This document discusses key performance indicators (KPIs) and counters for long term evolution (LTE) radio access networks (RANs). It describes various accessibility KPIs such as RRC connection setup success rate, S1 connection setup success rate, and initial E-RAB setup success rate. It also covers retainability KPIs like call drop rate and E-RAB drop rate. Finally, it discusses mobility KPIs including handover success rates for intra-LTE, inter-eNB X2, and inter-eNB S1 handovers. Formulas and measurement points are provided for calculating each of these KPIs and counters.
1.training lte ran kpi & counters rjilSatish Jadav
This document provides an introduction and overview of key performance indicators (KPIs) and associated counters for monitoring the performance of Samsung LTE networks. It describes accessibility KPIs related to session setup success rates, retainability KPIs like call drop rates, integrity KPIs involving throughput measurements, and mobility KPIs covering handover success rates. Formulas for calculating each KPI are provided along with explanations of relevant counters for each performance measurement area.
1) The document describes key performance indicators (KPIs) for measuring the performance of an LTE radio network. It discusses KPIs related to accessibility, retainability, mobility, and latency.
2) Accessibility KPIs measure aspects like call setup success rate, RRC setup success rate, and E-RAB setup success rate. Retainability KPIs measure call drop rate and call setup completion rate. Mobility KPIs measure handover success rates within LTE and between LTE and other technologies.
3) For each KPI, the document provides a definition, calculation formula, and description of which network events and counters are needed to measure the KPI. Baseline
A study on the effect of handover parameters on the network performance will be done in a trial cluster (part of Cerritos)
The parameter change to be implemented as an iterative process with each drive and the results to be compared to analyze the effect of the parameters
This document provides guidelines for LTE radio frequency (RF) network optimization. It describes the network optimization process including single site verification and RF optimization. Key aspects of RF optimization covered include preparing by collecting data and analyzing problems, adjusting parameters such as transmit power and neighbor lists, and ensuring optimization objectives like coverage, signal quality, and handover success rates are met. The document also details common issues like weak coverage, lack of a dominant cell, and cross coverage and methods for resolving them.
This document provides definitions and descriptions for key performance indicators (KPIs) related to an eNodeB. It includes KPIs in areas such as accessibility, retainability, and mobility. The KPIs measure things like call setup success rates, call drop rates, and handover success rates. Templates are provided for standardized KPI definition. The document is intended for network planners, administrators, and operators to understand eNodeB performance.
LTE uses various frequency bands and duplexing techniques to provide high-speed data and peak download speeds of up to 300 Mbps. It supports mobility of up to 350 km/h and uses advanced technologies like OFDM, SC-FDMA, MIMO and turbo coding to achieve low latency and high bandwidth. LTE specifications define channel bandwidths of 1.4, 3, 5, 10, 15 and 20 MHz with modulation schemes of QPSK, 16QAM and 64QAM.
This document provides technical training on optimizing LTE downlink throughput. It discusses:
1. The increasing commercial adoption of LTE networks and rapid growth of LTE users.
2. Challenges in optimizing LTE networks including insufficient analysis capabilities and experience-based adjustments.
3. A proposed optimization scheme involving in-depth analysis of issues like weak coverage, interference and throughput problems to identify root causes and targeted optimization suggestions.
The document discusses fault analysis and troubleshooting of LTE antenna and feeder systems. It describes techniques like RSSI analysis, frequency scanning, interference detection tests, and DTP testing to identify issues like passive intermodulation (PIM) and determine if the fault is in the antenna tower or below. Parameters for simulated load testing and online interference monitoring are also outlined.
1.training lte ran kpi & counters rjilSatish Jadav
This document provides an introduction and overview of key performance indicators (KPIs) and associated counters for monitoring the performance of Samsung LTE networks. It describes accessibility KPIs related to session setup success rates, retainability KPIs like call drop rates, integrity KPIs involving throughput measurements, and mobility KPIs covering handover success rates. Formulas for calculating each KPI are provided along with explanations of relevant counters for each performance measurement area.
1) The document describes key performance indicators (KPIs) for measuring the performance of an LTE radio network. It discusses KPIs related to accessibility, retainability, mobility, and latency.
2) Accessibility KPIs measure aspects like call setup success rate, RRC setup success rate, and E-RAB setup success rate. Retainability KPIs measure call drop rate and call setup completion rate. Mobility KPIs measure handover success rates within LTE and between LTE and other technologies.
3) For each KPI, the document provides a definition, calculation formula, and description of which network events and counters are needed to measure the KPI. Baseline
A study on the effect of handover parameters on the network performance will be done in a trial cluster (part of Cerritos)
The parameter change to be implemented as an iterative process with each drive and the results to be compared to analyze the effect of the parameters
This document provides guidelines for LTE radio frequency (RF) network optimization. It describes the network optimization process including single site verification and RF optimization. Key aspects of RF optimization covered include preparing by collecting data and analyzing problems, adjusting parameters such as transmit power and neighbor lists, and ensuring optimization objectives like coverage, signal quality, and handover success rates are met. The document also details common issues like weak coverage, lack of a dominant cell, and cross coverage and methods for resolving them.
This document provides definitions and descriptions for key performance indicators (KPIs) related to an eNodeB. It includes KPIs in areas such as accessibility, retainability, and mobility. The KPIs measure things like call setup success rates, call drop rates, and handover success rates. Templates are provided for standardized KPI definition. The document is intended for network planners, administrators, and operators to understand eNodeB performance.
LTE uses various frequency bands and duplexing techniques to provide high-speed data and peak download speeds of up to 300 Mbps. It supports mobility of up to 350 km/h and uses advanced technologies like OFDM, SC-FDMA, MIMO and turbo coding to achieve low latency and high bandwidth. LTE specifications define channel bandwidths of 1.4, 3, 5, 10, 15 and 20 MHz with modulation schemes of QPSK, 16QAM and 64QAM.
This document provides technical training on optimizing LTE downlink throughput. It discusses:
1. The increasing commercial adoption of LTE networks and rapid growth of LTE users.
2. Challenges in optimizing LTE networks including insufficient analysis capabilities and experience-based adjustments.
3. A proposed optimization scheme involving in-depth analysis of issues like weak coverage, interference and throughput problems to identify root causes and targeted optimization suggestions.
