 3-Oct 8-Oct 13-Oct 18-Oct 27-Oct 1-Nov 6-Nov 11-Nov 16-Nov 21-Nov 27-Nov 2-Dec 11-Dec 16-Dec 21-Dec 26-Dec 31-Dec 5-Jan 10-Jan 15-Jan 20-Jan 25-Jan 30-Jan 4-Feb 9-Feb NESR UL NI • MUI90_B had poor NESR of below 50% since October 2011 • Dereg codes were analyzed • CPE with MAC 00:1b:dd:77:4d:c9 was found to be sending repeated unsuccessful attempts • Case sent to CompanyA and faulty CPE removed from network • Current NESR stays more than 80%
  17. 17. P a g e | 18 High Base Diversity Example: Zero MIMO-B Example: 0 20 40 60 80 100 3-Oct 11-Oct 19-Oct 30-Oct 7-Nov 15-Nov 23-Nov 2-Dec 14-Dec 22-Dec 30-Dec 7-Jan 15-Jan 23-Jan 31-Jan 8-Feb MIMOA DL MIMOB DL BaseDiv DL • Sector GIJK_C Base Diversity 100% since October 2011 • Reported by 360Cellutions as worst cell • RF Head faulty confirmed by CompanyA operations and fixed • Now very little Base Diversity • Usage and throughput increased by more than 200% 0 500 1000 1500 3-Oct 9-Oct 15-Oct 24-Oct 30-Oct 5-Nov 11-Nov 17-Nov 23-Nov 30-Nov 10-Dec 16-Dec 22-Dec 28-Dec 3-Jan 9-Jan 15-Jan 21-Jan 27-Jan 2-Feb 8-Feb DL sector usage MB Total sector usage MB 0 2 4 6 8 10 3-Oct 9-Oct 15-Oct 24-Oct 30-Oct 5-Nov 11-Nov 17-Nov 23-Nov 30-Nov 10-Dec 16-Dec 22-Dec 28-Dec 3-Jan 9-Jan 15-Jan 21-Jan 27-Jan 2-Feb 8-Feb DL_RF_Throughput • Sector XYZ_A MIMO-B 0% since October 2011 • Reported by 360Cellutions as worst cell • Faulty Hardware fixed • Now MIMO-B about 40% • Usage and peak CPEs increased significantly
  18. 18. P a g e | 19 2. Other KPI based analysis KPI Name Meaning Criteria Data Sources for Analysis Common Cause and Solution Congested Cell (High RF Utilization) Cells with high data utilization which results in poor customer experience due to low data rates •DL RF Utilization > 80% •DL RF Throughput > 4Mbps •6 consecutive days AP stats High number of users with high data usage. Network redesign like downtilt, uptilt of neighbouring cell etc can mitigate this issue Low Traffic Cell (Low Data Usage) Sectors with very low data usage •Peak CPEs daily average < 1 •DL Usage > 50MB •Aleast twice in 7 days AP stats Few users in the vicinity. The sector can be removed and used elsewhere. Down Cell (NI = 95) Sectors with no activity due to a fault •NI = 95 •Peak CPEs daily average = 0 •RF Thput = 0 •RF Usage = 0 AP stats, Drive Hardware faulty needs to be replaced Congested cells report can be found on the accompanying DVD. Low traffic cell report can be found on the accompanying DVD. Down cell report can be found on the accompanying DVD.