The document discusses fault analysis and troubleshooting of LTE antenna and feeder systems. It describes techniques like RSSI analysis, frequency scanning, interference detection tests, and DTP testing to identify issues like passive intermodulation (PIM) and determine if the fault is in the antenna tower or below. Parameters for simulated load testing and online interference monitoring are also outlined.
This document describes the design of an LTE network optimization project by a group of students from Taiz University. It includes an introduction to LTE, the network planning process, and LTE system architecture. The network planning section discusses coverage planning including link budget calculations and propagation models, as well as capacity planning considering factors like interference levels and supported modulation schemes. The document also provides an overview of LTE system architecture components including the user equipment, E-UTRAN, EPC, and functions of each. It concludes with a section on LTE radio frequency optimization methods.
LTE KPI Optimization - A to Z Abiola.pptxssuser574918
1. The document discusses LTE post launch optimization, including problem causes, solutions, and case studies.
2. It describes different types of counters used to collect PM statistics, including peg, gauge, accumulator, scan, PDF, DDM, calculated, trigACC, and trigSCAN counters.
3. Potential causes of poor accessibility for E-RAB establishment are discussed, including poor coverage, alarms, high load, hardware issues, high UL interference, PCI conflicts, RACH root sequence index planning, UE camping in wrong cells, wrong system constant settings, and VSWR or cell availability issues.
This document provides formulas and proposed targets for key performance indicators (KPIs) related to LTE network monitoring. It includes KPIs for LTE OSS statistics measured at the network level and LTE drive test KPIs measured through field testing. For each KPI, it provides the detailed formula, measurement methodology, and a brief description. The goal is to establish a framework for initial discussion on monitoring LTE network performance.
The document discusses 4G LTE drive testing. It describes the necessary equipment for drive testing including a notebook, GPS, and LTE dongle. It outlines key LTE radio parameters that are measured like PCI, RSRP, SINR, and MIMO. It also discusses measuring UE state information, throughput, and LTE access procedures including attach requests, random access failures, and E-RAB failures. Finally, it compares the impact of ANR capabilities versus UE capabilities on measuring neighboring cells within and between eNodeBs.
This document discusses LTE CS Fallback features which allow LTE networks to reuse CS infrastructure to provide voice and other circuit switched services. CS Fallback enables LTE terminals to redirect to 2G/3G networks when initiating CS services like voice calls. The key aspects covered include the CS Fallback network architecture using the SGs interface, the combined attach procedure used for location updates, advantages/disadvantages of different CS Fallback mechanisms, and signaling flows for CS Fallback and paging.
1. The document provides Huawei's mobility strategy recommendations for Maxis' LTE network, which involves LTE, UMTS, and GSM networks.
2. The strategy addresses cell selection and reselection procedures in both idle and connected modes between the different RATs and frequencies. It aims to optimize coverage and load balancing through configuration of various priority and threshold parameters.
3. Over multiple revisions from 2012 to 2018, the strategy has been updated based on trials and discussions between Maxis and Huawei to refine the parameter settings and push more users to preferred frequencies like L2600.
This document provides suggestions to help operators reduce call setup time (CST) in benchmark tests. It describes enhancements that can be made to WCDMA RAN, LTE RAN, EPC, IMS, MSS and UDM networks. For each enhancement, it discusses the impacted domains, pros, cons, dependencies and references. The primary focus is on improving CST without compromising network performance. Local teams should evaluate which enhancements fit their specific network conditions and priorities.
Inter-frequency and inter-RAT handovers can be coverage, load, or service based. Coverage-based handovers are triggered by certain A3/A4/A5 events for inter-frequency and B1/B2 events for inter-RAT. The document discusses the parameters involved in measuring cells and configuring handovers, including measurement reports, handover commands, and key performance indicators for analyzing handover issues. Common causes of handover problems include poor downlink quality, interference, and abnormal X2 interface signaling.
This document provides guidelines for LTE radio frequency (RF) network optimization. It describes the network optimization process including single site verification and RF optimization. Key aspects of RF optimization covered include preparing for optimization by collecting data, analyzing problems related to coverage, signal quality and handover success rate, and adjusting parameters like transmit power, antenna tilts and neighboring cell configurations. Common issues addressed are weak coverage, coverage holes, lack of a dominant cell, and cross coverage between cells. Optimization methods and specific cases are presented to resolve different problems.
This document summarizes various LTE KPIs and performance metrics related to random access, RRC connection establishment, ERAB establishment, and issues that may impact them. It provides potential causes for high values or failures in these metrics as well as recommended actions to investigate like checking RF parameters, capacity, licenses, alarms, configuration, and optimizing physical antenna settings.
Huawei - Access failures troubleshooting work shopnavaidkhan
This document provides information on troubleshooting access failures in mobile networks, including:
1. It describes the general call setup procedure and potential points of failure, such as RRC, paging, and RACH access failures.
2. Common causes of access failures are discussed, like RF issues, radio parameter problems, and other miscellaneous causes.
3. Guidance is given on how to identify and resolve different types of failures, including steps to troubleshoot RRC access failures through analyzing configuration, alarms, traffic patterns, and radio parameters.
The document discusses key performance indicators (KPIs) for LTE networks. It describes KPIs related to accessibility, retainability, integrity, and mobility. Accessibility KPIs measure how successfully users can access the network, including session setup success rate, RRC connection success rate, and ERAB establishment success rate. Retainability KPIs evaluate how well services are retained once connected, such as call drop rate and ERAB drop rate. Integrity KPIs relate to throughput, including downlink and uplink throughput. Mobility KPIs cover handover success rates for different types of handovers between nodes. Formulas are provided for calculating many of the KPIs.
Ericsson important optimization parametersPagla Knight
The document lists important optimization parameters for Ericsson including parameters related to system configuration, capacity management, directed retry, handover, HSDPA/EUL, IRAT, and idle mode selection and reselection. It provides descriptions of over 50 parameters that control aspects such as power levels, admission limits, thresholds for cell reselection, and criteria for measurements.
The document discusses key performance indicators (KPIs) for 3G radio networks. It provides an overview of important KPIs such as call setup success rate, call drop rate, and data throughput. It describes methods for measuring KPIs including drive testing, stationary testing, and statistical analysis. The document also discusses how to optimize radio networks by adjusting parameters and resolving issues to improve KPIs like accessibility, retainability, and service integrity. Case studies demonstrate analyzing and troubleshooting KPI issues.
Engineer EMERSON EDUARDO RODRIGUES PRESENTA UNA NUEVA VERSION
THERE ONE NEW ONE PRESENTATION FOR 2G AND 3G ENGINEERING FOR LTE AND PSCORE ENGINEER
ITS VERY SUITABLE FOR YOUR RESEARCH AT ALL LEVELS OF RF ENGINEERING AND PS CS
This document provides an overview and detailed descriptions of Circuit Switched Fallback (CSFB) features in an evolved Radio Access Network (eRAN). It describes CSFB procedures for falling back from an LTE network to UTRAN or GERAN networks to support circuit switched services like voice calls. The document includes sections on CSFB architectures, handover decisions and executions, related interfaces, engineering guidelines, parameters and troubleshooting.
2 g and 3g kpi improvement by parameter optimization (nsn, ericsson, huawei) ...Jean de la Sagesse
The document discusses key performance indicators (KPIs) for 2G and 3G networks and how top telecom vendors like Ericsson, Huawei, and NSN optimize parameters to improve these KPIs. It outlines techniques for reducing TCH blocking, SD blocking, TCH drop, HOSR, TASR, SD drop, and improving paging success rate through actions like changing configuration parameters, enabling features, addressing hardware issues, and optimizing cells physically. The optimization of these parameters can help maintain balance between network throughput, capacity and radio quality while ensuring a seamless transition between 2G and 3G.
1) The document describes key performance indicators (KPIs) for measuring the performance of an LTE radio network. It defines KPIs related to accessibility, retainability, mobility, and latency.
2) Accessibility KPIs measure aspects like call setup success rate, RRC setup success rate, and E-RAB setup success rate. Mobility KPIs evaluate handover success rates within LTE and between LTE and other technologies.
3) Retainability KPIs track metrics such as call drop rate and call setup completion rate. The document also provides details on how to calculate each KPI and which counters are needed to measure the underlying events.
Drive tests are performed to continuously monitor and optimize network performance. Key parameters measured include RxLevel, RxQuality, Frame Erasure Rate, Bit Error Rate, Carrier to Interferer ratio, and Speech Quality Index for GSM networks. For CDMA networks, parameters like RxLevel, TxPower, Carrier Energy to Interference, Carrier to Interferer ratio, and Signal to Noise Ratio are measured. Maintaining these parameters within normal ranges helps ensure quality of service and identify issues needing attention.
The document provides an overview and analysis flow for optimizing the performance of a mobile network. It discusses various problems that can occur like low availability of control channels, congestion on signaling and traffic channels, and high drop call rates. For each problem, it lists probable causes and recommends actions to identify the issue and solutions to resolve it, such as adjusting configuration parameters, adding network capacity, or improving frequency planning. MML commands are also provided to check device logs, resources, and performance statistics for troubleshooting purposes.
The document discusses key performance indicators (KPIs) for an eRAN network. It provides an overview of the KPI system, describing different categories of KPIs including accessibility, retainability, mobility, availability, utilization, traffic, and latency. It then gives detailed descriptions of example KPIs, such as RRC setup success rate, ERAB setup success rate, call drop rate, and handover success rates. Counters for measuring each KPI are also mapped out. The document aims to help monitor the performance of an eRAN network using these standardized KPIs.
1) The document describes key performance indicators (KPIs) for measuring the performance of an LTE radio network. It discusses KPIs related to accessibility, retainability, mobility, and latency.
2) Accessibility KPIs measure aspects like call setup success rate, RRC setup success rate, and E-RAB setup success rate. Retainability KPIs measure call drop rate and call setup completion rate. Mobility KPIs measure handover success rates within LTE and between LTE and other technologies.
3) For each KPI, the document provides a definition, calculation formula, and description of which network events and counters are needed to measure the KPI. Baseline
This document describes the design of an LTE network optimization project by a group of students from Taiz University. It includes an introduction to LTE, the network planning process, and LTE system architecture. The network planning section discusses coverage planning including link budget calculations and propagation models, as well as capacity planning considering factors like interference levels and supported modulation schemes. The document also provides an overview of LTE system architecture components including the user equipment, E-UTRAN, EPC, and functions of each. It concludes with a section on LTE radio frequency optimization methods.
LTE KPI Optimization - A to Z Abiola.pptxssuser574918
1. The document discusses LTE post launch optimization, including problem causes, solutions, and case studies.
2. It describes different types of counters used to collect PM statistics, including peg, gauge, accumulator, scan, PDF, DDM, calculated, trigACC, and trigSCAN counters.
3. Potential causes of poor accessibility for E-RAB establishment are discussed, including poor coverage, alarms, high load, hardware issues, high UL interference, PCI conflicts, RACH root sequence index planning, UE camping in wrong cells, wrong system constant settings, and VSWR or cell availability issues.
This document provides formulas and proposed targets for key performance indicators (KPIs) related to LTE network monitoring. It includes KPIs for LTE OSS statistics measured at the network level and LTE drive test KPIs measured through field testing. For each KPI, it provides the detailed formula, measurement methodology, and a brief description. The goal is to establish a framework for initial discussion on monitoring LTE network performance.
The document discusses 4G LTE drive testing. It describes the necessary equipment for drive testing including a notebook, GPS, and LTE dongle. It outlines key LTE radio parameters that are measured like PCI, RSRP, SINR, and MIMO. It also discusses measuring UE state information, throughput, and LTE access procedures including attach requests, random access failures, and E-RAB failures. Finally, it compares the impact of ANR capabilities versus UE capabilities on measuring neighboring cells within and between eNodeBs.
This document discusses LTE CS Fallback features which allow LTE networks to reuse CS infrastructure to provide voice and other circuit switched services. CS Fallback enables LTE terminals to redirect to 2G/3G networks when initiating CS services like voice calls. The key aspects covered include the CS Fallback network architecture using the SGs interface, the combined attach procedure used for location updates, advantages/disadvantages of different CS Fallback mechanisms, and signaling flows for CS Fallback and paging.
1. The document provides Huawei's mobility strategy recommendations for Maxis' LTE network, which involves LTE, UMTS, and GSM networks.