  19. 19. P a g e | 20 Down Cell Example: • Sector KRCH_B NI 95 between Dec 18 – 28 • Utilization is 0 • Throughput is 0 • After issue resolution, all stats back to normal
  20. 20. P a g e | 21 3. Drive Analysis Drive test in scanned mode is the primary source of drive data analysis. In a nomadic Wimax network like CustomerA (no mobility) scanned data is the most relevant drive data and it is analyzed comprehensively. The following issues were analyzed in all cluster drives and recommendations for each problem were given in cluster analysis reports. All cluster analysis reports can be found on the accompanying DVD. As has been pointed out earlier dedicated mode drives are only done in specific issues i.e. to confirm if a certain modulation scheme is not available on a cell. Issue Type Meaning Criteria Data Sources for Analysis Common Cause and Solution Low Coverage Insufficient RF coverage for satisfactory user experience •RSSI < -80 •CINR < 10 Scanned Mode Drive No sites nearby, or site not transmitting properly. New site, network redesign or fault resolution. Interference Sectors with very low data usage •RSSI > -80 •CINR < 10 Scanned Mode Drive Wrong frequency assignment, needs to be corrected Swapped Sector Sector radiating in the wrong direction relative to the direction installed N/A Scanned Mode Drive Improper installation, needs to be physically corrected Database Issues Field data and network database mismatch N/A Scanned Mode Drive Either the database needs to be changed or site parameter changed
  21. 21. P a g e | 22 An example of issues found during drive test is given below: Low Coverage: • Snapshot shows Block F Model Town, Lahore has low coverage. • Pre drive test conducted on 28th October 2011 • Following changes requested by 360Cellutions: o LDRC_A: Change mechanical tilt of antenna from -7 to -5 o LHFB_C: Change mechanical tilt of antenna from -7 to -5 • Above changes were implemented by CompanyA on 10th December 2011 • Post Drive test was conducted to validate changes on 10th January 2012 • Post drive plot shows coverage has improved considerably after changing the parameter suggested by 360Cellutions. Pre Post
  22. 22. P a g e | 23 3. Redesign Recommendation The enhanced visibility, extensive on field testing provided the ingredients for comprehensive analysis. To have an impact on network performance, all analysis should lead to precise and practical recommendations. These recommendations are the solution for the observed problem. In this project, 360Cellutions adopted a systematic approach to provide and finalize the recommendations. The types of recommendations were fixed and each type was reached after a standard investigation process. Following are different types of recommendations;  Up Tilt Antenna  Site Reboot  Replace faulty Hardware  Site Health Check  Change Preamble  Check CPE Provisioning  Replace Faulty CPE  Change Azimuth  Down Tilt Antenna  Retune Frequency  Increase Power  Rectify Sector Swap  Enable Stats  Bring Site up  Add new Sector Addition
  23. 23. P a g e | 24 1. Total status Since the start of the project total, 451 technical recommendations are forwarded to CustomerA team for implementation. Table 4-1 provides the details of these recommendations. These precise recommendations are provided after extensive analysis and correlation of different data sources. Table 4-1: Recommendation details Recommendation type No of recommendations Up Tilt 161 Frequency 37 Sector Swap 46 Site Health Check 35 Stats 19 Azimuth 28 Site Down 15 Down Tilt 12 Preamble 13 Sector Reboot 56 Check CPE Provisioning 5 Other 9 Power Increase 9 Replace Faulty CPE 2 Site Reboot 2 Sector Addition 1 Hardware 1 0 40 80 120 160 200 UpTilt Frequency SectorSwap Drive SiteHealthCheck Stats Azimuth SiteDown DownTilt Preamble SectorReboot CheckCPEProvisioning Other PowerIncrease ReplaceFaultyCPE SiteReboot SectorAddition Hardware
  24. 24. P a g e | 25 2. Implementation status Out of total 451 recommendations, 202 recommendations are implemented (45%). The recommendations are verified and implemented by relevant CustomerA departments. The rest, 249 recommendations are being evaluated or under implementation. Once implemented in totality these are bound to bring more improvement in the network performance. Figure 4- 2 shows implementation status per type Figure 4-1: Implementation status per type 0 20 40 60 80 100 120 140 160 180 Implemented Underimplementation
  25. 25. P a g e | 26 3. Improvement Status Once implemented, the effect of recommendation is carefully analyzed by conducting a pre- post benchmarking. So far 38% of implemented recommendations have resulted in network improvement. 41% of implemented recommendations are under investigation. Figure 4-3 shows status pie chart Figure 4-2: Improvement Status Improvement examples Figure 4-4,& 4-5 show pre- post benchmark of implemented recommendations. Figure 4-4: Pre-post benchmarking of Sector down identification for site M7651_D Deteriorated 1% NoChange 20% Solved 38% UnderInvestigati on 41% Deteriorated NoChange Solved UnderInvestigation Pre Post