2. The strategy addresses cell selection and reselection procedures in both idle and connected modes between the different RATs and frequencies. It aims to optimize coverage and load balancing through configuration of various priority and threshold parameters.
3. Over multiple revisions from 2012 to 2018, the strategy has been updated based on trials and discussions between Maxis and Huawei to refine the parameter settings and push more users to preferred frequencies like L2600.
This document provides suggestions to help operators reduce call setup time (CST) in benchmark tests. It describes enhancements that can be made to WCDMA RAN, LTE RAN, EPC, IMS, MSS and UDM networks. For each enhancement, it discusses the impacted domains, pros, cons, dependencies and references. The primary focus is on improving CST without compromising network performance. Local teams should evaluate which enhancements fit their specific network conditions and priorities.
Inter-frequency and inter-RAT handovers can be coverage, load, or service based. Coverage-based handovers are triggered by certain A3/A4/A5 events for inter-frequency and B1/B2 events for inter-RAT. The document discusses the parameters involved in measuring cells and configuring handovers, including measurement reports, handover commands, and key performance indicators for analyzing handover issues. Common causes of handover problems include poor downlink quality, interference, and abnormal X2 interface signaling.
This document provides guidelines for LTE radio frequency (RF) network optimization. It describes the network optimization process including single site verification and RF optimization. Key aspects of RF optimization covered include preparing for optimization by collecting data, analyzing problems related to coverage, signal quality and handover success rate, and adjusting parameters like transmit power, antenna tilts and neighboring cell configurations. Common issues addressed are weak coverage, coverage holes, lack of a dominant cell, and cross coverage between cells. Optimization methods and specific cases are presented to resolve different problems.
This document summarizes various LTE KPIs and performance metrics related to random access, RRC connection establishment, ERAB establishment, and issues that may impact them. It provides potential causes for high values or failures in these metrics as well as recommended actions to investigate like checking RF parameters, capacity, licenses, alarms, configuration, and optimizing physical antenna settings.
Huawei - Access failures troubleshooting work shopnavaidkhan
This document provides information on troubleshooting access failures in mobile networks, including:
1. It describes the general call setup procedure and potential points of failure, such as RRC, paging, and RACH access failures.
2. Common causes of access failures are discussed, like RF issues, radio parameter problems, and other miscellaneous causes.
3. Guidance is given on how to identify and resolve different types of failures, including steps to troubleshoot RRC access failures through analyzing configuration, alarms, traffic patterns, and radio parameters.
The document discusses key performance indicators (KPIs) for LTE networks. It describes KPIs related to accessibility, retainability, integrity, and mobility. Accessibility KPIs measure how successfully users can access the network, including session setup success rate, RRC connection success rate, and ERAB establishment success rate. Retainability KPIs evaluate how well services are retained once connected, such as call drop rate and ERAB drop rate. Integrity KPIs relate to throughput, including downlink and uplink throughput. Mobility KPIs cover handover success rates for different types of handovers between nodes. Formulas are provided for calculating many of the KPIs.
Ericsson important optimization parametersPagla Knight
The document lists important optimization parameters for Ericsson including parameters related to system configuration, capacity management, directed retry, handover, HSDPA/EUL, IRAT, and idle mode selection and reselection. It provides descriptions of over 50 parameters that control aspects such as power levels, admission limits, thresholds for cell reselection, and criteria for measurements.
The document discusses key performance indicators (KPIs) for 3G radio networks. It provides an overview of important KPIs such as call setup success rate, call drop rate, and data throughput. It describes methods for measuring KPIs including drive testing, stationary testing, and statistical analysis. The document also discusses how to optimize radio networks by adjusting parameters and resolving issues to improve KPIs like accessibility, retainability, and service integrity. Case studies demonstrate analyzing and troubleshooting KPI issues.
Engineer EMERSON EDUARDO RODRIGUES PRESENTA UNA NUEVA VERSION
THERE ONE NEW ONE PRESENTATION FOR 2G AND 3G ENGINEERING FOR LTE AND PSCORE ENGINEER
ITS VERY SUITABLE FOR YOUR RESEARCH AT ALL LEVELS OF RF ENGINEERING AND PS CS
This document provides an overview and detailed descriptions of Circuit Switched Fallback (CSFB) features in an evolved Radio Access Network (eRAN). It describes CSFB procedures for falling back from an LTE network to UTRAN or GERAN networks to support circuit switched services like voice calls. The document includes sections on CSFB architectures, handover decisions and executions, related interfaces, engineering guidelines, parameters and troubleshooting.
2 g and 3g kpi improvement by parameter optimization (nsn, ericsson, huawei) ...Jean de la Sagesse
The document discusses key performance indicators (KPIs) for 2G and 3G networks and how top telecom vendors like Ericsson, Huawei, and NSN optimize parameters to improve these KPIs. It outlines techniques for reducing TCH blocking, SD blocking, TCH drop, HOSR, TASR, SD drop, and improving paging success rate through actions like changing configuration parameters, enabling features, addressing hardware issues, and optimizing cells physically. The optimization of these parameters can help maintain balance between network throughput, capacity and radio quality while ensuring a seamless transition between 2G and 3G.
1) The document describes key performance indicators (KPIs) for measuring the performance of an LTE radio network. It defines KPIs related to accessibility, retainability, mobility, and latency.
2) Accessibility KPIs measure aspects like call setup success rate, RRC setup success rate, and E-RAB setup success rate. Mobility KPIs evaluate handover success rates within LTE and between LTE and other technologies.
3) Retainability KPIs track metrics such as call drop rate and call setup completion rate. The document also provides details on how to calculate each KPI and which counters are needed to measure the underlying events.
Drive tests are performed to continuously monitor and optimize network performance. Key parameters measured include RxLevel, RxQuality, Frame Erasure Rate, Bit Error Rate, Carrier to Interferer ratio, and Speech Quality Index for GSM networks. For CDMA networks, parameters like RxLevel, TxPower, Carrier Energy to Interference, Carrier to Interferer ratio, and Signal to Noise Ratio are measured. Maintaining these parameters within normal ranges helps ensure quality of service and identify issues needing attention.
The document provides an overview and analysis flow for optimizing the performance of a mobile network. It discusses various problems that can occur like low availability of control channels, congestion on signaling and traffic channels, and high drop call rates. For each problem, it lists probable causes and recommends actions to identify the issue and solutions to resolve it, such as adjusting configuration parameters, adding network capacity, or improving frequency planning. MML commands are also provided to check device logs, resources, and performance statistics for troubleshooting purposes.
The document discusses key performance indicators (KPIs) for an eRAN network. It provides an overview of the KPI system, describing different categories of KPIs including accessibility, retainability, mobility, availability, utilization, traffic, and latency. It then gives detailed descriptions of example KPIs, such as RRC setup success rate, ERAB setup success rate, call drop rate, and handover success rates. Counters for measuring each KPI are also mapped out. The document aims to help monitor the performance of an eRAN network using these standardized KPIs.
1) The document describes key performance indicators (KPIs) for measuring the performance of an LTE radio network. It discusses KPIs related to accessibility, retainability, mobility, and latency.
2) Accessibility KPIs measure aspects like call setup success rate, RRC setup success rate, and E-RAB setup success rate. Retainability KPIs measure call drop rate and call setup completion rate. Mobility KPIs measure handover success rates within LTE and between LTE and other technologies.
3) For each KPI, the document provides a definition, calculation formula, and description of which network events and counters are needed to measure the KPI. Baseline
The document discusses key performance indicators (KPIs) for evaluating 4G LTE radio network performance. It describes KPIs in four categories: accessibility, retainability, mobility, and latency. Accessibility KPIs measure setup success rates for RRC connection, S1 signaling connection, and EPS bearer. Retainability KPIs measure call drop rates and call setup completion rates. Mobility KPIs measure handover success rates within LTE and between LTE and other technologies. Latency KPIs measure access latency and interrupt latency. Counters and formulas are provided for calculating each KPI.
The document discusses key performance indicators (KPIs) for 3G networks. It covers principles of 3G network optimization, including defining KPIs, monitoring counters, and tuning radio access network parameters. It provides examples of KPIs such as call setup success rate and blocking rate. It also describes new measurements and counters being introduced in the RU20 reporting suite to improve performance monitoring.
1. The document discusses NSA mobility management for Huawei's 5G network, including procedures for adding, changing, and releasing the secondary node (SgNB).
2. Key procedures covered include SgNB addition triggered by the MeNB, intra-SgNB and inter-SgNB PSCell changes, and intra-MeNB and inter-MeNB handovers.
3. NSA mobility is anchored to the LTE network, with the eNodeB delivering NR measurement configurations and processing measurement reports.
IRJET- Verification of AXI IP Core(Protocol) using System VerilogIRJET Journal
This document describes the verification of an AXI IP core protocol using SystemVerilog. It discusses:
1. The AXI protocol has 5 channels for read/write address, data, and response. It uses a handshake process between master and slave devices.
2. The verification environment created a UVM agent with a driver, monitor, and sequencer to generate stimuli. Different test cases were developed and passed using randomization.
3. The AXI protocol design was verified using the Questa simulation tool. Functional coverage and assertions were obtained to measure tested and untested portions of the design.
The document provides instructions for interpreting debug output on routers. It describes 8 steps to configure interfaces and verify routing table updates using the debug ip routing command on routers R1, R2, and R3. The steps have R1 configure its serial and LAN interfaces, and verify routing table updates are shown in the debug output. It also suggests establishing a separate session for R2 to observe debug output changes made on R1. The goal is to observe how the routing tables are updated as interfaces are configured on both routers.
Powerful business model for fixed wireless data using outdoor antennas - PaperAndre Fourie
Paper presented at the 2nd Africa Radio Comms Conference in Johannesburg - Nov 2015
By Andre Fourie
The revenue that can be generated by an LTE base station is influenced by the quality of the signal received by the customer premise equipment (CPE). Most CPE come with omni-directional indoor antennas, but have provision for the connection to external antennas.
Substituting the indoor antennas for directional outdoor antennas has a marked effect on the data transfer speeds of the network. There are two reasons for this. Firstly, outdoor antennas are physically larger than their indoor counterparts and thus have a higher gain. The increase in antenna gain translates directly to an increase in received signal strength. The second advantage is that the outdoor antenna sits in an environment that has much better propagating properties than the indoor antenna. Tests have shown that data speeds 3-5 times faster are possible using external antennas compared to indoor antennas.
It is shown, using a primitive financial model that fairly large financial gains can be made by equipping CPE devices with external antennas.
IRJET- The RTL Model of a Reconfigurable Pipelined MCMIRJET Journal
This document presents two Register Transfer Level (RTL) models for a reconfigurable pipelined multiple constant multiplier (MCM) architecture. The first model uses a ripple carry adder, while the second model replaces it with a carry lookahead adder. Both models are constructed using Verilog and simulated using ModelSim. Simulation results show the second model has a 3.53% higher maximum clock frequency and throughput due to the faster carry lookahead adder. It also has 3.53% lower latency but uses 1.65% more power. The second model provides faster performance with moderate increases in resource usage and power consumption.
A network administrator is troubleshooting connectivity issues between a router and a non-Cisco device running Frame Relay. The exhibit shows the router configuration. The likely cause of the Layer 2 connectivity problem is that the ietf keyword is missing when enabling Frame Relay on the serial interface. Adding this keyword should repair the connectivity issue.
We are going to cover complete list of VoLTE IMS KPI and performance Indicators . This includes :-
VoLTE IMS Control Plane KPI
- RSR : Registration Success Ratio (%)
- CSSR : Call Setup Success Rate (%)
- CST : Call Setup Time (s)
- MHT/ACD : Average Call duration (s)
VoLTE IMS User Plane KPI
- Mute Rate (%)
- MOS Score (1-5)
- RTP Packet Loss (%)
- One Way Calls (%)
Packet Core 4G Network LTE KPI
- Volte Attach Success Rate (%)
- VoLTE QCI=5 Paging Success Rate (%)
- Dedicated Bearer Activation Success Rate (%)
- IMS IP POOL Utilization (%)
- Create Bearer Success Rate (%)
Radio VoLTE KPI
- Call Drop rate (%)
- SRVCC Success Rate (%)
- Handover SR (%)
The document discusses the basic software architecture of a digital switching system. It describes the operating system, database management, and classification of digital switch software. It also provides an overview of a basic call model, including the connect sequence, and discusses the software linkages required during a typical call. Finally, it presents a simplified flow diagram for a call forwarding feature.