  26. 26. P a g e | 27 Figure -5: Low coverage removal through uptilt of M4232_C through antenna uptilt Pre Post
  27. 27. P a g e | 28 4. Follow up process Numerous improvement recommendations have been sent to CustomerA from 360Cellutions by analyzing Network Statistics, Deregistration Codes and Network Alarms through SYS tool and Drive Test results through FDI tool. These recommendations are recorded into an automatic database called Tracker. It provides summary reports with implementation and improvement status. It also helps in monitoring the progress of the whole project. A conscious effort is made to keep update process simple and automatic. Figure 5.1 illustrates the flow chart for the tracking process The tracker reports are shared bi-weekly with CustomerA teams to track implementation of change recommendations. Furthermore, a weekly conference call is conducted to discuss important cases under implementation. This strong follow up and tracking process binds all three phases; Data collection, Analysis and solution and is one of the key reasons of achieving good network performance in such a short time span. Figure 5-1: Follow up and tracking process flow chart
  28. 28. P a g e | 29 Agilent JET 5. Extra mile During the course of the project 360Cellutions team added additional value by providing solution and analysis which was out of the project scope. The main objective of these value additions was to facilitate CustomerA team in their network improvement drive. Following are the different initiatives taken during this project. 1. Data collection tool (JET) 360cellutions has developed a new scanning interface: JET. This allowed scan mode drive test to be conducted without the need for a dedicated scanner or Agilent E6474A-X dongle. Table 6-1 shows advantages of JET over Agilent. Figure 6-1 shows a comparative snapshot of JET data collection tool with Agilent. Figure 6-3: Agilent Vs JET Feature Agilent JET Green Packet Compatibility Not compatible with Green Packet, only with Motorola CPE (beceem), which is now discontinued by CustomerA Fully compatible and tested with Green Packet Better Sampling Rate One sample about every 9 seconds One sample every 6 seconds, Comparison shown on a map. BSID representation BSID is not correctly exported for scanned mode BSID correctly exported for scanned mode, makes drive analysis much more precise Map Trail Map trail is not visible, only current location is visible Map trail as well as current location is visible 64-bit OS compatibility Cannot be used on Windows 64-bit machines Can be used on 64-bit as well as 32-bit OS Exporting Exporting of Agilent log files is required to csv format which is used as FDI input (post-processing tool) No need for exporting, the log files can be directly input into FDI Figure 6-1: Snap shot of Agilent and JET Data collection
  29. 29. P a g e | 30 2. Special Feature testing Preamble comprises introductory bits of DL Data Map in Wimax standard. It tells the data about ciphering(permutation) schemes. 360Cellutions initiated series of tests in CustomerA’s network to determine efficient use of Preamble codes. Such efficient utilization and strategic planning of preamble codes can render greater percentage of network resources free as compared to the current utilization of resources, by removing interference in network considerably. 360Cellutions suggested a three phased trial. The Trial included following objective •Phase 1: Effect of Segment ID on interference •Phase 2: Effect of Preamble on interference •Phase 3: Effect of same Segment ID and same Preamble on interference •Phase 4: Effect of PSUC1/3 on interference improvement A detailed testing methodology was shared and agreed with CustomerA team. The result of this trial concluded that PUSC 1/3 cannot be implemented in the CustomerA network due to the older version of software release. The report can be found on the accompanying DVD. 3. Missing Cells Identification While analyzing reports in SYS it was observed that there are a lot cells missing from the AP stats. If there were less than four sectors in the raw stats the entire AP (site) was ignored since there was no way of finding out the sector IDs. 360Cellutions devised a change in the CustomerA script that extracted raw data from EMS. Now each Sector ID is included in the raw stats and hence no sector is ignored when loading raw stats into the SYS server. About 20% of the overall AP sectors had missing stats which were recovered using the solution given by 360Cellutions.
  30. 30. P a g e | 31 6. Conclusion The optimization service provided by 360Cellutions has shown how important it is to continually monitor and analyze network performance to keep a wireless network in a healthy condition. There is room for further improvement. Some important projects have been planned for the future like Spectrum Strategy Optimization. It will also be worth considering an expansion of this service to include other cities.

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