The document provides an overview and analysis process for optimizing the W-Paging problem in a network. It begins with collecting network information such as traffic statistics and alarms. The analysis process involves identifying optimization goals, locating specific paging problems, analyzing typical cases, and verifying optimization solutions. Key performance indicators for paging include success rates for various paging types initiated by the core network or radio access network.
9Tuts.Com New CCNA 200-120 New CCNA New Questions 2Lori Head
The output "MTU 1500 bytes" refers to the maximum transmission unit, which is the maximum size of a packet or frame that can be sent in a single piece over a link in a network.
The correct answer is F. The maximum frame size that can traverse this interface is 1500 bytes.
Syed Idrish has over 2 years of experience in network support roles. He currently works at Samsung Electronics troubleshooting backhaul issues like low throughput and VoLTE call quality. Previously he worked at Tikona Digital Network and Vedang Cellular Service in network support and project engineering roles. He has skills in Linux, routing protocols, switching, and troubleshooting networking issues. He is pursuing a CCNP in routing and switching and holds a BE in Electronics and Communications.
The document discusses optimization of a 3G UMTS HSPA radio network in a BSNL service area. It explains that optimization is a continuous process of maintaining and improving network performance by analyzing statistics and drive test data. Successful optimization requires understanding reasons for call failures, capturing call parameters prior to drops, and analyzing call flows. The document outlines parameters used in optimization like BSIC, LAI, latency, and describes the drive test procedure and post-processing tools used to analyze network performance data.
Shajeer P is seeking a position in electronics, communication, or allied software fields. He has over 5 years of experience in telecommunications engineering, including roles with Batco Telecom and Integrated Wireless Solutions. His experience includes tasks like network fault troubleshooting, equipment configuration and software upgrades, radio link installation and optimization, and drive testing to analyze network performance. He is proficient in telecom software like OMS 1410 and has a Bachelor's degree in Electronics and Communication Engineering.
IBM Streams V4.1 and Incremental Checkpointinglisanl
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The document discusses network audit of a radio access network (RAN) in a GSM system. It provides details on:
1) The benefits of network audits in identifying issues, improving quality and processes, and optimizing network design.
2) The steps of a network audit including information gathering, analysis, and recommendations.
3) Key performance indicators measured for the RAN including accessibility, retainability, neighbor parameters, frequency planning, and competitive benchmarks.
4) An example audit of a city's network where data was collected and analyzed to identify problems and make recommendations for optimization.
Basics of performance measurement in umtsEkwere Udoh
This document discusses performance measurement in UMTS networks. It provides definitions for key performance indicators (KPIs) and explains how KPIs can be calculated from raw performance data collected from network elements. Specifically, it notes that proper KPI definitions require considering factors like protocol message types, network topology, and how measurements are aggregated. The document also outlines the basic approach for performance measurement equipment to capture and filter relevant data from UTRAN interfaces in order to compute meaningful KPIs.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
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Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
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What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
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Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
1. Telecom Earth Your One Stop for Telecom Updates, Forum, Discussion and Job Portal
LTE 0
LTE KPIs, Counters & Timers
BY TELECOMEARTH · PUBLISHED DECEMBER 7, 2016 · UPDATED JANUARY 18, 2017
0
SHARES
RAN KPIs & Counters Introduction
RAN KPIs
1. Accessibility
2. Retainability
3. Mobility
4. Integrity
Accessibility KPIs are used to measure
how successfully user is able to access
the network.
Divided in 3 segments, RRC setup, S1
setup & ERAB setup
RRC Connection Setup Success Rate:-
Description
Probability success rate for RRC Connections establishment.
Successful attempts compared with total number of attempts.
KPI Formula
[ConnEstabSucc/ ConnEstabAtt] * 100
ConnEstabAtt: RRC connection establishments attempt count
ConnEstabSucc: RRC connection establishments success count
Unit: Percentage(%)
Measuring point
For statistics on RRC connection establishment
Attempt statistic is counted when the RRC Connection Request
message is received.
Success statistic is counted when the RRC Connection Setup
Complete message is received.
S1 Connection Setup Success Rate
Description
Probability success rate for Logical S1-Connections establishment.
Successful attempts compared with total number of attempts.
KPI Formula
[S1ConnEstabSucc/S1ConnEstabAtt] * 100
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2. S1ConnEstabAtt: S1-connection establishment attempt count
S1ConnEstabSucc: S1-connection establishment success count
Unit: Percentage(%)
Measuring point
For statistics on Logical S1-connection establishment
when the Initial UE message is transmitted, it is counted as Attempt;
when the Initial Context Setup Request message is received, it is
counted as Success.
Initial E-RAB Setup Success Rate
Description
Probability success rate for initial E-RABs establishment.
Successful attempts compared with total number of attempts.
KPI Formula
[EstablnitSuccNbr/ EstablnitAttNbr] * 100
EstablnitAttNbr: E-RAB setup attempt count
EstablnitSuccNbr: E-RAB setup success count
Unit: Percentage(%)
Measuring point
For E-RAB setup statistics
When the Initial Context Setup Request message is received upon
initial call setup, it is counted as Attempt.
When the Initial Context Setup Response message is transmitted, it is
counted as Success.
Additional E-RAB Setup Success Rate
Description
Probability success rate for additional E-RABs establishment.
Successful attempts compared with total number of attempts.
KPI Formula
[EstabAddSuccNbr/ EstabAddAttNbr] * 100
EstabAddAttNbr: Additional E-RAB setup attempt count
EstabAddSuccNbr: Additional E-RAB setup success count
Unit: Percentage(%)
Measuring point
For Additional E-RAB setup statistics
When eNBreceives the E-RAB Setup Request message from MME, it is
counted as Attempt.
After eNBsends E-RAB Setup Response message to MME, it is
counted as Success.
Session Setup Success Rate
Description
Probability success rate of overall initial attach procedure.
Product of RRC connection setup success rate, S1 signaling connection
setup success rate and initial E-RAB establishment success rate.
KPI Formula
(ConnEstabSucc/ ConnEstabAtt) * (S1ConnEstabSucc / S1ConnEstabAtt) *
(EstablnitSuccNbr/ EstablnitAttNbr) * 100
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3. ConnEstabAtt: RRC connection establishments attempt count
ConnEstabSucc: RRC connection establishments success count
S1ConnEstabAtt: S1-connection establishment attempt count
S1ConnEstabSucc: S1-connection establishment success count
EstablnitAttNbr: E-RAB setup attempt count
EstablnitSuccNbr: E-RAB setup success count
Unit: Percentage(%)
Call Drop Rate
Description
Probability abnormally released(call drop) for established
connections.
The call drop statistics are on the calls that are connected
successfully but abnormally dropped due to eNB failure or by the
MME.
KPI Formula
[Call Drop(All type id sum) / (EstabInitSuccNbr+ InterX2InSucc +
InterS1InSucc)] * 100
Call Drop(All type id) : Call Drop count about all type
EstablnitSuccNbr: E-RAB setup success count
InterX2InSucc : X2 HO success count in target eNB
InterS1InSucc : S1 HO success count in target eNB
Unit: Percentage(%)
Measuring point
For Call Drop statistics,
Calls released by the eNB due to user inactivity, normally released by
the MME, and released by the UE duplication are not considered
abnormally terminated.
For established connection statistics,
Successful call connection indicates that the default bearer setup is
successful or incoming handover is successful for a call.
4. ERAB Drop Rate
Description
Probability abnormally released E-RAB for established connections.
This formula expresses E-RAB drop rate with respect to successful E-
RAB attempts, as R2 expresses E-RAB drop rate with respect to total E-
RAB session time.
KPI Formula
ErabDropRate= RelActive/ (EstabInitSuccNbr+ EstabAddSuccNbr) * 100
RelActive: Number of active E-RABs, for which a call is released due
to abnormal operation in eNB.
EstabInitSuccNbr: Number of successfully established initial E-RAB.
EstabAddSuccNbr: Number of successfully established added E-RAB.
Unit: Percentage(%)
Measuring point
For E-RAB drop statistics
E-RABs released by the eNB due to user inactivity and normally
released by the MME are not considered abnormally terminated.
For established E-RAB statistics,
Successful E-RAB establishment considers both of the default and
additional bears setup successful.
Handover Success Rate-Intra LTE
Description
Success rate of overall handover.
Successful attempts compared with total number of handover attempts.
KPI Formula
HO Success Rate = [(IntraEnbSucc+ InterX2OutSucc + InterS1OutSucc) /
(IntraEnbAtt+ InterX2OutAtt + InterS1OutAtt)] * 100
IntraEnbAtt: Intra eNB Handover attempt count
IntraEnbSucc: Intra eNB Handover success count
InterX2OutAtt : X2 Handover attempt count in source eNB
InterX2OutSucc : X2 Handover success count in source eNB
InterS1OutAtt : S1 Handover attempt count in source eNB
InterS1OutSucc : S1 Handover success count in source eNB
Unit: Percentage(%)
Measuring point
Please refer to the following slides for the details of measuring points of
each parameter.
Intra-eNB Handover
Description
Success rate for intra-eNB handover.
Successful attempts compared with total number of attempts.
KPI Formula
[IntraEnbSucc/ IntraEnbAtt] * 100
IntraEnbAtt: Intra eNBHandover attempt count
IntraEnbSucc: Intra eNBHandover success count
Unit: Percentage(%)
Measuring point
For intra-eNB HO statistics
when an intra-handover is decided after the Measurement Report
message arrival, it is counted as Attempt;
When the target cell successfully receives the RRC Connection
Recon guration Complete message from the UE, it is counted as
Success.
Inter-eNB X2 Out Handover
Description
Success rate for X2 Out handover.
5. Successful attempts compared with total number of attempts.
KPI Formula
[InterX2OutSucc / InterX2OutAtt] * 100
InterX2OutAtt : X2 Handover attempt count in source eNB
InterX2OutSucc : X2 Handover success count in source eNB
Unit: Percentage(%)
Measuring point
For X2 handover out statistics
when the X2 Handover Request message can be transmitted to the
target eNB after the inter X2 handover decision following the
Measurement Report message arrival, it is counted as Attempt;
The target eNB transmits the X2 UE Context Release message to the
source eNB when the handover is successfully completed. At this
point, the source eNB is counted as Success.
Inter-eNB S1 Out Handover
Description
Success rate for S1 handover.
Successful attempts compared with total number of attempts.
KPI Formula
[InterS1OutSucc / InterS1OutAtt] * 100
InterS1OutAtt : S1 Handover attempt count in source eNB
InterS1OutSucc : S1 Handover success count in source eNB
Unit: Percentage(%)
Measuring point
For inter S1 handover out statistics
when the S1 Handover Required message can be transmitted to the
MME after the inter S1 handover decision following the Measurement
Report message arrival, it is counted as Attempt;
The MME transmits the S1 UE Context Release Command message to
the source eNB when the handover is successfully completed in the
target eNB. At this point, the source eNB is counted as Success.
Handover Interruption Time
Description
Statistics of the average setup time of the handover interrupt time in the
target eNB for each cell.
PEG
IntraHOTime: Average Inter-eNB HO interrupt time
X2HOTime : Average X2 HO interrupt time
S1HOTime : Average S1 HO interrupt time
Unit: msec
6.
Cell Throughput (MAC Layer)
Description
Statistics data for the MAC layer cell throughput
Average size of the transport block (TB) successfully sent/received,
among the downlink/uplink TBs that the eNB’sMAC allocated to the UE
KPI Formula
AirMacUlThru= [(AirMacByteUl* 8)/(5.12 * AirMacByteUlCnt)]
AirMacDlThru= [(AirMacByteDl* 8)/(5.12 * AirMacByteDlCnt)]
AirMacUlEfctivThru= [(AirMacByteUl* 8)/AirMacTtiUl]*1000
AirMacDlEfctivThru= [(AirMacByteDl* 8)/AirMacTtiUl]*1000
Unit: Kbps
Packet Discard Rate
Description
Drop rate for downlink packet drops of the user plane traf c, and is
counted by E-RAB QoS level(QCI).
Packet drops can occur due to congestion, traf c management etc.
KPI Formula
7. Packet Drop Rate = {[PdcpSduDropRateDl+ (1 –PdcpSduDropRateDl/ 10^6)
* PdcpPduDropRateDl] / 10^6} x 100
PdcpSduDropRateDl: DL PDCP SDU packet drop rate on the downlink
that occurred for one minute at PDCP layer
PdcpPduDropRateDl: DL PDCP PDU packet drop rate on the downlink
that occurred for 10 seconds at RLC layer
Unit: Packet Drop Rate (%), PdcpSduDropRateDl&
PdcpPduDropRateDl(ppm)
Measuring point
For PDCP SDU Drop Rate statistics
When buffer over ow occurs at the PDCP layer, PDCP SDU will be
discarded.
For PDCP PDU Drop Rate statistics,
When buffer over ow occurs at the RLC layer, PDCP PDU will be
discarded.
Packet Delay
Description
Statistics data for the DL PDCP SDU delay de ned in the standard 3GPP
TS 36.314 for each QCI.
Average DL PDCP SDU delay per QCI
This measurement refers to packet delay for DRBs. For arrival of packets
the reference point is PDCP upper SAP. For successful reception the
reference point is MAC lower SAP
KPI Formula
Packet Delay
PdcpSduDelay: PDCP SDU delay on the downlink.
Unit: msec
Measuring point
For DL PDCP SDU delay statistics
From the point in time when PDCP SDU arrives to the point in time
when the last piece of PDCP SDU was received by the UE according to
received HARQ feedback information.
Block Error Rate (BLER)-Post HARQ
Description
Block Error Rate (BLER) is an error rate of data transmission of
PDSCH/PUSCH after all HARQ procedures.
KPI Formula
DlResidualBLER= [ DlTransmission_Nacked_Retrans3 /
DlTransmission_Retrans0 ] * 100
DlTransmission_Nacked_Retrans3 : Count of the 3rd PDSCH HARQ
retransmission failure
DlTransmission_Retrans0 : Count of the initial PDSCH HARQ
transmissions
UlResidualBLER= [ UlTransmission_Nacked_Retrans27 /
UlTransmission_Retrans0 ] * 100
UlTransmision_Nacked_Retrans27 : Count of the 27th PUSCH HARQ
retransmission failure
UlTransmission_Retrans0 : Count of the initial PUSCH HARQ
transmission
Unit: Percentage(%)
Retransmission Rate (DL/UL)
Description
Retransmission rate of DL and UL user traf c.
Number of retransmitted blocks compared with total transmitted blocks.
KPI Formula
Retransmission Rate DL = [(DlTransmission_Retrans1 +
DlTransmission_Retrans2 + DlTransmission_Retrans3) /
(DlTransmission_Retrans0 + DlTransmission_Retrans1 +
DlTransmission_Retrans2 + DlTransmission_Retrans3)] * 100
Retransmission Rate UL =[(UlTransmission_Retrans1 +
UlTransmission_Retrans2 + UlTransmission_Retrans3 + … +
UlTransmission_Retrans27) / (UlTransmission_Retrans0 +
UlTransmission_Retrans1 + UlTransmission_Retrans2 +
UlTransmission_Retrans3 + … + UlTransmission_Retrans27)] * 100
Unit: Percentage(%)
Summary
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8.
LTE Timers:-
LTE
Timers
Function at Start/Stop/Expiry
T300
>>Starts at the RRC connection REQ transmit
>>Stops at the Receipt of RRC connection setup or reject message OR at the cell
reselection time OR upon abortion of connection establishment by Higher layers
(L2/L3).
>>At the expiry performs the actions
T301
>>Starts at the RRC Connection Re-establishment REQUEST
>>Stops at the Receipt of RRC Connection Re-establishment OR
RRC Connection Re-Establishment REJECT message OR
When selected cell becomes unsuitable to continue further
>>At expiry, it Go to RRC_IDLE mode
T303
>>Starts when access is barred while performing RRC CONNECTION
ESTABLISHMENT for MO(Mobile Originating) calls
>>Stops while entering RRC_CONNECTED and upon cell re-selection mode
>>At expiry, Informs higher layers about barring alleviation
T304
>>Starts at the Receipt of RRC CONNECTION RECONFIGURATION message along
with Mobility Control Info OR at the receipt of mobility from EUTRA command
message including CELL CHANGE ORDER
>>Stops at the successful completion of HANDOVER to EUTRA or CELL CHANGE
ORDER is met
>>At expiry, it performs action based on need.
1. In the case of CELL CHANGE ORDER from E-UTRA OR intra E-UTRA handover,
initiate the RRC connection re-establishment procedure.
2. In case of HANDOVER to E-UTRA, perform the actions de ned as per the
speci cations applicable for the source RAT.
T305
>>starts when access is barred while performing RRC CONNECTION
ESTABLISHMENT for MO signaling
>>Stops when entering RRC_CONNECTED and when UE does cell re-selection
>> At expiry, Informs higher layers about barring alleviation
T310
>>Starts when UE detects PHY layer related problems (when it receives N310
consecutive out-of-sync INDs from lower layers)
>>Stops 1. When UE receives N311 consecutive in-sync INDs from lower layers/
2. Upon triggering the HANDOVER procedure
3. Upon initiating the CONNECTION RE-ESTABLISHMENT procedure
>> At expiry, if security is not activated it goes to RRC IDLE else it initiates the
CONNECTION RE-ESTABLISHMENT Procedure
T311
>>Starts while initiating RRC CONNECTION RE-ESTABLISHMENT procedure
>>stops upon selection of suitable E-UTRA cell OR a cell using another RAT
>>At expiry it enters RRC IDLE state
T320
>> Starts upon receipt of t320 or upon cell re- selection to E-UTRA from another RAT
with validity time con gured for dedicated priorities (in which case the remaining
validity time is applied).
>>Stops upon entering RRC_CONNECTED state, when PLMN selection is performed
on request by NAS OR upon cell re-selection to another RAT
>> At expiry, it discards the cell re-selection priority info provided by dedicated
signaling
T321
>>starts upon receipt of measCon g including a reportCon g with the purpose set
to reportCGI
>> Stops at either of following cases:
1. Upon acquiring the information needed to set all elds of globalCellId for the
requested cell
2. upon receipt of measCon g that includes removal of the reportCon g with the
purpose set to reportCGI
>> At expiry initiates the measurement reporting procedure, stop performing the
related measurements and remove the corresponding measID